--- title: "AI Agents for SOX Testing & Internal Audit" description: "Bead AI's agents run your existing SOX testing plans end to end: pull evidence, test controls, and draft working papers with a full decision log." url: "https://usebead.ai/" --- # AI Agents for Internal Audit We automate 80% of manual work, so you can focus on navigating the risk. [Request a demo](https://usebead.ai/contact) The team previously worked at Meta, OpenAI, EY, KPMG, 11x, BlackRock, DeepMind and GoCardless. Bead is backed by a16z speedrun. ## Automating control testing workflows end-to-end From managing evidence requests, to testing, to marking up documentation. AI agents follow your existing testing plans step by step, producing auditable decision logs at every stage. No setup or custom configuration required. ### Coverage Automate testing 100% of controls, reducing overall testing time by 70% ### Cost savings Reduce reliance on co-sourcing. No more knowledge drain and turnover risk ### Churn Keep your best auditors by removing toil, and letting them focus on knowledge work ## What Can you do with Bead AI? ### Process any evidence Test any evidence, no matter how complex. Test whole populations, not just limited samples. ### Test any controls with AI Test using existing testing attributes. Get fully auditable results, traced back to every data point used. ### Generate support in your format Generate support in native Excel format, fully customized to your templates. ## Control testing with AI Upload your existing testing plan and Bead AI’s agents follow it step by step. No configuration needed. The AI evaluates samples, identifies exceptions, and produces a complete decision log showing every judgment it made and why. [Book a call](https://usebead.ai/contact) ## Supporting documentation Bead AI automatically produces working papers after each test, marked up with linked evidence and structured exception narratives. Templates are fully customizable to match your organization’s formatting standards. Reviewers spend their time on exceptions and judgment calls – not on copying evidence into spreadsheets. [Book a call](https://usebead.ai/contact) ## How is Bead AI different? | | Today | With Bead AI | | --- | --- | --- | | Testing speed | Days–weeks per control | Minutes per control | | Evidence collection | Hours of mapping and validation | Instant validation | | Sample sizes | Capped by time and capacity | Full population coverage | | Audit trail | Manual documentation | Automatic decision logs | | Scalability | Linear with headcount | Parallel AI agents | | Data security | Varies — third-party risk | SOC 2 Type II, no data training | ## Runs Where Your Data Lives ### Cloud Managed multi-tenant with industry-leading logical tenant separation. ### Private Cloud Dedicated single-tenant with custom data residency. ### On-Premises Inside your network. LLM calls use zero-retention APIs. [Learn more about our deployment options →](https://usebead.ai/platform/deployment) ## Designed for auditors, built for Enterprise [![AICPA SOC for Service Organizations](https://usebead.ai/images/aicpa-soc.png)](https://trust.usebead.ai/) ### SOC 2 Type II Certified See our [trust center](https://trust.usebead.ai/) to learn more. ### Private Data Stays Private Your evidence never trains a model. Only the minimum context a test needs reaches a provider, under zero retention. ### Control Data Residency Stored and processed in the US — or in your own environment. --- --- title: "Bead AI Blog: SOX Testing, ITGC & Audit Automation" description: "Field notes from the Bead AI team on automating SOX and ITGC testing with AI agents: evidence collection, tool comparisons, and working papers." url: "https://usebead.ai/blog" --- # Latest blog posts Field notes on automating SOX testing with AI agents. ### [Introducing collaboration mode](https://usebead.ai/blog/collaboration-mode-comments-on-control-tests) Sep 3, 2026 · Today we are releasing collaboration mode. Do all of your testing, from collecting evidence to final reviews, without leaving the platform. ### [Step-by-Step: Pick a Workiva Alternative for Audit Automation](https://usebead.ai/blog/step-step-pick-workiva-alternative-audit-automation) Jul 27, 2026 · A four-step process for replacing Workiva: build a scorecard, compare alternatives, run a 90-day pilot on your own data, and make the business case. ### [AI Agents for SOX Compliance: Automating Audit Testing & Workpapers](https://usebead.ai/blog/ai-agents-sox-compliance-automating-audit-testing-workpapers) Jul 24, 2026 · How AI agents cut manual SOX work: they collect evidence, test controls, flag exceptions and draft workpapers your external auditor can follow. ### [Bead AI as a Workiva Alternative for Internal Audit Automation](https://usebead.ai/blog/bead-ai-workiva-alternative-internal-audit-automation) Jul 23, 2026 · Where Bead AI and Workiva differ on SOX testing: Workiva manages the workflow, Bead's agents execute the tests and produce the working papers. ### [Best Platforms for Automating SOX and ITGC Compliance 2026](https://usebead.ai/blog/sox-itgc-automation-ai-works-tools-lead-2026) Jul 22, 2026 · The platforms that automate SOX and ITGC compliance in 2026, ranked on test execution, evidence collection and audit-ready output. ### [Agentic AI for SOX Controls Testing](https://usebead.ai/blog/agentic-ai-sox-controls-testing) Mar 12, 2026 · How agentic AI tests SOX controls: evidence collection, full-population testing, exception analysis and an auditor-ready trail of every decision. ### [Audit Software Comparison: Top Tools for Internal Audit Teams in 2026](https://usebead.ai/blog/audit-software-comparison-top-tools-internal-audit-teams-2026) Mar 12, 2026 · AuditBoard, Workiva, Diligent and AI-native platforms compared on testing execution, evidence handling, working papers and price for 2026. ### [Best AI for SOX Testing: How to Evaluate Solutions and Why AI-Native Platforms Win](https://usebead.ai/blog/best-sox-testing-tool) Mar 12, 2026 · Five criteria that separate SOX workflow tools from AI-native platforms that actually execute tests, cover full populations, and document the result. --- --- title: "Agentic AI for SOX Controls Testing: How It Works" description: "How agentic AI tests SOX controls: evidence collection, full-population testing, exception analysis and an auditor-ready trail of every decision." url: "https://usebead.ai/blog/agentic-ai-sox-controls-testing" published: 2026-03-12 author: "Alexey Zanin" --- # Agentic AI for SOX Controls Testing ![Illustration for Agentic AI for SOX Controls Testing](https://usebead.ai/images/blog/agentic-ai-sox-controls-testing.svg) ## The evidence execution gap in SOX Agentic AI for SOX is agentic software that runs testing procedures end to end under auditor review: collecting evidence, applying control logic, flagging exceptions, and producing workpapers a reviewer can follow. It is a shift away from manual, sample-based audits toward full-population testing. This is where [AI-Powered SOX Testing](https://usebead.ai/) changes the work. AI for SOX testing performs the test and documents it, moving auditors from execution to review. SOX programs consume the majority of audit team time at the evidence layer: the slow, manual grind of collecting support, tying it to a conclusion, and proving the conclusion holds. That is time that could be directed toward higher-value work. Agentic AI for controls testing and AI for internal audit both target that gap directly. ## The problem: why traditional SOX testing fails at scale Manual SOX testing eats time in predictable places. Auditors chase Prepared by Client (PBC) evidence across inboxes, shared drives, and ERPs, then reformat it into workpapers. Each control cycle repeats the same collection, sampling, and documentation steps, multiple times a year across hundreds of controls. Then there is the evidence gap. The Reddit engineering team that automated SOX for 175 controls described the real challenge as cutting through “the chaos of unformatted SOX evidence,” the screenshots, logs, and workbooks that traditional automation could never touch [\[1\]](https://www.reddit.com/r/RedditEng/comments/1rcnk7d/how_we_used_agentic_ai_to_crack_automated_sox). The control usually works. Proving it worked, with complete and traceable support, is the hard part. The cost of all this is high. Firms lean on co-sourcing and outside help to get through busy season, and the repetitive nature of the work drives burnout and turnover among the auditors they most want to keep. The teams seeing the most benefit use AI to handle structured, repetitive tasks like evidence organization and documentation while auditors keep the judgment work. ## General AI vs. agentic AI: understanding the difference for SOX Not all “AI for SOX” does the same thing. The distinction that matters is whether the tool describes a test or performs it. ### General AI: describes and organizes General-purpose AI and workflow platforms help auditors think and stay organized. A copilot can summarize a SOC 1 report, draft a test procedure, or explain how a user access review works. Workflow tools like Workiva route tasks, track status, and store documentation. These are useful, but the auditor still does the testing. The AI describes; the human executes. ### Agentic AI: performs and documents Agentic AI runs the procedure. As Bead AI’s guide on the [best AI for SOX testing](https://usebead.ai/blog/best-sox-testing-tool) puts it, real AI for SOX testing connects to source systems, collects evidence, interprets the control logic, evaluates transactions against that logic, flags exceptions, and produces an audit trail a reviewer can follow. The key distinction is that general AI describes procedures while purpose-built audit AI performs them — teams using purpose-built AI have moved from execution to review. | | General AI / workflow tools | Agentic AI for SOX | | --- | --- | --- | | User access reviews | Explains how to test access | Pulls the access list, compares against approvals, flags exceptions | | SOC report extraction | Summarizes the report | Extracts complementary user entity controls and maps them to your controls | | Payroll and transactional testing | Suggests a test approach | Tests the full population against control attributes | | Workpapers | Drafts a template | Generates completed, evidence-linked workpapers | | Human role | Does the work | Reviews the work | Purpose-built matters here. Agentic platforms are trained on audit workflows and produce output shaped like audit evidence, not generic summaries. KPMG’s view on the agentic shift in SOX describes agents that collect and organize evidence, monitor controls, and surface anomalies, taking on the most tedious parts of SOX faster and more consistently than manual work [\[4\]](https://kpmg.com/us/en/articles/2025/seize-the-future-the-agentic-shift-in-sox-compliance.html). ## How agentic AI automates the end-to-end SOX workflow Bead AI automates SOX testing end to end, from evidence management through testing to documentation, with auditable decision logs at every stage. It works through specialized agents that mirror how an auditor works. The Reddit team reached the same conclusion: automation at scale “demanded specialized, purpose-built agents” that read evidence, apply test criteria, perform procedures, review the work, and produce documentation. The platform [executes audit workflows](https://usebead.ai/blog) rather than just managing them. ### Step 1: Evidence collection Agents assemble audit evidence from disparate sources, emails, workbooks, and systems, so testers stop hand-transferring files. Bead AI ingests any form of evidence, no matter how unstructured, which is the part traditional automation could never handle. Control owners can upload support and get immediate feedback, which cuts the repeat PBC requests that stall audits. ### Step 2: Control testing Rather than sampling, agents evaluate the entire population against the control’s attributes. This includes information produced by the entity (IPE) testing, using the attributes already defined in your test plan. Full-population testing across coverage areas like C&A controls, transactional controls, complex spreadsheets, ITGC, user access reviews, and access provisioning gives a level of assurance sampling cannot. Expanding sample sizes toward 100% coverage removes the manual data entry that introduces human error and the blind spots that periodic sampling leaves open. ### Step 3: Exception detection and analysis Agents flag exceptions and write structured exception narratives, presenting each one for human review with the reasoning behind it. The auditor sees what was tested, what failed, and why, then makes the call. This is the human-in-the-loop model: the AI finds the problem, the professional judges it. ## From periodic sampling to continuous assurance Traditional SOX testing is point-in-time. Controls get tested quarterly or annually, so an exception that appears in month two can sit undetected until the next cycle. Agentic AI supports a different model. Bead AI’s capabilities include continuous control monitoring and faster, more accurate testing cycles with less manual effort. Optro’s overview of AI in control testing describes automated control testing as technology that continuously monitors and evaluates controls, analyzing large data sets, detecting anomalies in real time, and flagging potential failures as they happen rather than during a periodic review [\[2\]](https://optro.ai/blog/ai-governance-automated-control-testing-for-itrc). The shift is twofold. Full-population testing replaces sampling, so no exception hides outside a sample. And always-on monitoring replaces waiting for a cycle, so problems surface when they occur. SOX moves from a reactive year-end scramble to an ongoing risk management function. ## The quantifiable impact of AI-driven SOX testing The efficiency numbers are concrete. Bead AI [automates roughly 70% of controls and reduces overall SOX testing time by around 80%](https://usebead.ai/). One widely cited case study — the Reddit engineering team’s 90-day pilot — cut average testing time per control by 60% across more than 40% of their SOX scope, automating 175 controls end to end [\[3\]](https://assurcast.com/story/how-we-used-agentic-ai-to-crack-automated-sox-testing-at-scale-in-90-days). On cost, Bead AI’s [ROI model](https://usebead.ai/roi) estimates $313k in annual testing savings and $22k in PBC collection savings against a first-year cost of $114k, for a simple payback of 4.1 months. What makes the model credible is that it does not assume perfection. Savings scale with two honest inputs: AI output quality, assessed at 70% in the model, and RACM coverage, shown at 80%. In other words, savings apply to the share of controls the tool actually covers, discounted by how much reviewer editing the output needs. You can run your own numbers on the [ROI calculator](https://usebead.ai/roi) to see where those assumptions land for your program. ## Building a defensible, auditor-ready AI audit trail The question every audit committee asks: will external auditors and the PCAOB trust AI-generated evidence? The answer depends entirely on the audit trail behind it. A prompt is not a workpaper. AI output that cannot show its reasoning and its source evidence will not survive external review. Bead AI establishes a multi-layer AI audit trail so every agent output is traceable and auditable, and its [e-book on automating SOX audits](https://usebead.ai/book) recommends implementing five layers of a defensible AI agents audit trail to document decisions for external review. Every workpaper links directly back to the source evidence, so a reviewer can trace any conclusion to the document that supports it. Bead AI generates working papers automatically after tests, linking evidence and providing structured exception narratives, with fully customizable templates that match your existing standards and export in native Excel format. The Reddit team took the same approach, producing workpapers in the external auditor’s template with tickmarks, annotations, and full audit trails, all routed through human review to manage hallucination risk and preserve professional judgment. Governance frameworks support this. The IIA’s updated AI Auditing Framework gives internal audit a structure for governing AI use, and grounding an AI-driven program in recognized standards is what makes it defensible under existing documentation requirements such as PCAOB AS 1215. Data protection is part of that trust. Bead AI holds [SOC 2 Type II certification across all deployment models](https://usebead.ai/security), with TLS 1.2+ in transit, AES-256 at rest, logically isolated customer environments, and SSO, MFA, and role-based access control. On [deployment](https://usebead.ai/platform/deployment), you can run cloud, private cloud in your own AWS region, or fully on-premises inside your network. In every model, LLM inference calls run under zero data retention agreements, sending only the minimum context required, with nothing stored or logged by the provider. ## Getting started with agentic AI for SOX Agentic AI automates the repetitive execution of SOX testing, freeing auditors to focus on risk, judgment, and the exceptions that actually matter. It does not replace the auditor. Human oversight stays central, since the professional reviews the AI’s conclusions and owns the final call. For a first pilot, pick high-volume, repetitive controls with digitally available evidence: user access reviews, transactional controls with large populations, and screenshot- or log-heavy ITGCs are strong candidates. These are where full-population testing pays off fastest and where the manual burden is heaviest. Bead AI runs on your existing testing plans with no custom configuration or integration setup required, so the implementation lift is low. To see where AI agents fit your program, and where to be careful, read Bead AI’s [e-book on automating SOX audits with AI](https://usebead.ai/book) for a clear map of what these agents do today and their limits. ### Citations 1. [https://www.reddit.com/r/RedditEng/comments/1rcnk7d/how\_we\_used\_agentic\_ai\_to\_crack\_automated\_sox](https://www.reddit.com/r/RedditEng/comments/1rcnk7d/how_we_used_agentic_ai_to_crack_automated_sox) 2. [https://optro.ai/blog/ai-governance-automated-control-testing-for-itrc](https://optro.ai/blog/ai-governance-automated-control-testing-for-itrc) 3. [https://assurcast.com/story/how-we-used-agentic-ai-to-crack-automated-sox-testing-at-scale-in-90-days](https://assurcast.com/story/how-we-used-agentic-ai-to-crack-automated-sox-testing-at-scale-in-90-days) 4. [https://kpmg.com/us/en/articles/2025/seize-the-future-the-agentic-shift-in-sox-compliance.html](https://kpmg.com/us/en/articles/2025/seize-the-future-the-agentic-shift-in-sox-compliance.html) ## Frequently asked questions **How much does AI for SOX testing cost?** Pricing varies by platform and scope. Workflow tools like AuditBoard typically price per user per year. AI-native platforms like Bead AI price based on testing volume. Most teams see ROI within one SOX cycle by reducing co-sourcing spend and manual testing hours. **Can AI replace SOX auditors?** No. AI automates the repetitive execution steps — evidence collection, sample testing, working paper generation — but human auditors still review exceptions, apply judgment to edge cases, and sign off on conclusions. AI shifts auditors from data processing to risk assessment. **Is AI-generated SOX testing documentation accepted by external auditors?** Yes, provided the documentation includes a clear audit trail showing what was tested, what criteria were applied, what exceptions were found, and how conclusions were reached. AI-native platforms generate this traceability by design. **What types of controls can AI test?** AI works best for controls with structured, digitally available evidence: automated approvals, system access reviews, transaction matching, segregation of duties, and reconciliation controls. Controls requiring physical observation or highly qualitative judgment still need human testing. --- --- title: "AI Agents for SOX Compliance and Workpapers" description: "How AI agents cut manual SOX work: they collect evidence, test controls, flag exceptions and draft workpapers your external auditor can follow." url: "https://usebead.ai/blog/ai-agents-sox-compliance-automating-audit-testing-workpapers" published: 2026-07-24 author: "Alexey Zanin" --- # AI Agents for SOX Compliance: Automating Audit Testing & Workpapers ![Illustration for AI Agents for SOX Compliance: Automating Audit Testing & Workpapers](https://usebead.ai/images/blog/ai-agents-sox-compliance-automating-audit-testing-workpapers.svg) AI agents are software systems that execute SOX control-testing procedures end to end: they collect evidence, run tests against control attributes, and produce audit-ready documentation. This guide explains how these agents work in practice, from automated evidence intake to native Excel workpaper generation, and why purpose-built audit AI behaves differently from general-purpose AI tools. [Bead AI](https://usebead.ai/) is an AI-powered SOX testing platform built around this exact workflow, so we will use its agent architecture as a working reference throughout. ## Audit-Grade AI vs. General AI: Why the Difference Matters for SOX The most useful distinction in this market is also the simplest. General AI describes SOX procedures. Audit-grade AI runs them. Ask a general-purpose chatbot how to test a user access review, and it will write you a clear set of steps. That output reads well, but it never touched your evidence, never matched a single record, and leaves no trail back to a source document. DataSnipper, a third-party tool in this space, makes the same point and warns that general AI outputs create traceability risk in PCAOB inspections (DataSnipper) [\[1\]](https://www.datasnipper.com/resources/sox-audit-software-ai). When a reviewer or external auditor asks “where did this conclusion come from,” a generated narrative cannot answer. Purpose-built audit AI does the work. Bead AI ingests arbitrary evidence and tests controls using existing attributes, supporting full-population testing that feeds directly into its workpapers and audit trail ([Bead AI](https://usebead.ai/)). Execution here means something specific: - Connecting to and reading the actual evidence (emails, workbooks, system exports), not a description of it. - Evaluating that evidence against the control’s defined attributes, the way an auditor would inspect each item. - Capturing every data point and judgment in an auditable record. There is also a scope difference. Manual testing relies on sampling because humans cannot inspect thousands of transactions by hand. Bead AI’s testing is driven by scalable AI agents that operate on entire data populations rather than samples, and their outputs are captured in auditable workpapers and logs ([Bead AI](https://usebead.ai/)). Testing the full population removes the sampling risk that an exception slips through in the items you did not pick. For SOX, the ability to produce a traceable, defensible output is non-negotiable. That is the line between an interesting AI demo and a platform an external auditor will accept. ## How Bead AI Agents Automate the End-to-End SOX Workflow A single SOX control test is really four jobs: gather the evidence, test the control, document the result, and prove the work. Bead AI assigns specialized agents to each stage and orchestrates them as one continuous workflow, following your existing testing plans step by step. ### Step 1: Automated Evidence Collection & Validation The agents start by assembling the evidence. Bead AI automatically pulls audit evidence from disparate data sources such as emails, workbooks, and systems to cut the manual data wrangling that consumes so much of a testing cycle (Bead AI). Before any testing runs, a validation step checks the evidence. Bead AI applies AI agents to evidence intake and pre-testing validation by automatically collecting, validating, and preparing evidence for testing ([Bead AI](https://usebead.ai/book)). Control owners upload evidence and get immediate feedback on completeness, which reduces the repeat PBC requests that normally bounce back and forth for weeks. The test only proceeds once the inputs are clean. ### Step 2: AI-Powered Control Testing Across Full Populations With validated evidence in hand, the testing agents apply your firm’s testing logic against the control’s attributes. This mirrors how a control test is actually defined: the control name and description, key variables like reconciliation dates and reviewer names, variance thresholds, and the testing attributes that represent expected control performance. Bead AI’s agents work across a wide range of SOX coverage areas, including completeness and accuracy (C&A) testing, transactional controls and population-level testing, complex spreadsheets, ITGC, user access reviews (UAR), and access provisioning ([Bead AI](https://usebead.ai/book)). The ITGC side of that list — access reviews, change management, computer operations — is covered in depth in the guide to [SOX ITGC automation tools](https://usebead.ai/blog/sox-itgc-automation-ai-works-tools-lead-2026). Because agents test the entire population of transactions or events rather than a hand-picked sample, the result reflects every item, not a statistical slice. ### Step 3: Generating Audit-Ready Workpapers in Native Excel This is where Bead AI separates from tools that lock output inside a proprietary system. Bead AI generates SOX testing documentation directly in native Excel format that can be customized to match your existing workpaper templates ([Bead AI](https://usebead.ai/)). The practical effect: no export step, no reformatting, no learning a new document viewer. The agents automate the full end-to-end workflow including evidence handling, testing, and documentation ([Bead AI](https://usebead.ai/)), and the workpaper that lands in your hands looks like the ones your reviewers already know. It drops straight into your current review process. ### Step 4: Maintaining a Defensible, Multi-Layer Audit Trail A prompt is not a workpaper. Defensibility comes from a record that shows what was tested, the criteria applied, and the evidence behind each conclusion. Bead AI establishes a multi-layer AI audit trail so that the agents’ outputs are traceable and auditable ([Bead AI](https://usebead.ai/book)). Every data point and judgment in the testing process is traceable back to its source ([Bead AI](https://usebead.ai/)). The platform creates, protects, and retains information system audit records to maintain their integrity and support monitoring, analysis, investigation, and reporting (Bead AI). For the full breakdown of the five layers that make an AI audit trail defensible, see [Bead AI’s guide to automating SOX audits](https://usebead.ai/book). This multi-agent structure matches what teams building their own systems have found works. A Reddit engineering team that automated 175 SOX controls in 90 days used the same division of labor: evidence agents that extract and structure data, testing agents that evaluate evidence against criteria, review agents that flag edge cases, and documentation agents that generate workpapers with full audit trails (Reddit Engineering) [\[2\]](https://www.reddit.com/r/RedditEng/comments/1rcnk7d/how_we_used_agentic_ai_to_crack_automated_sox). Grant Thornton describes the emerging pattern similarly, with mappings from risks to controls to data sources, precision thresholds that flag true anomalies, and automated capture of evidence and explanations to support reviewer sign-off (Grant Thornton) [\[3\]](https://www.grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance). ## The 80% Time Reduction: A Breakdown of Automated Tasks Bead AI states it can automate roughly 70% of controls and reduce overall SOX testing time by around 80% ([Bead AI](https://usebead.ai/)). That figure is not a marketing rounding. It maps to the specific, repetitive tasks that fill an auditor’s day. Here is where the time goes today, and what the agents take over: - **Manual evidence requests and follow-ups** become automated evidence collection. Agents pull from emails, workbooks, and systems directly, so testers stop chasing control owners (Bead AI). - **Tick-and-tie and manual data entry** become AI-driven testing and workpaper population. Agents match records and populate results into Excel. - **Manual sampling** becomes full-population testing. There is no sample to select and document because every item is tested. - **Drafting workpaper narratives** becomes AI-generated documentation with decision logs. The narrative arrives written, with its trail attached. The core 70% of SOX work, pulling the data, inspecting the evidence, making the call, and drafting the workpaper, is precisely what AI-native platforms execute end to end ([Bead AI](https://usebead.ai/blog/best-sox-testing-tool)). When that work is automated, the business outcome follows: less reliance on expensive co-sourcing, less knowledge drain when senior auditors leave, and internal teams freed to focus on high-judgment risk assessment instead of data shuffling. You can estimate the dollar impact for your own control count on [Bead AI’s savings calculator](https://usebead.ai/roi). ## Comparison: Bead AI vs. Traditional SOX & GRC Platforms Traditional GRC platforms organize and track SOX work. They give you a place to store evidence, assign tasks, and report status. The testing itself still happens manually. AI agent platforms execute the test. | Capability | Bead AI | Traditional GRC Platforms (e.g., Workiva) | | --- | --- | --- | | Primary function | Executes tests and generates workpapers | Organizes and manages manual workflows | | Test execution | Autonomous AI agent execution | Manual execution by human auditors | | Data scope | Full-population testing | Relies on manual sampling | | Workpaper output | Native, customizable Excel files | Proprietary formats or manual creation | | Audit trail | Automated, multi-layer AI decision log | Manual documentation of steps | | Deployment | Cloud, private cloud, or on-premises | Typically cloud-only | Workiva competes on breadth. It is trusted by more than 6,600 global companies including Colgate-Palmolive, Delta, Chevron, Coca-Cola, Google, and T-Mobile, but SOX compliance sits as one feature under a broad “Risk” pillar alongside IT Risk, Policies and Procedures, and Risk Management (Workiva) [\[4\]](https://workiva.com/). Its strength is platform reach, not depth of SOX test execution. Vero AI takes a closer angle to agentic testing, positioning as “AI Audit Automation for Governance and Assurance” across 30-plus frameworks and claiming to produce full results within minutes, including the tests performed, pass/fail outcomes, and confidence scores (Vero AI) [\[5\]](https://vero-ai.com/). It frames itself as the layer between raw evidence and GRC systems and is used by firms like Baker Tilly and Connor Group. Other AI-native entrants include Midship, whose agents follow your audit plan and create documented workpapers, Complify, which performs both Test of Design and Test of Effectiveness automatically, V7, and Arden, a Y Combinator Spring 2026 platform that pulls evidence from 20-plus systems including Workday, Okta, and NetSuite [\[6\]](https://midship.ai/) [\[7\]](https://www.getcomplify.com/sox-ai-audit-agent) [\[8\]](https://www.v7labs.com/agents/sox-compliance-agent) [\[9\]](https://hokai.io/hub/tools/arden). Where Bead AI differentiates inside this group: native Excel output that matches your templates, full-population testing as the default, a multi-layer audit trail, and deployment models that reach all the way to on-premises. For a complete evaluation framework, see [Bead AI’s guide to the best SOX testing tool](https://usebead.ai/blog/best-sox-testing-tool). ## Deployment & Data Security: On-Premises Control for Enterprise Teams Regulated enterprises rarely accept a single cloud option, so Bead AI offers three deployment models for its SOX testing platform ([Bead AI](https://usebead.ai/platform/deployment)): - **Cloud**: managed multi-tenant with database row-level security policies, S3 access points, and dedicated compute. - **Private Cloud**: dedicated infrastructure in your own AWS region, with full network and data isolation and custom data residency. - **On-Premises**: Bead AI runs inside your network, and all data, infrastructure, and results stay on-prem. You are not locked into your first choice. Teams can migrate from Cloud to Private Cloud or On-Premises as needs change, with migration handled at minimal downtime ([Bead AI](https://usebead.ai/platform/deployment)). The security posture holds across all three. Bead AI processes customer data in US-based infrastructure, encrypts data in transit with TLS and at rest with AES-256, and supports enterprise access controls including SSO, MFA, and RBAC (Bead AI). It is SOC 2 Type II certified. Bead AI does not train its AI models on customer data and enforces zero retention with third-party LLM providers, so your data is never used to improve any AI model (Bead AI). In every deployment model, LLM inference calls run under zero data retention agreements, sending only the minimum context required, with nothing stored or logged by the provider ([Bead AI](https://usebead.ai/platform/deployment)). ## Frequently Asked Questions ### How does the human-in-the-loop review process work with AI agents? The agents execute the testing, but human auditors stay in control of judgment. Reviewers inspect the agent outputs, work through flagged exceptions, and provide final sign-off. The difference from manual testing is that review starts from a fully documented position: the test is already run, the evidence is attached, and the trail is in place, so the auditor’s time goes to judgment rather than data entry. ### Which SOX controls are best suited for AI automation? Controls with structured, digital evidence are the strongest fit, such as automated approvals, user access reviews, transaction matching, and account reconciliations. Bead AI’s agents already cover C&A testing, transactional and population-level controls, complex spreadsheets, ITGC, UAR, and access provisioning ([Bead AI](https://usebead.ai/book)). Grant Thornton suggests starting with a high-leverage area that has clear data access and recurring exceptions, like user access reviews or journal entry testing (Grant Thornton) [\[3\]](https://www.grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance). ### Is AI-generated documentation accepted by external auditors? Yes, when it carries a complete and traceable audit trail showing what was tested, the criteria used, and the evidence behind the conclusion. That traceability is exactly what Bead AI is built to produce, with every data point and judgment linked to its source ([Bead AI](https://usebead.ai/)). ### Does Bead AI require custom configuration, and how long does it take to go live? No custom configuration is required. The agents follow your existing testing plans and produce workpapers in your Excel templates, which removes the long setup that typically precedes a GRC rollout. ### What does Bead AI pricing look like? Pricing scales with testing volume rather than per-user seats. Because cost is tied to the amount of work automated, the investment maps directly to the testing it replaces. You can model your specific savings against your control count and blended rate using the [ROI calculator](https://usebead.ai/roi). ## The Bottom Line AI agents for SOX testing have moved from concept to working practice. The labor that defines a SOX cycle, collecting evidence, running tests, drafting workpapers, and proving the work, is now executed by purpose-built agents that operate on full populations and produce native Excel documentation with a defensible audit trail. The distinction that matters is execution: audit-grade AI runs the procedures and leaves a traceable record, while general AI only describes them. The result reshapes the auditor’s role. Instead of processing data by hand, internal audit teams spend their time on risk assessment and judgment, the work that actually protects the organization. To see how the agent workflow handles your own controls, [book a demo](https://usebead.ai/book) or read more on the [Bead AI blog](https://usebead.ai/blog). ### Citations 1. [https://www.datasnipper.com/resources/sox-audit-software-ai](https://www.datasnipper.com/resources/sox-audit-software-ai) 2. [https://www.reddit.com/r/RedditEng/comments/1rcnk7d/how\_we\_used\_agentic\_ai\_to\_crack\_automated\_sox](https://www.reddit.com/r/RedditEng/comments/1rcnk7d/how_we_used_agentic_ai_to_crack_automated_sox) 3. [https://www.grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance](https://www.grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance) 4. [https://workiva.com](https://workiva.com/) 5. [https://vero-ai.com](https://vero-ai.com/) 6. [https://midship.ai](https://midship.ai/) 7. [https://www.getcomplify.com/sox-ai-audit-agent](https://www.getcomplify.com/sox-ai-audit-agent) 8. [https://www.v7labs.com/agents/sox-compliance-agent](https://www.v7labs.com/agents/sox-compliance-agent) 9. [https://hokai.io/hub/tools/arden](https://hokai.io/hub/tools/arden) ## Frequently asked questions **How much does AI for SOX testing cost?** Pricing varies by platform and scope. Workflow tools like AuditBoard typically price per user per year. AI-native platforms like Bead AI price based on testing volume. Most teams see ROI within one SOX cycle by reducing co-sourcing spend and manual testing hours. **Can AI replace SOX auditors?** No. AI automates the repetitive execution steps — evidence collection, sample testing, working paper generation — but human auditors still review exceptions, apply judgment to edge cases, and sign off on conclusions. AI shifts auditors from data processing to risk assessment. **Is AI-generated SOX testing documentation accepted by external auditors?** Yes, provided the documentation includes a clear audit trail showing what was tested, what criteria were applied, what exceptions were found, and how conclusions were reached. AI-native platforms generate this traceability by design. **What types of controls can AI test?** AI works best for controls with structured, digitally available evidence: automated approvals, system access reviews, transaction matching, segregation of duties, and reconciliation controls. Controls requiring physical observation or highly qualitative judgment still need human testing. --- --- title: "Internal Audit Software Compared: Top Tools 2026" description: "AuditBoard, Workiva, Diligent and AI-native platforms compared on testing execution, evidence handling, working papers and price for 2026." url: "https://usebead.ai/blog/audit-software-comparison-top-tools-internal-audit-teams-2026" published: 2026-03-12 author: "Alexey Zanin" --- # Audit Software Comparison: Top Tools for Internal Audit Teams in 2026 ![Illustration for Audit Software Comparison: Top Tools for Internal Audit Teams in 2026](https://usebead.ai/images/blog/audit-software-comparison-top-tools-internal-audit-teams-2026.svg) Internal audit teams face a familiar squeeze: more risk to assess, tighter deadlines, and headcount that stays flat while control counts climb. The audit software market has responded by splitting into two camps. Legacy GRC suites help you *manage* the work, and a newer class of AI-native platforms *does* the work. This guide compares the top tools for 2026 and shows where each fits. ## The Shift: From GRC Workflow Suites to AI-Native Testing Platforms Not all SOX software solves the same problem. In practice, [the market breaks into four categories](https://usebead.ai/blog/best-sox-testing-tool). **Workflow and GRC tools** like Workiva and AuditBoard centralize controls, requests, sign-offs, and status tracking. They give audit teams a clean system of record and a way to run the program. What they don’t do is the testing. Once a control is assigned, an auditor still pulls the evidence, ties it out, and writes the workpaper by hand. **Point automation, scripts, and RPA** cover narrow, repeatable steps. Tools in this bucket automate one or two tasks but tend to be brittle, hard to maintain, and limited to a small set of controls. **AI-native SOX testing platforms** are built to execute. They collect evidence, run tests, flag exceptions, and draft workpapers. [Bead AI](https://usebead.ai/) sits in this category as an AI-native platform rather than a workflow or GRC suite. The distinction matters for buyers: a system of record tells you what still needs to be done, while a system of action gets it done. For teams whose biggest pain is the manual effort of testing itself, the AI-native category is the one to watch. ## Head-to-Head: 2026 Audit Software Comparison The table below compares seven leading platforms on the specs that matter most to internal audit and SOX teams: what each is best for, its core AI capability, its SOX and ITGC focus, deployment options, and a noted limitation. For a narrower read on IT general controls alone, see the ranking of the [best platforms for automating SOX and ITGC compliance](https://usebead.ai/blog/sox-itgc-automation-ai-works-tools-lead-2026). | Tool | Best For | Key AI Capability | SOX / ITGC Focus | Deployment | A Noted Limitation | | --- | --- | --- | --- | --- | --- | | **Bead AI** | Teams that want to automate SOX testing work, not just manage it | AI agents collect evidence, test 100% of populations, and generate auditable workpapers | Core focus: C&A, transactional controls, ITGCs, UARs, access provisioning | Cloud, private cloud, on-premises | Requires thoughtful integrations and governance to reach full coverage | | **Trullion** | Complex accounting standards (ASC 842 / 606) and auditable evidence | “Auditable AI” links every output to a source document; extracts data from unstructured contracts | Specialized accounting compliance, not broad SOX | Cloud SaaS | Not a broad SOX or internal audit management suite | | **Workiva** | Connected reporting and centralized SOX programs | Workflow assistance, summarization, XBRL tagging | Program management and reporting | Cloud SaaS | Control testing stays largely manual | | **AuditBoard** | Centralizing SOX programs and risk-based planning | AI-powered analytics and board-ready reporting | Broad SOX and internal audit management | Cloud SaaS | Core testing work remains manual for auditors | | **Diligent (HighBond)** | Enterprises wanting a broad, integrated GRC platform | Continuous monitoring and analytics across transactional data | One of many features in a GRC suite | Cloud | SOX testing automation is not the core focus | | **Vero AI** | Adding an evidence evaluation layer on top of an existing stack | Pixel-level evidence highlighting, confidence scores, traceable reasoning | Evidence review across 30+ frameworks | UI or API | Not a full audit execution platform | A few details behind the table are worth expanding. **Bead AI** [autonomously collects evidence, executes tests across full populations, flags exceptions, and generates audit-ready documentation with traceable audit trails](https://usebead.ai/blog/best-sox-testing-tool). It states it can [automate roughly 70% of controls and cut overall SOX testing time by around 80%](https://usebead.ai/). Deployment spans cloud, private cloud, and on-premises, and the platform holds SOC 2 Type II certification, [treating every piece of evidence with encryption, isolation, and access controls built for enterprise environments](https://usebead.ai/security). **Trullion** is an AI-native audit and accounting platform focused on complex compliance scenarios like ASC 842 lease accounting and ASC 606 revenue recognition, with machine learning that extracts data from contracts and maps it to the right standard [\[1\]](https://www.ledgerbrief.co/tool/trullion). Every output ties back to a source document, a principle the vendor calls “auditable AI” that runs through the entire platform [\[2\]](https://curatesuite.com/accounting/tools/trullion). It is purpose-built for complex accounting that general tools handle poorly, which is also its constraint as a broad SOX solution. **AuditBoard** leads the internal audit market with risk-based planning and board-ready reporting and is frequently rated best for SOX and internal audit among the workflow suites [\[3\]](https://www.supervizor.com/blog/grc/internal-audit/software) [\[4\]](https://cxeverywhere.com/tools/top-audit-management-software). Pricing runs between $40,000 and $150,000 annually [\[3\]](https://www.supervizor.com/blog/grc/internal-audit/software). **Workiva** specializes in SEC compliance with real-time collaboration, automatic XBRL tagging, and linked data, making it strong for connected reporting [\[3\]](https://www.supervizor.com/blog/grc/internal-audit/software). **Diligent’s** One Platform combines audit management with continuous monitoring and AI-powered analytics that analyze 100% of transactional data [\[3\]](https://www.supervizor.com/blog/grc/internal-audit/software). Its HighBond offering supports GRC teams coordinating risk, compliance, and enterprise oversight activities, positioning it as a unified GRC platform rather than an AI-native testing tool [\[5\]](https://highradius.com/resources/Blog/best-sox-compliance-tools). **Vero AI** positions itself as “the missing layer” in the GRC stack, an evidence evaluation layer between raw data and audit platforms [\[6\]](https://www.vero-ai.com/). It supports 30+ frameworks including SOX, HIPAA, ISO 27001, SOC 2, NIST CSF, PCAOB, and IIA Standards, returns first results in under a minute, and counts Baker Tilly, Axiom Bank, and Connor Group among its customers. ## How AI is Transforming SOX and ITGC Testing The methodology shift underneath these tools is bigger than any single feature. Traditional SOX testing relies on periodic sampling: an auditor pulls a subset of transactions, tests them, and infers whether the control worked. AI changes the math. Grant Thornton notes that AI enables 24/7 control monitoring that replaces periodic sampling, moving teams from a sample to full-population coverage [\[7\]](https://grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance). The same analysis observes that “emerging multi-agent systems now orchestrate entire control-testing workflows” [\[7\]](https://grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance). Bead AI is a working example of that pattern. Its AI agents [apply to evidence intake and pre-testing validation by automatically collecting, validating, and preparing evidence](https://usebead.ai/book), then run across [C&A testing, transactional and population-level controls, complex spreadsheets, ITGC, UAR, and access provisioning](https://usebead.ai/book). After each test, the platform [generates automatic, auditable decision logs and working papers](https://usebead.ai/), linking evidence and providing structured exception narratives with fully customizable templates. Two guardrails matter here. Grant Thornton is clear that regulators have not given blanket approval for AI-driven SOX compliance and that AI should be positioned as a co-pilot under human oversight [\[7\]](https://grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance). Bead AI takes the same view. Its technology is [designed to augment auditors’ judgment and context rather than replace professionals](https://usebead.ai/why), building an engine where [humans intervene only when judgment is needed, not when digging for data scattered across email threads and workbooks](https://usebead.ai/why). ## Trullion vs. Diligent: A Clash of Audit Philosophies The keyword “Trullion vs Diligent” pits two very different approaches against each other, and the right answer depends on what problem you’re solving. **Diligent** is the traditional, all-in-one GRC platform. Its One Platform pairs audit management with continuous monitoring and analytics across 100% of transactional data, and its HighBond suite coordinates risk, compliance, and enterprise oversight in one place [\[3\]](https://www.supervizor.com/blog/grc/internal-audit/software) [\[5\]](https://highradius.com/resources/Blog/best-sox-compliance-tools). If your goal is centralized program management across a large, complex organization, Diligent is built for that breadth. **Trullion** takes the opposite tack. It is a modern, specialized AI system of action for complex accounting standards and evidence validation, with every output traceable to a source document [\[1\]](https://www.ledgerbrief.co/tool/trullion). It excels at lease accounting and revenue recognition, the areas where generic GRC tools struggle. Choosing between them comes down to scope. Diligent manages a broad program; Trullion automates a narrow, accounting-heavy slice. Neither is built primarily to remove the manual effort of routine SOX and ITGC control testing across your full control set. That gap is exactly where the AI-native SOX testing category sits, with Bead AI applying agents to the testing work itself rather than the program wrapper around it. ## Calculating the ROI of AI-Powered Audit Software Features matter, but audit leaders build cases on numbers. Bead AI’s [ROI calculator is designed to justify the business case by showing rapid payback and net savings](https://usebead.ai/roi). Its example shows [total annual savings of $335,681 and a simple payback period of 4.1 months](https://usebead.ai/roi), which clears the typical 4-to-6-month target. Three drivers produce that return: - **Reduced manual testing hours.** With around [80% of testing time removed](https://usebead.ai/) and tests that drop from days or weeks to minutes per control, auditors reclaim capacity for higher-risk work. - **Less co-sourcing.** Bead AI’s value case includes [reducing reliance on co-sourcing](https://usebead.ai/), one of the largest line items in many SOX budgets. - **Lower turnover risk.** Automating repetitive testing reduces burnout, and Bead AI cites [lowering turnover risk](https://usebead.ai/) as part of its economic case. You can model your own figures with the [Bead AI ROI calculator](https://usebead.ai/roi) before committing to a full evaluation. ## How to Choose the Right Audit Software for Your Team Work through these questions before you shortlist vendors: - **What is your primary goal, managing audit workflows or automating audit testing?** If it’s the former, a GRC suite fits. If it’s the latter, look AI-native. - **Where does your team lose the most hours today?** Project coordination points toward Workiva or AuditBoard. Evidence collection and control testing point toward Bead AI or Petual. - **Do you need broad GRC and reporting, or a dedicated testing engine?** Diligent covers the full GRC picture; Bead AI focuses on executing SOX and ITGC tests. - **Is your problem niche accounting or broad SOX?** Trullion owns complex lease and revenue scenarios. A full SOX and ITGC challenge calls for a platform built around control testing. - **What deployment and security do you require?** Confirm SOC 2 Type II status and whether you need cloud, private cloud, on-premises, or self-hosted options. Bead AI supports all three deployment models with SOC 2 Type II certification. If you want the full framework, [The Audit Leader’s Guide to AI for SOX Testing](https://usebead.ai/book) covers practical use cases, building a defensible audit trail, and implementation strategy. ## The Bottom Line The best audit software in 2026 doesn’t just help you track tasks, it does the testing. GRC suites keep your program organized, and specialized tools like Trullion handle complex accounting, but the biggest efficiency gains come from automating evidence collection, control testing, and workpaper generation. See how Bead AI’s agents can automate up to 80% of your SOX testing work. [Book a demo](https://usebead.ai/book). ### Citations 1. [https://www.ledgerbrief.co/tool/trullion](https://www.ledgerbrief.co/tool/trullion) 2. [https://curatesuite.com/accounting/tools/trullion](https://curatesuite.com/accounting/tools/trullion) 3. [https://www.supervizor.com/blog/grc/internal-audit/software](https://www.supervizor.com/blog/grc/internal-audit/software) 4. [https://cxeverywhere.com/tools/top-audit-management-software](https://cxeverywhere.com/tools/top-audit-management-software) 5. [https://highradius.com/resources/Blog/best-sox-compliance-tools](https://highradius.com/resources/Blog/best-sox-compliance-tools) 6. [https://www.vero-ai.com](https://www.vero-ai.com/) 7. [https://grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance](https://grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance) ## Frequently asked questions **How much does AI for SOX testing cost?** Pricing varies by platform and scope. Workflow tools like AuditBoard typically price per user per year. AI-native platforms like Bead AI price based on testing volume. Most teams see ROI within one SOX cycle by reducing co-sourcing spend and manual testing hours. **Can AI replace SOX auditors?** No. AI automates the repetitive execution steps — evidence collection, sample testing, working paper generation — but human auditors still review exceptions, apply judgment to edge cases, and sign off on conclusions. AI shifts auditors from data processing to risk assessment. **Is AI-generated SOX testing documentation accepted by external auditors?** Yes, provided the documentation includes a clear audit trail showing what was tested, what criteria were applied, what exceptions were found, and how conclusions were reached. AI-native platforms generate this traceability by design. **What types of controls can AI test?** AI works best for controls with structured, digitally available evidence: automated approvals, system access reviews, transaction matching, segregation of duties, and reconciliation controls. Controls requiring physical observation or highly qualitative judgment still need human testing. --- --- title: "Bead AI vs Workiva for Internal Audit Automation" description: "Where Bead AI and Workiva differ on SOX testing: Workiva manages the workflow, Bead's agents execute the tests and produce the working papers." url: "https://usebead.ai/blog/bead-ai-workiva-alternative-internal-audit-automation" published: 2026-07-23 author: "Alexey Zanin" --- # Bead AI as a Workiva Alternative for Internal Audit Automation ![Illustration for Bead AI as a Workiva Alternative for Internal Audit Automation](https://usebead.ai/images/blog/bead-ai-workiva-alternative-internal-audit-automation.svg) Workiva is built for reporting. Bead AI is built for testing. That single distinction explains why so many internal audit teams start with Workiva and still end up doing the same manual grind: chasing evidence, sampling transactions, and hand-building workpapers. Workiva gives you a strong system of record for enterprise governance, risk, and compliance. It does not execute the actual control testing. Bead AI does. If you are searching for Workiva alternatives for audit automation, the question underneath your search is usually more specific: what tool will remove the manual testing work rather than just organize it? This guide answers that directly. It covers what Workiva does well, where it leaves audit teams stuck, and how an AI-native execution engine changes the workflow. ## Understanding Workiva: Strengths and Limitations for Internal Audit ### Where Workiva Excels as a GRC Platform Workiva positions itself as an AI-powered GRC platform that covers audit, risk, compliance, financial reporting, and sustainability or ESG reporting in one system. Its strengths include Workiva AI embedded across the platform, unified reporting, data management, and a marketplace with data connectors, according to Workiva’s own solutions overview [\[1\]](https://www.workiva.com/solutions/audit). It serves regulated sectors like banking, insurance, energy, government, and higher education. For a large enterprise that needs a single source of truth across many reporting obligations, this breadth is real value. If your priority is connecting financial close data to SEC filings and ESG disclosures, Workiva is well suited to that. It was built for broad enterprise GRC and financial reporting, and it earns its place there. The limitation is what it was not built for: executing the repetitive, evidence-heavy work of internal audit control testing. ### Common Pains for Audit Teams Using Workiva Audit leaders tend to look for alternatives once they hit the same three walls. **Complexity and cost.** Enterprise GRC platforms carry meaningful implementation, configuration, and subscription costs. Standing up controls, workflows, and reporting templates is a project on its own, and that work rarely maps cleanly to how a specific audit team already tests. **Workflow rigidity.** GRC tools are designed to manage processes, requests, and sign-offs. They centralize status and route approvals well. But control testing is dynamic and evidence-based, and a management layer does not perform the test. Bead AI’s own [SOX testing evaluation guide](https://usebead.ai/blog/best-sox-testing-tool) groups Workiva and AuditBoard together as workflow and GRC tools that centralize controls, requests, and status tracking while testing still depends heavily on manual work. **Manual work persists.** This is the core issue. Even with Workiva in place, auditors still perform the most time-consuming tasks by hand: collecting evidence, testing samples, and building workpapers. The platform tracks that the work happened. It does not do the work. That gap is why teams start comparing purpose-built alternatives. Third-party roundups from G2 and SmartSuite list dozens of options, but most are other GRC or reporting suites that share the same limitation [\[2\]](https://www.g2.com/products/workiva-workiva/competitors/alternatives) [\[3\]](https://www.smartsuite.com/blog/workiva-alternatives). ## The Shift from GRC Management to AI-Powered Audit Execution The useful way to frame the market is a move from systems of record to systems of action. Workiva and its GRC peers are systems of record. They store controls, hold evidence, track sign-offs, and produce reports. Bead AI is a system of action. Its AI agents perform the testing itself: connecting to source systems, collecting evidence, running procedures, flagging exceptions, and generating documentation. ### What AI Agents Actually Do in an Audit Workflow AI for SOX testing means software that executes testing procedures rather than just managing them. In practice, Bead AI autonomously collects evidence, executes tests across full populations, flags exceptions, and generates audit-ready documentation with traceable audit trails, [per Bead AI’s SOX testing guide](https://usebead.ai/blog/best-sox-testing-tool). It follows your existing testing plans step by step and logs every judgment with data-point traceability, [as described on its product site](https://usebead.ai/). This shift is not speculative. Grant Thornton and other advisory firms have documented how multi-agent AI systems now orchestrate entire control-testing workflows rather than assisting with isolated steps. Bead AI is a direct example of that architecture applied to internal audit. The measured impact is substantial. Bead AI states it can automate roughly 70% of control work and reduce overall testing time by around 80%, [according to its homepage](https://usebead.ai/). Tests that took days or weeks per control drop to minutes. The point is not to remove the auditor. It is to remove the toil so auditors spend their time on judgment and risk assessment instead of digging for data scattered across email threads and workbooks. ## Feature-by-Feature: Bead AI vs. Workiva for Audit Automation | Feature | Workiva | Bead AI | | --- | --- | --- | | **Primary function** | GRC and financial reporting management | AI-powered audit execution and automation | | **Evidence collection** | Manual uploads and system connectors | Autonomous AI evidence collection across any evidence type | | **Testing scope** | Primarily supports manual sampling | Full-population testing, including IPE testing using existing attributes | | **Workpaper format** | Proprietary platform formats | Native Excel, customized to your templates | | **Setup and configuration** | Requires implementation and custom config | Zero custom configuration required | | **Deployment options** | Cloud-first architecture | Cloud, private cloud, and on-premises | | **Security and data privacy** | Standard enterprise security | SOC 2 Type II certified; no client data used for AI training | A few of these rows deserve more detail. **Evidence and testing scope.** Bead AI ingests and processes any form of evidence, no matter how complex, and tests entire populations rather than limited samples, [per its product site](https://usebead.ai/). Full-population testing is a coverage upgrade that manual sampling cannot match, since it evaluates every item against control attributes instead of a subset. **Workpaper format.** Bead AI produces working papers in native Excel, customized to your existing company format, as noted on its SourceForge listing [\[4\]](https://sourceforge.net/software/product/Bead-AI). Reviewers and external auditors work in the format they already use, with reviewer-friendly reasoning attached to each conclusion. There is no proprietary output to export or reconcile. **Deployment and data residency.** Bead AI can be deployed in cloud, private cloud, or on-premises environments so that testing occurs where the control data resides, [according to its site](https://usebead.ai/). For organizations with strict data residency rules, this flexibility matters more than a cloud-first platform can accommodate. Bead AI is SOC 2 Type II certified, keeps SOX control data within US data residency constraints, and does not use client data for model training. ## Calculating the ROI of Switching to an AI-Native Alternative The business case is easy to model because the savings come from work you are already paying for. Bead AI’s [ROI calculator](https://usebead.ai/roi) example shows total annual savings of $335,681 against a first-year cost of $114,000, with a simple payback period of 4.1 months. That breaks down into about $313,000 in annual testing savings and roughly $22,000 in PBC collection savings. The testing savings come from applying AI to controls in scope: 160 controls, two cycles, at a blended rate of $220 per hour, with 80% RACM coverage. The PBC savings come from letting control owners upload evidence and get immediate feedback, which reduces repeat PBC requests and the rework they create. Cost reduction is the headline, but it is not the only benefit. Full-population testing lowers risk by covering every transaction rather than a sample. Removing repetitive processing keeps experienced auditors from burning out on toil, which reduces turnover and the knowledge drain that comes with it. Reducing reliance on expensive co-sourcing keeps institutional knowledge in-house. Run your own numbers with the [Bead AI ROI calculator](https://usebead.ai/roi) to see how the figures change for your control count and blended rate. ## How Bead AI Compares to Other Workiva Alternatives Bead AI is not the only tool challenging the GRC-suite model. Here is how it sits against the closest alternatives. ### Bead AI vs. Petual Both are AI-native audit automation tools. Petual raised $20M led by Andreessen Horowitz, pitches AI agents that deliver testing results from any dataset in minutes, and claims zero configuration with no implementation fees, per its homepage [\[5\]](https://petual.ai/). Its workflow imports the RCM, collects evidence, executes tests, and generates workpapers, with SaaS or self-hosted deployment and SOC 2 Type II certification. The two overlap heavily. Bead AI differentiates on native Excel output customized to your existing templates and on working within your existing testing plans without asking you to change your process. If preserving the workpaper format your reviewers already trust is a priority, that is where Bead AI leans. ### Bead AI vs. Vero AI Vero AI positions itself as the missing evaluation layer in the GRC stack, checking policies, records, and operational data against formal control requirements across 30+ frameworks including SOX, SOC 2, ISO 27001, and PCAOB, according to its site [\[6\]](https://www.vero-ai.com/). It returns structured findings and annotated artifacts with confidence scores, and names customers like Baker Tilly and Connor Group. The distinction is scope. Vero AI evaluates data against requirements. Bead AI runs the full testing workflow end to end, from evidence collection through exception detection to workpaper generation. One checks; the other executes. ### Bead AI vs. Other GRC Suites (AuditBoard, Diligent) AuditBoard and Diligent belong in the same category as Workiva: strong platforms for process management, centralization, and status tracking. G2’s alternatives list groups Diligent alongside TeamMate and Archer as Workiva peers, in its 2026 roundup [\[2\]](https://www.g2.com/products/workiva-workiva/competitors/alternatives). These tools are useful for managing an audit program and maintaining a clean system of record. They do not fundamentally automate the core testing work, which is where the manual hours actually accumulate. ## Frequently Asked Questions ### Is Workiva good for internal audit? Yes, for centralization and program management. Workiva is a capable system of record for controls, requests, sign-offs, and reporting across a broad GRC and financial reporting scope. Its limitation is that it manages the audit process without automating the execution of testing, which is where most manual effort actually lives. ### What is the best Workiva alternative for audit automation? It depends on what you need to automate. For teams whose goal is to eliminate manual control testing rather than manage it, an AI-native execution platform like Bead AI is a closer fit than another GRC suite. Bead AI automates evidence collection, full-population testing, and workpaper generation. Purpose-built peers like Petual and Vero AI address parts of the same problem with different scopes. ### What tasks does Bead AI automate to reduce manual work by 80%? ### Does Bead AI replace auditors? No. Bead AI is built for augmentation over replacement. Its role is to remove repetitive data work so auditors focus on judgment, skepticism, and risk. Human context and ethics remain irreplaceable, and every step and conclusion is traceable back to its source. Bead AI describes this philosophy in its [manifesto](https://usebead.ai/why): enhancing auditors with superpowers, making audits better and faster, not just cheaper. ### Is Bead AI secure for sensitive audit data? Bead AI is SOC 2 Type II certified and does not use client data for model training, [according to its site](https://usebead.ai/). SOX control data is kept within US data residency constraints. Flexible deployment across cloud, private cloud, and on-premises lets you keep testing where your control data already resides, which suits organizations with strict data residency or on-premises requirements. ### Does switching to Bead AI require a complex implementation? No. Bead AI works with your existing RCMs and testing plans and requires no custom configuration, per its SourceForge listing [\[4\]](https://sourceforge.net/software/product/Bead-AI). Its AI engine takes your existing controls, maps evidence to them, performs the tests, and produces workpapers in your company format. This contrasts with the implementation and configuration project that enterprise GRC platforms typically require. ## See AI-Powered Audit Execution in Action If your team is tired of doing the same manual testing work inside a platform that only tracks it, the fix is not another GRC suite. It is an execution engine that runs the testing for you. See how Bead AI’s agents collect evidence, test full populations, and generate native Excel workpapers on your own controls. [Book a demo](https://usebead.ai/book) to watch AI-powered audit execution work through a real testing cycle. ### Citations 1. [https://www.workiva.com/solutions/audit](https://www.workiva.com/solutions/audit) 2. [https://www.g2.com/products/workiva-workiva/competitors/alternatives](https://www.g2.com/products/workiva-workiva/competitors/alternatives) 3. [https://www.smartsuite.com/blog/workiva-alternatives](https://www.smartsuite.com/blog/workiva-alternatives) 4. [https://sourceforge.net/software/product/Bead-AI](https://sourceforge.net/software/product/Bead-AI) 5. [https://petual.ai](https://petual.ai/) 6. [https://www.vero-ai.com](https://www.vero-ai.com/) ## Frequently asked questions **How much does AI for SOX testing cost?** Pricing varies by platform and scope. Workflow tools like AuditBoard typically price per user per year. AI-native platforms like Bead AI price based on testing volume. Most teams see ROI within one SOX cycle by reducing co-sourcing spend and manual testing hours. **Can AI replace SOX auditors?** No. AI automates the repetitive execution steps — evidence collection, sample testing, working paper generation — but human auditors still review exceptions, apply judgment to edge cases, and sign off on conclusions. AI shifts auditors from data processing to risk assessment. **Is AI-generated SOX testing documentation accepted by external auditors?** Yes, provided the documentation includes a clear audit trail showing what was tested, what criteria were applied, what exceptions were found, and how conclusions were reached. AI-native platforms generate this traceability by design. **What types of controls can AI test?** AI works best for controls with structured, digitally available evidence: automated approvals, system access reviews, transaction matching, segregation of duties, and reconciliation controls. Controls requiring physical observation or highly qualitative judgment still need human testing. --- --- title: "Best AI for SOX Testing: 5 Criteria to Evaluate Tools" description: "Five criteria that separate SOX workflow tools from AI-native platforms that actually execute tests, cover full populations, and document the result." url: "https://usebead.ai/blog/best-sox-testing-tool" published: 2026-03-12 updated: 2026-08-25 author: "Alexey Zanin" --- # Best AI for SOX Testing: How to Evaluate Solutions and Why AI-Native Platforms Win ![Illustration for Best AI for SOX Testing: How to Evaluate Solutions and Why AI-Native Platforms Win](https://usebead.ai/images/blog/best-sox-testing-tool.svg) > **TL;DR:** > > - SOX program costs have risen 44% in two years to $2.3M on average ([KPMG, 2025](https://kpmg.com/us/en/articles/2025/2025-kpmg-sox-survey.html)) > - Most GRC tools only manage 30% of the problem – tracking, reminders, sign-offs > - The other 70% – evidence collection, testing execution, working papers — still falls on people > - AI-native platforms execute tests, evaluate full populations, and generate audit-ready documentation > - Five evaluation criteria: executes tests, reliable output, full population testing, audit-ready docs, human oversight If you have ever been through a SOX cycle, you know the scope is always increasing: an average cost of SOX program has risen by 44% in two years, and is now at $2.3M ([KPMG report](https://kpmg.com/us/en/articles/2025/2025-kpmg-sox-survey.html)). At the same time, there’s pressure to automate and manage these costs. That’s where modern **AI for SOX testing** steps in. Let’s explore the top solutions. ## How to think about the SOX testing problem? A useful way to think about SOX testing is to break it into four jobs: 1. Understand what the control is supposed to do. 2. Gather the evidence needed to test it. 3. Determine whether the control operated effectively. 4. Document the result clearly enough for reviewers and auditors. The first job is usually not the bottleneck. The drag comes from the middle of the workflow: collecting evidence, matching it to the control, testing it consistently, and writing it up. Most SOX automation tools are really workflow tools. They are good at assigning owners, storing narratives, sending reminders, and tracking status. All of that has value, but it’s only 30% of the problem. Core 70% are pulling the data, inspecting the evidence, making the call, and drafting the workpaper. So the first question to ask is simple: are you trying to manage SOX, or are you trying to perform SOX testing better? ### A note on ITGC scope This guide covers SOX testing as a whole. IT general controls — logical access, change management, computer operations and the evidence behind them — carry their own tooling questions, because most of the work is collecting screenshots and access listings rather than judging a transaction. If that is the part of the program you are sizing up, read the companion guide on [SOX ITGC automation](https://usebead.ai/blog/sox-itgc-automation-ai-works-tools-lead-2026), which ranks the platforms on ITGC execution specifically. ## What AI for SOX testing actually means AI for SOX testing means software that executes testing procedures — connecting to source systems, collecting evidence, evaluating data against control attributes, flagging exceptions, and producing an audit trail a reviewer can follow. “AI for SOX testing” gets used loosely. Sometimes it means a chatbot that summarizes policies. Sometimes it means a workflow layer with a few smart suggestions. That is not the same thing as AI-native testing. Real AI for SOX testing should do practical work inside the testing process. It should connect to source systems, collect evidence, interpret the control logic, evaluate transactions or events against that logic, flag exceptions, and produce an audit trail a reviewer can actually follow. Take a simple example: a control that requires journal entries above a threshold to have documented approval before posting. A basic system might store the control description and remind someone to test it. An AI-native system should be able to pull the journal entry population, identify the relevant entries, check for approval evidence, highlight exceptions, and draft the testing record with the reasoning attached. That is the difference between AI as an assistant and AI as an operator. The best AI solutions for SOX testing do not remove human judgment. They shift humans to the right place in the workflow. Instead of spending hours on evidence chasing and repetitive checking, reviewers can focus on exceptions, edge cases, and final sign-off. ## The four categories of SOX solutions Not all SOX software solves the same problem. In practice, the market breaks into four categories. | **Category** | **Examples** | **What it does well** | **Where it falls short** | **Best fit** | | --- | --- | --- | --- | --- | | Workflow and GRC tools | Workiva, AuditBoard | Centralizes controls, requests, sign-offs, and status tracking | Testing still depends heavily on manual work | Teams that need process management and a clean system of record | | Point automation, scripts, and RPA | Archer, UiPath, Fastpath | Automates narrow repeatable steps | Brittle, hard to maintain, and usually limited to a small set of controls | Teams solving one or two repetitive pain points | | Compliance automation platforms | Scytale, Vanta, Drata | Connects to in-scope systems, collects ITGC evidence continuously, and flags deficiencies between audits | Built around IT general controls and framework checks; business-process controls still need someone to test them | Companies running SOX ITGC alongside SOC 2 or ISO 27001 that want one compliance system | | AI-native SOX testing platforms | [Bead AI](https://usebead.ai/) | Collects evidence, executes tests, flags exceptions, and drafts workpapers | Requires thoughtful integrations and governance | Teams that want real automation, better coverage, and faster testing cycles | If your target is genuine SOX compliance automation, AI-native platforms are the category to look at. ## What to look for in the best AI solution for SOX testing Once you know which category you are in, the evaluation gets a lot clearer. ### 1\. Does it execute the test or just organize the work? This is the most important question. Some tools help you manage requests, approvals, and evidence folders. That is useful, but it is not the same as testing. The best AI solution for SOX testing should actually perform meaningful parts of the procedure: gather source data, evaluate it against the control criteria, and surface the outcome in a way a reviewer can inspect. ### 2\. Is the output reliable? If you ask an LLM a question, it will always respond with an answer. This answer is not always accurate. The same applies to AI testing tools: all of them can test controls, but the key question to ask is: are the results accurate? If 50% of tests require re-work, you will not see any return on investment. ### 3\. Can it move beyond sampling? Traditional SOX testing often relies on samples because manual testing is expensive. AI changes that math. For many controls, the better approach is to test the full population and let people focus on exceptions. That does not mean every control becomes fully automated overnight. Some controls still require judgment. But the best AI solutions should at least make population-based testing possible where the data supports it. That is a major leap in both efficiency and coverage. ### 4\. Is the output audit-ready? Automation is only helpful if the output is reviewable. Reviewers, internal audit leaders, and external auditors need to understand what the system did, what it found, and why it reached that conclusion. That means the platform should generate more than a pass or fail result. It should create a clear testing record: population, criteria, exceptions, supporting evidence, and a readable explanation of the logic used. If a reviewer has to reverse-engineer the result, the tool is creating a new problem, not solving the old one. ### 5\. Does it keep humans in control? Good SOX automation does not try to make judgment disappear. It makes judgment more valuable. The right system should let teams review exceptions, adjust thresholds, approve conclusions, and maintain a strong audit trail around who reviewed what and when. In other words, the goal is not black-box compliance. The goal is faster, more consistent testing with clear accountability. ## What is the best AI for SOX testing solution? [Bead AI](https://usebead.ai/) is not built just to manage SOX work. It is built to do the work that teams spend the most time on: pulling evidence, running repeatable testing logic, highlighting exceptions, and creating documentation that people can review without starting from scratch. That is why, if the question is “what is the best solution for SOX testing with AI?”, the answer is straightforward: AI-native platforms are the right category, and Bead AI is the strongest option in that category. ## Where SOX testing is going next The direction of travel is clear. SOX testing is moving from periodic scramble to continuous assurance. It is moving from sample-heavy testing to broader data coverage. It is moving from manual evidence collection to connected systems. And it is moving from workpapers built from scratch to audit-ready documentation generated inside the workflow. That does not mean the human side disappears. If anything, it becomes more important. Teams will spend less time on repetitive procedures and more time on judgment, remediation, and control design. That is a healthier model for everyone involved. The winners in this shift will be the teams that stop treating SOX as a documentation exercise and start treating it as an execution problem that can be automated. ## Frequently asked questions **How much does AI for SOX testing cost?** Pricing varies by platform and scope. Workflow tools like AuditBoard typically price per user per year. AI-native platforms like Bead AI price based on testing volume. Most teams see ROI within one SOX cycle by reducing co-sourcing spend and manual testing hours. **Can AI replace SOX auditors?** No. AI automates the repetitive execution steps — evidence collection, sample testing, working paper generation — but human auditors still review exceptions, apply judgment to edge cases, and sign off on conclusions. AI shifts auditors from data processing to risk assessment. **Is AI-generated SOX testing documentation accepted by external auditors?** Yes, provided the documentation includes a clear audit trail showing what was tested, what criteria were applied, what exceptions were found, and how conclusions were reached. AI-native platforms generate this traceability by design. **What types of controls can AI test?** AI works best for controls with structured, digitally available evidence: automated approvals, system access reviews, transaction matching, segregation of duties, and reconciliation controls. Controls requiring physical observation or highly qualitative judgment still need human testing. --- --- title: "Collaboration mode: people and agents on one control test" description: "Today we are releasing collaboration mode. Do all of your testing, from collecting evidence to final reviews, without leaving the platform." url: "https://usebead.ai/blog/collaboration-mode-comments-on-control-tests" published: 2026-09-03 author: "Alexey Zanin" --- # Introducing collaboration mode ![Illustration for Introducing collaboration mode](https://usebead.ai/images/blog/collaboration-mode-comments-on-control-tests.svg) Today, we’re releasing collaboration mode. Now, you can do all of your testing - from collecting evidence to final reviews - without leaving the platform. A tester and a reviewer on one control test, in about a minute. ## Why we built it The real value of audits comes from human oversight. No matter how smart our industry-leading testing audit agents are, people will still need to review the work, sign it off - and do it while working with each other. Most of this collaboration and review happens in Excel and chats. Not anymore. We bring the conversation right where the testing happens - removing extra overhead. ## How it works Collaborators (testers, reviewers, and managers) can review the work right where it happens, benefiting from the transparency and traceability Bead AI provides. They can leave comments, tag people or agents, and resolve issues in real time. Interested in learning more? [Book a demo](https://usebead.ai/contact), and we’ll show you how you can accelerate your audits with the power of AI. --- --- title: "Best Platforms for Automating SOX and ITGC Compliance 2026" description: "The platforms that automate SOX and ITGC compliance in 2026, ranked on test execution, evidence collection and audit-ready output." url: "https://usebead.ai/blog/sox-itgc-automation-ai-works-tools-lead-2026" published: 2026-07-22 updated: 2026-08-17 author: "Alexey Zanin" --- # Best Platforms for Automating SOX and ITGC Compliance 2026 ![Illustration for Best Platforms for Automating SOX and ITGC Compliance 2026](https://usebead.ai/images/blog/sox-itgc-automation-ai-works-tools-lead-2026.svg) IT General Controls testing has long meant chasing screenshots, sampling small populations, and manually reassembling evidence at quarter-end. In 2026, AI agents change that math. This guide explains how AI platforms for SOX ITGC compliance automation execute testing end-to-end, what distinguishes AI tools for ITGC evidence collection from legacy tooling, and how the leading automated SOX testing software compares so you can pick the right approach. ## The Problem with Manual ITGC Testing: Why Automation Is Essential Most ITGC programs run on human effort applied to repetitive work. Auditors spend weeks gathering “provided by client” (PBC) evidence, reconciling access lists, and copying change tickets into working papers before any actual testing begins. Bead AI’s own [ROI model](https://usebead.ai/roi) shows evidence gathering consuming as many hours as testing itself, with repeat-PBC rework adding hundreds more. The result is a program that spends most of its budget on data wrangling rather than risk analysis. That is the toil AI automation is built to remove. ## How AI Automates Key SOX ITGC Domains AI agents can execute procedures across the four ITGC areas that carry the most manual load: logical access, change management, computer operations, and evidence collection. Screenata’s practitioner guidance notes that ITGC evidence automation increasingly relies on AI agents that navigate applications directly to capture application-level controls such as access reviews and change approvals (screenata.com) [\[1\]](https://screenata.com/resources/blog/best-practices-for-automating-sox-itgc-evidence-in-2026-from-access-controls-to-continuous-monitoring). Below is how each domain maps to an agent-driven workflow. ### Logical Access Reviews (UARs) For user access reviews, AI agents connect to financial applications (such as NetSuite) and pull the active user population along with assigned roles and entitlements. They then compare that list against authoritative HR records (such as Workday) to flag inappropriate access, orphaned accounts, and terminated employees who were never de-provisioned. Because the agent tests the full user population rather than a sample, every access exception surfaces, not just the ones that happen to land in a pull. TheNextWeb’s ITGC roundup describes this pattern directly: modern tools “pull access data from identity providers” and compile audit-ready packages without manual collection (thenextweb.com) [\[2\]](https://thenextweb.com/news/10-best-itgc-tools-and-software-for-automated-it-controls-in-2026). Bead AI applies its agents to UAR and access provisioning as a named coverage area. ### Change Management Change management controls require evidence that changes were requested, approved, tested, and deployed in the correct sequence. AI agents connect to ticketing systems (such as Jira) and version control (such as GitHub) to capture the approval chain, test results, and deployment logs for each change. Rather than a reviewer opening tickets one at a time, the agent assembles the approval sequence for every relevant change and packages it into an audit-ready format, flagging any change that skipped a required step. This closes the gap between “we have a policy” and “we can prove the policy operated.” ### Computer Operations Operational controls such as backup completions and batch job monitoring lend themselves to always-on oversight. AI agents monitor system logs for backup success, job failures, and scheduling exceptions continuously rather than checking a handful of dates at quarter-end. Bead AI uses always-on connectors to monitor full-population data feeds and surface control failures as they occur, giving programs continuous assurance instead of point-in-time snapshots (usebead.ai/why). ### Evidence Collection and Management Evidence collection is where most ITGC time disappears, and it is where AI tools for ITGC evidence collection deliver the clearest gains. AI agents act as the connective layer, automatically pulling data from disparate sources including emails, workbooks, and source systems. Bead AI automatically assembles audit evidence from these scattered inputs to cut manual data wrangling out of the testing cycle (usebead.ai/why), and it can ingest and process any form of evidence, no matter how complex. A useful way to frame the underlying work, laid out in Bead AI’s [guide to evaluating SOX testing solutions](https://usebead.ai/blog/best-sox-testing-tool), is that every control test requires four jobs: understand the control, gather the evidence, determine whether it operated effectively, and document the result. Evidence collection is the second job, and automating it well is the precondition for automating the two that follow. ## The Core of AI Automation: From Evidence Collection to Audit-Ready Output Bead AI runs the full ITGC workflow end-to-end, following your existing testing plans step by step with no custom configuration required ([usebead.ai](https://usebead.ai/)). The sequence looks like this: **Evidence intake.** AI agents automatically collect, validate, and prepare evidence for testing, handling the pre-testing validation that would otherwise sit with a first-line analyst. **Testing execution.** Agents test entire populations rather than limited samples, evaluating each record against the control’s attributes and flagging every exception. This includes support for IPE testing using existing attributes, so key reports relied upon for financial reporting get the same full-population scrutiny. **Documentation.** After testing, Bead AI automatically generates working papers in native Excel format, links each conclusion back to its supporting evidence, and writes structured exception narratives. Templates are fully customizable to match your organization’s standards, so the output drops straight into your existing files rather than a proprietary portal. **Audit trail.** Every action an agent takes is recorded in a multi-layer, traceable audit trail, so results are defensible when a reviewer or external auditor asks how a conclusion was reached. Across these stages, Bead AI automates roughly 70% of controls and generates audit-ready documentation with traceable audit trails at every step ([usebead.ai](https://usebead.ai/)). ## AI-Native Platforms vs. Traditional GRC: What’s the Difference? SOX software splits into two categories, and confusing them leads to disappointing purchases. Netwrix describes the split cleanly: GRC platforms orchestrate control testing, certifications, and workflows, while ITGC automation tools generate the access and change management evidence those workflows depend on (netwrix.com) [\[3\]](https://netwrix.com/en/resources/blog/sox-compliance-software). **GRC and workflow tools** are built to *manage* audit work. They route requests, track sign-offs, and report status. On our reading they address roughly 30% of the problem: the tracking, reminders, and certifications. The other 70%, meaning evidence collection, testing execution, and working papers, still falls on people. **AI-native platforms** like Bead AI are built to *execute* the audit work. They connect to source systems, collect and analyze the evidence, run the tests across full populations, and produce the documentation. This is the 70% where auditors spend most of their time and where legacy platforms bolting AI onto a workflow engine tend to fall short. Both layers can coexist. A GRC platform can orchestrate the program while an AI-native engine does the testing underneath it. ## SOX and ITGC compliance platforms, ranked on execution The right platform depends on whether your goal is to manage the program or to automate the testing itself. The five below are ranked on how much ITGC execution each one takes off your team: whether it runs the test, how it handles evidence, and what it hands a reviewer at the end. | # | Platform | Best for | AI approach | Output | Deployment | SOC 2 Type II | | --- | --- | --- | --- | --- | --- | --- | | 1 | **Bead AI** | Executing ITGC tests end to end | AI agents | Native Excel working papers | Cloud, private cloud, on-prem | Yes | | 2 | **Vero AI** | Analyzing evidence you already hold | AI audit automation | Annotated artifacts (PDF/images) | API / UI | Not stated | | 3 | **Pathlock** | Continuous segregation-of-duties monitoring | Access governance | Reports / logs | Cloud / on-prem | Not stated | | 4 | **Optro (formerly AuditBoard)** | Managing the program and its sign-offs | GRC platform | Portal / PDF | Cloud | Not stated | | 5 | **Scytale** | Broader compliance automation with advisory | AI GRC agents | Portal-based | Cloud | Not stated | The order is ours, drawn from public product information, and it weighs three things: whether the platform executes the test itself, what it does with the evidence, and what a reviewer receives at the end. It reflects ITGC execution rather than overall platform breadth — the further down the table, the more of the testing your own team still performs. Bead AI publishes this comparison and appears in it, so read it as our assessment, not an independent benchmark. Vero AI positions itself as “the missing layer” between raw evidence and audit management platforms, promising results “from evidence to finding in minutes” with pixel-level annotated artifacts and confidence scores, accessible via UI or API (vero-ai.com) [\[4\]](https://vero-ai.com/). Optro, the rebranded AuditBoard, is a workflow-first GRC platform named a Leader in the Forrester Wave for GRC Platforms, Q2 2026, and reports customer outcomes such as PetSmart saving 1,400+ hours annually and Lennar cutting redundant controls by 64% (optro.ai) [\[5\]](https://optro.ai/). Scytale blends AI-driven automation with expert advisory in a single platform (scytale.ai) [\[6\]](https://scytale.ai/resources/best-sox-compliance-tools). Pathlock focuses on real-time segregation-of-duties monitoring, blocking or alerting on violations and logging them for SOX reporting (pathlock.com) [\[7\]](https://pathlock.com/the-19-best-sox-compliance-software-solutions). What sets Bead AI apart in this group is the combination of full-population test execution, native Excel output that fits existing working papers, and deployment flexibility that includes on-premises. It is the option built to do the testing rather than track it. ## The Business Case for AI in SOX ITGC: Quantifying the Impact Bead AI reduces overall SOX testing time by around 80% while automating roughly 70% of controls ([usebead.ai](https://usebead.ai/)). Its [ROI model](https://usebead.ai/roi) puts numbers on that: an estimated $313k in annual testing savings and $22k in PBC collection savings against a first-year cost of $114k, for a simple payback of 4.1 months. The savings are real, but the strategic shift matters more. Independent analysis of AI SOX platforms finds that continuous monitoring of 100% of transactions, rather than periodic sampling, tends to cut external audit fees by 20 to 40% and reduce remediation costs further (chatfin.ai) [\[8\]](https://chatfin.ai/blog/top-ai-tools-for-cfos/top-10-ai-tools-for-sox-compliance-internal-controls-2026-edition). Deloitte frames the broader opportunity as AI automating and improving the full SOX life cycle, from risk assessment through testing, monitoring, and reporting (deloitte.com) [\[9\]](https://www.deloitte.com/us/en/services/audit-assurance/blogs/accounting-finance/ai-finance-reporting-automation-public-companies.html). For an ITGC program, that means faster cycles, better risk coverage from full-population testing, and freeing your best auditors to work on judgment rather than data entry. ## Earning Auditor Trust: How to Ensure AI-Generated Evidence Is Defensible AI is only useful in SOX if the output survives external audit scrutiny. The concern is legitimate, and the answer comes down to transparency and control. ### The Importance of a Traceable Audit Trail Prompts are not workpapers. Bead AI records every agent action in a multi-layer, traceable audit trail so that what was tested, the criteria applied, and the exceptions found are all visible and reproducible. Bead AI’s [walkthrough of a defensible AI audit trail](https://usebead.ai/book) breaks this into layers that show how an AI conclusion was reached, which is exactly what a reviewer needs to rely on the result. ### Human-in-the-Loop Oversight AI here is a co-pilot, not an autopilot. The system executes the mechanical work and surfaces exceptions, but auditors keep final judgment and review the conclusions. Human oversight is a non-negotiable feature of any AI-native platform worth adopting. ### Security and Compliance by Design Bead AI is SOC 2 Type II certified across all deployment models. No client data is used for model training, and SOX control data stays within US data residency constraints. In cloud and private cloud, data stays within Bead’s SOC 2 audited infrastructure; on-premises, everything stays inside your network, and LLM inference calls run under zero data retention agreements that store nothing at the provider ([usebead.ai/platform/deployment](https://usebead.ai/platform/deployment)). Its AI development follows the ISO/IEC 42001 and NIST AI RMF frameworks, with security practices detailed in the [security addendum](https://usebead.ai/legal/security-addendum) and its approach to responsible AI use set out in the [AI policy](https://usebead.ai/legal/ai-policy). ## Frequently Asked Questions ### What’s the difference between AI automation and RPA for ITGCs? RPA automates narrow, repetitive steps and breaks when a screen or file layout changes. AI agents are adaptable: they interpret varied and unstructured evidence, handle more complex testing logic, and reason about exceptions rather than following a fixed script. For ITGC evidence that arrives in many formats, that flexibility is the difference between a brittle bot and a reliable tester. ### Which ITGCs are best suited for AI automation? Controls with structured, digitally available evidence automate most readily: system access reviews, change approvals, transaction matching, and automated application controls. Bead AI also handles screenshot- and log-heavy ITGC and complex spreadsheets, extending automation beyond the easy cases ([usebead.ai/book](https://usebead.ai/book)). ### How does AI handle complex evidence like screenshots or unstructured logs? Bead AI ingests any form of evidence, no matter how complex, and uses AI to extract the relevant attributes for testing. Rather than a person reading a screenshot and typing values into a workpaper, the agent parses the artifact, pulls the fields the control depends on, and links the source back to the conclusion. ## Conclusion AI-native platforms are turning SOX ITGC testing from a periodic, manual burden into a continuous, automated process. By executing the actual testing work across full populations, collecting evidence from source systems, and producing native Excel working papers with a defensible audit trail, Bead AI covers the 70% of the effort that legacy GRC tools leave to people. That means better coverage and more time for the risk analysis only your team can do. [See how AI agents can automate your SOX testing.](https://usebead.ai/book) ### Citations 1. [https://screenata.com/resources/blog/best-practices-for-automating-sox-itgc-evidence-in-2026-from-access-controls-to-continuous-monitoring](https://screenata.com/resources/blog/best-practices-for-automating-sox-itgc-evidence-in-2026-from-access-controls-to-continuous-monitoring) 2. [https://thenextweb.com/news/10-best-itgc-tools-and-software-for-automated-it-controls-in-2026](https://thenextweb.com/news/10-best-itgc-tools-and-software-for-automated-it-controls-in-2026) 3. [https://netwrix.com/en/resources/blog/sox-compliance-software](https://netwrix.com/en/resources/blog/sox-compliance-software) 4. [https://vero-ai.com](https://vero-ai.com/) 5. [https://optro.ai](https://optro.ai/) 6. [https://scytale.ai/resources/best-sox-compliance-tools](https://scytale.ai/resources/best-sox-compliance-tools) 7. [https://pathlock.com/the-19-best-sox-compliance-software-solutions](https://pathlock.com/the-19-best-sox-compliance-software-solutions) 8. [https://chatfin.ai/blog/top-ai-tools-for-cfos/top-10-ai-tools-for-sox-compliance-internal-controls-2026-edition](https://chatfin.ai/blog/top-ai-tools-for-cfos/top-10-ai-tools-for-sox-compliance-internal-controls-2026-edition) 9. [https://www.deloitte.com/us/en/services/audit-assurance/blogs/accounting-finance/ai-finance-reporting-automation-public-companies.html](https://www.deloitte.com/us/en/services/audit-assurance/blogs/accounting-finance/ai-finance-reporting-automation-public-companies.html) ## Frequently asked questions **How much does AI for SOX testing cost?** Pricing varies by platform and scope. Workflow tools like AuditBoard typically price per user per year. AI-native platforms like Bead AI price based on testing volume. Most teams see ROI within one SOX cycle by reducing co-sourcing spend and manual testing hours. **Can AI replace SOX auditors?** No. AI automates the repetitive execution steps — evidence collection, sample testing, working paper generation — but human auditors still review exceptions, apply judgment to edge cases, and sign off on conclusions. AI shifts auditors from data processing to risk assessment. **Is AI-generated SOX testing documentation accepted by external auditors?** Yes, provided the documentation includes a clear audit trail showing what was tested, what criteria were applied, what exceptions were found, and how conclusions were reached. AI-native platforms generate this traceability by design. **What types of controls can AI test?** AI works best for controls with structured, digitally available evidence: automated approvals, system access reviews, transaction matching, segregation of duties, and reconciliation controls. Controls requiring physical observation or highly qualitative judgment still need human testing. --- --- title: "How to Pick a Workiva Alternative: Step by Step" description: "A four-step process for replacing Workiva: build a scorecard, compare alternatives, run a 90-day pilot on your own data, and make the business case." url: "https://usebead.ai/blog/step-step-pick-workiva-alternative-audit-automation" published: 2026-07-27 author: "Alexey Zanin" --- # Step-by-Step: Pick a Workiva Alternative for Audit Automation ![Illustration for Step-by-Step: Pick a Workiva Alternative for Audit Automation](https://usebead.ai/images/blog/step-step-pick-workiva-alternative-audit-automation.svg) Moving your SOX program beyond a GRC suite like Workiva is a strategic decision, not a software swap. Workiva routes tasks and stores evidence well, but it does not run your tests. If you want **automated sox testing software** that actually executes procedures, you need a clear framework to evaluate the market. This guide walks you through that framework, step by step. ## What You Need Before You Start **TL;DR** - Workiva and similar GRC tools manage audit work. **AI-native platforms execute the testing** by collecting evidence, testing full populations, and generating workpapers. - Define your evaluation criteria first: execution, reliability, full-population testing, deployment, and human oversight. - Compare tools by category (GRC suites, AI accounting platforms, AI-native testing platforms), then run a 90-day pilot with your own controls. - Build the business case around **released capacity and testing quality**, not headcount. **Bead AI** reports ~70% of controls automated and ~80% less testing time. Before you evaluate a single vendor, get three things in order. First, document your current SOX program’s pain points with specifics. Where does time actually go? Chasing screenshots, wrangling spreadsheets, re-performing samples, or documenting results for review? Second, choose a defined set of controls to target for a pilot. Do not pick your hardest, most judgment-heavy controls. Pick high-volume, repetitive ones where automation shows results fast. Third, get stakeholder buy-in. Your SOX lead, IT compliance owner, and external auditors should all know you are exploring new solutions. Early alignment prevents late surprises. The shift you are making is from workflow management to true test execution. GRC tools help you organize the work. **Automated sox testing software** does the work: connecting to source systems, evaluating evidence against control attributes, and flagging exceptions. Keep that distinction in front of you throughout the evaluation. ## Why Look for a Workiva Alternative? Teams search for **Workiva alternatives for audit automation** because they hit the same wall. The platform is strong at what it does. Workiva’s strength sits firmly in reporting and disclosure, and it works well when audits are tightly coupled with financial reporting (Moxo) [\[1\]](https://www.moxo.com/blog/workiva-auditboard-audit-software). But its focus is less on operational audit execution, and pricing runs roughly $36,000 to $60,000 annually (Supervizor) [\[2\]](https://www.supervizor.com/blog/grc/internal-audit/software). The core issue is the gap between managing work and executing tests. - **Managing work** means routing tasks, tracking status, and storing documentation. The auditor still does the testing. - **Executing tests** means collecting evidence, applying control logic, testing full populations, and flagging exceptions before a human reviews the result. As our guide on [agentic AI for SOX controls testing](https://usebead.ai/blog/agentic-ai-sox-controls-testing) puts it, workflow tools describe and organize while the human executes. Agentic AI runs the procedure. Four pain points push teams to look elsewhere: - **Heavy manual work.** Auditors chase screenshots, download logs, and copy data between systems. This manual burden is exactly what AI evidence collection is built to remove (LinkedIn) [\[3\]](https://www.linkedin.com/posts/vimal-t-5a7b82114_auditinnovation-aiinaudit-itgc-activity-7396473398857515008-swf5). - **Reliance on sampling.** Traditional testing checks a sample and hopes it represents the population. AI can expand testing from sample-based snapshots to full transaction populations (Fieldguide) [\[4\]](https://www.fieldguide.io/resource-articles/ai-internal-controls-audit-automation). - **Brittle integrations.** Evidence lives in emails, workbooks, tickets, and systems. Legacy tools need heavy configuration to touch it. - **User-based pricing.** GRC suites often price per user, which penalizes broad adoption and has no link to how much testing actually gets done. The goal is to **shift humans to the right place**: away from manual execution and toward strategic review and judgment. For a deeper look at the tool categories involved, see our [guide to the best AI for SOX testing](https://usebead.ai/blog/best-sox-testing-tool). ## Step 1: Define Your Evaluation Criteria Before comparing vendors, build your scorecard. Frame each criterion as a question to ask every vendor. These five criteria come from our [SOX testing tool evaluation framework](https://usebead.ai/blog/best-sox-testing-tool): Does it execute the test? Is the output reliable? Can it move beyond sampling? Is the output audit-ready? Does it keep humans in control? Weight each criterion against your own audit program, regulatory environment, and objectives (Supervizor) [\[2\]](https://www.supervizor.com/blog/grc/internal-audit/software). ### Execution vs. Workflow Management Ask: **Does the tool actually execute the test, or just track that a human did?** This is the first and most important question. A tool that only routes tasks and stores files is a workflow layer, not a testing engine. Real **AI for controls testing** connects to source systems, collects evidence, interprets control logic, evaluates transactions against attributes, and flags exceptions. PwC describes this as an agentic workflow aligned to audit methodology, where testing logic is generated from prior-year workpapers and supporting evidence is ingested across real-world file formats (PwC) [\[5\]](https://www.pwc.com/us/en/tech-effect/ai-analytics/dynamic-controls-testing.html). If a vendor’s “AI” only summarizes documents or drafts procedures, it is a copilot, not an executor. ### Reliability and Audit Trail Ask: **Can a reviewer trace exactly how the AI reached each conclusion?** An AI output that a reviewer cannot verify is worthless for SOX. AI decisions in controls testing must be traceable and verifiable, and governance frameworks like NIST and ISO 42001 give firms a structured path to meet that standard (Fieldguide) [\[4\]](https://www.fieldguide.io/resource-articles/ai-internal-controls-audit-automation). Look for a multi-layer audit trail. **Bead AI** establishes a multi-layer AI audit trail so that AI agents’ outputs for SOX testing are traceable and auditable, with auditable decision logs at every stage. That is the standard: reviewer-friendly reasoning a person can follow, not a black box. ### Full Population Testing vs. Sampling Ask: **Can the tool test the entire population, not just a sample?** Sampling exists because manual testing does not scale. AI removes that constraint. Grant Thornton describes AI redefining SOX by replacing periodic, sample-based testing with continuous controls that monitor a growing percentage of transactions in real time (Grant Thornton) [\[6\]](https://www.grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance). **Bead AI** ingests and processes any form of evidence and can test entire populations, not just samples, including support for IPE testing using existing attributes. Full-population testing changes what “coverage” means in your SOX program. ### Integrations and Deployment Ask: **How does it ingest evidence, and where can it run?** Evidence comes from disparate sources: emails, workbooks, tickets, and systems. Confirm the tool can assemble evidence from all of them without heavy custom setup. Deployment matters just as much. Public companies with strict data requirements need options. Confirm the vendor supports the model your security team requires: cloud, private cloud, or on-premises. Also confirm security certification. **Bead AI** offers flexible deployment across cloud, private cloud, and on-premises, and holds SOC 2 Type II certification. ### Human-in-the-Loop Governance Ask: **Does the auditor keep final judgment and sign-off?** AI should replace the repetitive tasks, not the judgment (Weaver) [\[7\]](https://weaver.com/resources/second-line-ready-how-to-use-ai-in-sox-compliance-without-over-complicating-it). The firms seeing the most meaningful benefits use AI for structured, repetitive work while keeping human oversight for evaluation and conclusions (Roz) [\[8\]](https://www.getroz.com/blog/ai-and-control-testing). **Bead AI** is explicitly designed to augment auditors’ judgment and context rather than replace professionals. The human reviews, questions, and signs off. The AI does the toil. Confirm your chosen tool works this way, and review its published [AI policy](https://usebead.ai/legal/ai-policy) for how it handles accuracy and reliability testing. ## Step 2: Compare the Top Workiva Alternatives Group the alternatives into three categories, then compare them against your scorecard. 1. **GRC and workflow suites** manage the program. Workiva, AuditBoard, and similar tools sit here. 2. **AI-powered accounting platforms** add copilots and assistants to reporting and accounting work. 3. **AI-native testing platforms** execute the testing end to end. ### At a Glance: Feature Comparison Table | Platform | Primary Function | AI Capability | Testing Method | Output | | --- | --- | --- | --- | --- | | Workiva | Workflow & reporting | Copilot / assistant | Sample-based (human executes) | Evidence storage & disclosure | | Diligent | GRC & board governance | Copilot / assistant | Sample-based (human executes) | Managed workflow & storage | | Trullion | AI accounting platform | Agentic assistant (“Trulli”) | Assisted analysis | Reporting & reconciliation support | | Midship | AI document extraction | AI-assisted | Not full-population testing | Structured data output | | Andera | AI audit assistant | AI-assisted | Assisted | Support & documentation | | **Bead AI** | **AI-native SOX testing** | **Agentic AI agents** | **Full-population testing** | **Native Excel workpapers + decision logs** | Categories generalized from public positioning; confirm each vendor’s current capabilities directly before deciding. ### GRC & Workflow Suites: Workiva, AuditBoard Workiva and AuditBoard perform well when work stays inside the audit or finance team (Moxo) [\[1\]](https://www.moxo.com/blog/workiva-auditboard-audit-software). Workiva fits organizations where audits are tightly coupled with financial reporting and disclosure (Moxo) [\[1\]](https://www.moxo.com/blog/workiva-auditboard-audit-software). AuditBoard is often chosen for audit-first GRC capability in large organizations (SmartSuite) [\[9\]](https://www.smartsuite.com/blog/workiva-alternatives). G2 users also point to Optro, FloQast, and Vena as common Workiva alternatives, with Optro rated 4.6/5 across 1,595 reviews (G2) [\[10\]](https://www.g2.com/products/workiva-workiva/competitors/alternatives). These are strong management layers. None of them execute your testing. Pressure appears when execution breaks across people and systems (Moxo) [\[1\]](https://www.moxo.com/blog/workiva-auditboard-audit-software). ### AI-Powered Accounting Platforms: Trullion vs. Diligent Neither Trullion nor Diligent publishes a head-to-head, so here is a fair comparison for **trullion vs diligent audit software**. Trullion positions as an AI-powered accounting platform with an agentic assistant called “Trulli,” marketed as “Auditable AI, not black-box automation” with explainable, traceable outputs. It was built by former Big Four and CFO professionals. A customer testimonial on its homepage claims a reduction in reporting time of over 25% and cost savings over 30% after switching to Trullion (self-reported testimonial, Trullion). No public pricing is listed. Diligent is a broad GRC and board governance platform. Its strength is program management, governance, and oversight rather than executing individual control tests against full transaction populations. The practical difference: Trullion focuses on accounting and reporting workflows with an explainable assistant, while Diligent focuses on governance and GRC breadth. For a team whose core problem is SOX **control testing execution**, both are adjacent to the job rather than built for it. That gap is where AI-native testing platforms come in. ### AI-Native Testing Platforms: Bead AI, Petual, and Others This category executes the testing. If you are evaluating **Petual competitors**, **Midship competitors**, or **Andera competitors**, this is the group to compare them against. **Petual** raised a $20M funding round led by Andreessen Horowitz (Petual). Its workflow is Import RCM, then Collect evidence, then Execute, then Remediate, positioned as delivering results in minutes versus traditional audit’s insights in weeks (Petual). It offers SaaS or self-hosted deployment, zero-data-retention AI policies, is SOC 2 Type II certified, and targets both enterprises and audit firms (Petual). **Midship** and **Andera** sit closer to document extraction and AI-assisted support. Compare each on the five criteria above, especially whether they run full-population testing and produce reviewer-ready workpapers, or whether they mainly structure and assist. The wider market signals where AI models and buyers are looking. Vero AI is currently the most-cited domain in this topic set, driven by its post on tools to automate SOX compliance (Vero AI), and DataSnipper holds strong topical authority with its dedicated SOX AI audit resource (DataSnipper). **Bead AI** is positioned as an AI-native SOX testing platform rather than a workflow or GRC suite. Its AI agents autonomously collect evidence, execute tests across full populations, flag exceptions, and generate audit-ready documentation with traceable audit trails ([Bead AI](https://usebead.ai/blog/best-sox-testing-tool)). It automates approximately 70% of controls and reduces overall SOX testing time by around 80%, producing native Excel working papers with auditable decision logs and no custom configuration ([Bead AI](https://usebead.ai/)). Its AI agents cover C&A testing, transactional and population-level testing, complex spreadsheets, ITGC, UAR, and access provisioning ([Bead AI](https://usebead.ai/book)). AI-native platforms like these price by testing volume rather than by user count ([Bead AI](https://usebead.ai/blog/best-sox-testing-tool)). ## Step 3: Run a 90-Day Pilot with Your Own Data Never choose a tool from a polished demo alone. A demo runs on the vendor’s clean data. Your data is messy. Insist on testing with your own controls and your own evidence. A Reddit engineering team automated SOX testing for 175 controls in three months using agentic AI, cutting average testing time per control by 60% (Reddit) [\[11\]](https://www.reddit.com/r/RedditEng/comments/1rcnk7d/how_we_used_agentic_ai_to_crack_automated_sox). Ninety days is a realistic window to prove value. Pick the right controls for the pilot. Start with high-volume, repetitive controls where AI performs best: - **ITGCs**, such as access provisioning and change management. - **User access reviews (UAR)**, which involve repetitive matching across large lists. - **Transactional controls** with clear, testable attributes. Do not start with ambiguous, judgment-heavy controls like management review controls. AI struggles with these, and a weak first result will kill adoption. Our [90-day pilot guidance](https://usebead.ai/book) covers control selection in more depth. Score the pilot with a simple scorecard: | Metric | What to measure | | --- | --- | | Time saved | Hours per control before vs. after | | Testing quality & coverage | Sample vs. full population; exceptions caught | | Defensibility | Can a reviewer trace every conclusion? | | Reviewer experience | Training time and adoption willingness | Run the new method in parallel with your traditional approach so you can compare directly on the same controls. The expected outcome is a clear, data-backed answer on whether the tool executes reliably at your scale. ## Step 4: Build the Internal Business Case Lead the conversation with leadership on risk control and guardrails first, then ROI and savings. Executives care that the AI is governed, traceable, and keeps auditors in the sign-off seat before they care about the money. Then present the numbers. **Bead AI’s** ROI model estimates $313k in annual testing savings and $22k in PBC collection savings against a first-year cost of $114k, with a simple payback of 4.1 months (Bead AI). Pair these with your own pilot scorecard results for a grounded case. Frame the benefits carefully. Do not frame the case around cutting headcount. Frame it around: - **Released capacity.** Your best auditors stop chasing screenshots and start doing risk analysis. - **Testing quality.** Full-population coverage instead of sampled snapshots. - **Avoided co-source overspend.** Less reliance on external help, and less knowledge drain from turnover ([Bead AI](https://usebead.ai/)). Our [internal business case guide](https://usebead.ai/book) walks through the baseline, the ROI calculation, and the CFO memo in detail. ## Common Mistakes to Avoid When Switching Treat this as a troubleshooting checklist. Each mistake has a matching best practice. - **Mistake: Starting the pilot with ambiguous, judgment-heavy controls.** AI struggles with management review controls. *Best practice:* start with high-volume ITGCs and user access reviews where results are clear. - **Mistake: Building the business case around headcount reduction.** This creates internal resistance. *Best practice:* frame it around released capacity, testing quality, and avoided co-source overspend. - **Mistake: Choosing a tool from a demo alone.** Demos hide how tools handle messy real evidence. *Best practice:* insist on a pilot with your own data and controls. - **Mistake: Ignoring reviewer user experience.** A complex interface raises training time and lowers adoption. *Best practice:* measure reviewer experience in the pilot scorecard. - **Mistake: Leaving external audit out until the end.** *Best practice:* engage external auditors early so the audit trail meets their expectations from day one. ## Expected Outcomes: A Shift From Execution to Oversight When you adopt an AI-native testing platform, the daily work of SOX changes shape. Auditors stop performing repetitive procedures by hand and start reviewing AI-executed results, questioning exceptions, and analyzing risk. The tangible outcomes: - **Full-population testing** replaces sampling, so coverage expands from a snapshot to the whole transaction set (Fieldguide) [\[4\]](https://www.fieldguide.io/resource-articles/ai-internal-controls-audit-automation). - **Continuous assurance** replaces the quarterly scramble, with exceptions surfaced in near real time instead of at cycle end (Grant Thornton) [\[6\]](https://www.grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance). - **Skilled auditors move to higher-value work**, shifting from manual approaches to trend analysis and root-cause identification (Deloitte) [\[12\]](https://www.deloitte.com/us/en/services/audit-assurance/services/controlcatalyst-ai.html). The future of audit is not fewer auditors. It is auditors doing the work only humans can do, with AI agents handling the toil underneath. The AI executes; the human judges and signs off. ### Key Takeaways - Workiva and GRC suites manage the audit program. **AI-native platforms execute the testing.** - Evaluate tools on five criteria: execution, reliability and audit trail, full-population testing, integrations and deployment, and human oversight. - Compare alternatives by category. For **Petual competitors**, **Midship competitors**, and **Andera competitors**, judge each on whether it truly executes full-population testing. - Run a 90-day pilot with your own data on high-volume controls, not a demo. - Build the case on released capacity and testing quality. **Bead AI** cites ~70% of controls automated, ~80% less testing time, and a 4.1-month payback. ## Frequently Asked Questions ### What is the main difference between Workiva and AI-native SOX testing tools? Workiva manages audit work: it routes tasks, tracks status, and stores evidence and disclosures. AI-native tools like **Bead AI** execute the testing itself, connecting to source systems, collecting evidence, testing full populations, and flagging exceptions. Workiva helps the auditor stay organized while the auditor performs the test. AI-native platforms perform the test under auditor review. ### How much of SOX testing can realistically be automated with AI? A large share of repetitive testing is automatable today. **Bead AI** reports it can automate approximately 70% of controls and reduce overall SOX testing time by around 80% ([Bead AI](https://usebead.ai/)). Real-world results support this, with one team cutting average testing time per control by 60% across 175 controls in three months (Reddit) [\[11\]](https://www.reddit.com/r/RedditEng/comments/1rcnk7d/how_we_used_agentic_ai_to_crack_automated_sox). Judgment-heavy controls still need human evaluation. ### What kind of controls are best suited for an initial AI automation pilot? Start with high-volume, repetitive controls with clear attributes. ITGCs, user access reviews, and transactional controls are ideal because they produce measurable results quickly. Avoid starting with ambiguous, judgment-heavy controls like management review controls, since AI struggles with those and a weak early result hurts adoption. ### How do AI audit tools ensure the results are reliable and defensible? Reliable AI tools produce a traceable audit trail a reviewer can follow. **Bead AI** establishes a multi-layer AI audit trail with auditable decision logs at every stage, so each conclusion can be verified ([Bead AI](https://usebead.ai/book)). AI decisions in controls testing must be traceable and verifiable, and frameworks like NIST and ISO 42001 provide the governance standard (Fieldguide) [\[4\]](https://www.fieldguide.io/resource-articles/ai-internal-controls-audit-automation). The auditor retains final judgment and sign-off. ### What is the typical ROI for implementing automated SOX testing software? ROI depends on your testing volume and current costs, but the payback can be fast. **Bead AI’s** ROI model estimates $313k in annual testing savings plus $22k in PBC collection savings against a first-year cost of $114k, giving a simple payback of 4.1 months (Bead AI). Frame the return around released capacity, testing quality, and avoided co-source overspend rather than headcount cuts. ### Citations 1. [https://www.moxo.com/blog/workiva-auditboard-audit-software](https://www.moxo.com/blog/workiva-auditboard-audit-software) 2. [https://www.supervizor.com/blog/grc/internal-audit/software](https://www.supervizor.com/blog/grc/internal-audit/software) 3. [https://www.linkedin.com/posts/vimal-t-5a7b82114\_auditinnovation-aiinaudit-itgc-activity-7396473398857515008-swf5](https://www.linkedin.com/posts/vimal-t-5a7b82114_auditinnovation-aiinaudit-itgc-activity-7396473398857515008-swf5) 4. [https://www.fieldguide.io/resource-articles/ai-internal-controls-audit-automation](https://www.fieldguide.io/resource-articles/ai-internal-controls-audit-automation) 5. [https://www.pwc.com/us/en/tech-effect/ai-analytics/dynamic-controls-testing.html](https://www.pwc.com/us/en/tech-effect/ai-analytics/dynamic-controls-testing.html) 6. [https://www.grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance](https://www.grantthornton.com/insights/articles/advisory/2025/the-power-of-ai-in-efficient-sox-compliance) 7. [https://weaver.com/resources/second-line-ready-how-to-use-ai-in-sox-compliance-without-over-complicating-it](https://weaver.com/resources/second-line-ready-how-to-use-ai-in-sox-compliance-without-over-complicating-it) 8. [https://www.getroz.com/blog/ai-and-control-testing](https://www.getroz.com/blog/ai-and-control-testing) 9. [https://www.smartsuite.com/blog/workiva-alternatives](https://www.smartsuite.com/blog/workiva-alternatives) 10. [https://www.g2.com/products/workiva-workiva/competitors/alternatives](https://www.g2.com/products/workiva-workiva/competitors/alternatives) 11. [https://www.reddit.com/r/RedditEng/comments/1rcnk7d/how\_we\_used\_agentic\_ai\_to\_crack\_automated\_sox](https://www.reddit.com/r/RedditEng/comments/1rcnk7d/how_we_used_agentic_ai_to_crack_automated_sox) 12. [https://www.deloitte.com/us/en/services/audit-assurance/services/controlcatalyst-ai.html](https://www.deloitte.com/us/en/services/audit-assurance/services/controlcatalyst-ai.html) ## Frequently asked questions **How much does AI for SOX testing cost?** Pricing varies by platform and scope. Workflow tools like AuditBoard typically price per user per year. AI-native platforms like Bead AI price based on testing volume. Most teams see ROI within one SOX cycle by reducing co-sourcing spend and manual testing hours. **Can AI replace SOX auditors?** No. AI automates the repetitive execution steps — evidence collection, sample testing, working paper generation — but human auditors still review exceptions, apply judgment to edge cases, and sign off on conclusions. AI shifts auditors from data processing to risk assessment. **Is AI-generated SOX testing documentation accepted by external auditors?** Yes, provided the documentation includes a clear audit trail showing what was tested, what criteria were applied, what exceptions were found, and how conclusions were reached. AI-native platforms generate this traceability by design. **What types of controls can AI test?** AI works best for controls with structured, digitally available evidence: automated approvals, system access reviews, transaction matching, segregation of duties, and reconciliation controls. Controls requiring physical observation or highly qualitative judgment still need human testing. --- --- title: "The Audit Leader's Guide to AI for SOX Testing" description: "A free 8-chapter field guide (~90 min, PDF and print) on making AI agents work inside a SOX program. Vendor-neutral, written for Internal Audit leaders." url: "https://usebead.ai/book" --- # The Audit Leader's Guide to AI for SOX Testing A short, opinionated field guide for Internal Audit leaders on making AI agents work inside a SOX program. - Agents - Audit Trail - ROI - 90-Day Pilot - Build · Buy · Configure - Evidence - External Audit 8 chapters · ~90 minutes · PDF + print. Vendor-neutral. ![Cover of The Audit Leader's Guide to AI for SOX Testing](https://usebead.ai/images/book-cover.jpeg) ## What's in the book? Get a clear overview of AI Agents. Understand where they are useful, how to apply them, and the limitations. **1\. The Manual Machine** - The Director's Chair - The Numbers - The Budget Squeeze - The Team Tax - This Is Accelerating **2\. Why SOX Automation Failed** - Why SOX Evidence Is Uniquely Hard - What RPA Got Right, and Where It Broke - Prompts - Why Prompt Libraries Stall - Key Takeaways **3\. What AI Agents Actually Are** - The Comparison: Prompts vs. Agents - So What Is an Agent? - What Changed in 2025 - Why a Bigger Prompt Is Not the Answer - The Six Components of an Agent - Key Takeaways **4\. Where AI Agents for SOX Testing Work Now** - Evidence Intake and Pre-Testing Validation - C&A Testing - Transactional Controls and Population-Level Testing - Complex Spreadsheets - Screenshot- and Log-Heavy ITGC - UAR and Access Provisioning - Where to Be Careful - Use Cases Map - Key Takeaways **5\. The Audit Trail That Makes It Defensible** - Why Prompts Are Not Workpapers - The Five Layers of a Defensible AI Agents Audit Trail - Walkthrough: The Five Layers in Action - Why AI Agents for SOX Can Enhance Manual Testing - External Audit Readiness - The Regulatory Guidance - Key Takeaways **6\. Build, Buy, or Configure** - The Three Paths - Path 1: Configure - Path 2: Build - Path 3: Buy - How to Evaluate - Beyond the Pilot - Common Mistakes - Key Takeaways **7\. The Internal Case** - The Foundation - Establishing the Baseline - The ROI Calculation - The 90-Day Pilot - Pick the Right Pilot - The Pilot Scorecard - The CFO Memo - Key Takeaways **8\. The Next 18 Months** - More Autonomous Audits - Evidence Collection Will Change First - From Periodic Testing to Broader Monitoring - Auditing Agents vs. Auditing Humans - From Discrete Cycles to Continuous Loops - The Enterprise Trust Layer - What Stays Stubbornly Manual - What Changes for the Team - Key Takeaways --- --- title: "Careers at Bead AI | San Francisco" description: "Open roles at Bead AI, a small product-obsessed team in San Francisco building AI agents that run SOX and internal audit testing." url: "https://usebead.ai/careers" --- # Bead is reimagining auditing for the AI era We are building an autonomous trust layer to enable audits to shift from a compliance burden to a world where auditors can be risk navigators, providing companies the assurance needed to adjust continuously in an ever changing world. We are a small, product-obsessed team based in San Francisco, backed by some of the world’s leading investors and driven by the ambition to use AI to reinvent a whole industry. ## Open roles 1 - [Founding Account Executive San Francisco, Remote, US](https://jobs.gem.com/bead-ai/am9icG9zdDpbvz4ohocnw9GczvwIx6_O) --- --- title: "Book a Bead AI Demo: AI SOX Testing in Action" description: "Book a call to see how Bead AI automates SOX testing: agents run your testing plans, handle evidence, and produce working papers." url: "https://usebead.ai/contact" --- # Watch agents test your controls - A control tested live, working paper in your Excel template - 70% less testing time - Trusted from mid-cap to the Fortune 10 Built and backed by people from - EY - KPMG - Meta - OpenAI - BlackRock - a16z speedrun SOC 2 Type II audited. Your data is never used for model training ([security](https://usebead.ai/security)). To request a demo, fill in the form on this page, or book a call directly at https://cal.com/team/bead-ai/demo. Email: founders@usebead.ai. --- --- title: "Acceptable Use Policy" description: "What customers may and may not do with the Bead AI platform, including prohibited, abusive, illegal and security-compromising uses." url: "https://usebead.ai/legal/acceptable-use-policy" --- # Acceptable Use Policy This Acceptable Use Policy is part of Your Terms with Bead AI. Any terms used but not defined in this Acceptable Use Policy have the meaning set forth in the Terms. You agree not to, and not direct or allow third parties to use the Bead AI Platform: - to violate, or encourage the violation of, the legal rights of others; - to engage in, promote or encourage illegal activity; - for any unlawful, invasive, infringing, defamatory or fraudulent purpose; - to affirmatively represent or hold out Output as solely human-generated; - to intentionally distribute viruses, worms, Trojan horses, corrupted files, hoaxes, or other items of a destructive or deceptive nature; - to interfere with the use of the Services, or the equipment used to provide the Services, by anyone; - to disable, interfere with or circumvent any aspect of the Services; - to use the Services in violation of the Terms; and - to build similar or competitive products or features of the Bead AI Platform or of our subcontractors. --- --- title: "AI Policy" description: "How Bead AI develops and deploys AI in the platform: compliance with AI regulations, data sourcing, accuracy and reliability testing, and transparency." url: "https://usebead.ai/legal/ai-policy" --- # AI Policy This Artificial Intelligence Policy (the “AI Policy”) sets out Bead AI’s approach to the development and deployment of artificial intelligence (“AI”) in connection with its service (that is, app.usebead.ai) (the “Service”). The AI Policy is intended to provide transparency regarding Bead AI’s practices and principles relating to the use of AI, including compliance with applicable laws, responsible use, data sourcing, technical and organizational measures, transparency, and risk management. This AI Policy serves as a statement of Bead AI’s current practices and commitments in relation to the responsible use of AI. Bead AI may update or amend this AI Policy from time to time to reflect changes in technology, regulation, or industry best practices. This AI Policy should be read alongside any AI acceptable use policy that Bead AI releases from time to time, which can be found at usebead.ai/legal. ## 1\. Compliance with laws To the extent applicable to Bead AI’s provision of the Service, Bead AI will comply with applicable laws, regulations or directives in relation to the provision of AI (collectively, “AI Regulations”). ## 2\. AI literacy and responsible use Bead AI will take steps to ensure a sufficient level of AI literacy of its employees dealing with the operation and use of AI in connection with the Service in accordance with the AI Regulations. Bead AI has implemented and will maintain internal policies and procedures for the ethical and responsible use of AI. ## 3\. Data sources Bead AI will take steps to obtain all necessary rights and/or licenses required to use the data sets that are incorporated into the Service and implement procedures to monitor and verify compliance with third parties when collecting such data. ## 4\. Technical and organizational measures Bead AI implements and maintains a number of technical and organizational measures in relation to the development and provision of AI technologies in connection with the Service. Examples of such measures include: - internal policies to regulate the use and development of AI; - a number of security measures, including those described in our Security Addendum available at usebead.ai/legal; - testing to establish, monitor, and verify the level of accuracy and reliability, and suitability of AI used for the purpose of the Service; and - change management processes to ensure continuing compliance with applicable laws and industry standards. ## 5\. Transparency Bead AI has implemented procedures to assist you in ensuring that those natural persons that you choose to interact with the Service are informed that they are interacting with AI. --- --- title: "Cookie Policy" description: "Which cookies usebead.ai sets, what each one is for, how long it lasts, and how to change your consent at any time." url: "https://usebead.ai/legal/cookie-policy" --- # Cookie Policy ## Application This policy applies to all employees, contractors, and vendors while doing business with Bead Technologies Inc. and others who have access to European Union (EU) and the European Economic Area (EEA) data subject information (“personal data”) in connection with Bead Technologies Inc’s’ operating activities. ## Policy Bead Technologies Inc. believes in transparency about collection and use of data. This policy provides information about how and when Bead Technologies Inc. uses cookies for these purposes. Capitalized terms used in this policy, but not defined, have the meaning set forth in our Privacy Policy, which also includes additional details about the collection and use of information at Bead Technologies Inc. ## What is a cookie? Cookies are small text files sent by us to your computer or mobile device, which enable Bead Technologies Inc. features and functionality. They are unique to your account or your browser. Session-based cookies last only while your browser is open and are automatically deleted when you close your browser. Persistent cookies last until you or your browser delete them or until they expire. ## Does Bead Technologies Inc. use cookies? Yes. Bead Technologies Inc. uses cookies and similar technologies like single-pixel gifs. Bead Technologies Inc. uses both session-based and persistent cookies. Bead Technologies Inc. sets and accesses cookies on the domains operated by Bead Technologies Inc. and its corporate affiliates (collectively, the “Sites”). In addition, Bead Technologies Inc. uses third party cookies, like Google Tag Manager. ## How is Bead Technologies Inc. using cookies? Some cookies are associated with your account and personal information to remember that you are logged in and which workspaces you are logged into. Other cookies are not tied to your account but are unique and allow us to carry out analytics and customization, among other similar things. Cookies can be used to recognize you when you visit a Site or use our Services, remember your preferences, and give you a personalized experience that is consistent with your settings. Cookies also make your interactions faster and more secure. ## Categories of use - **Authentication:** If you’re signed into the Services, cookies help Bead Technologies Inc. show you the right information and personalize your experience. - **Preferences, features, and services:** Cookies denote UI preferences and settings allowing you to persist your preferences across visits. - **Marketing:** Bead Technologies Inc. may use cookies to help deliver marketing campaigns and track their performance (e.g., a user signed up to Bead Technologies Inc.). Similarly, Bead Technologies Inc’s partners may use cookies to provide us with information about your interactions with their services, but use of those third-party cookies would be subject to the service provider’s policies. - **Performance, Analytics, and Research:** Cookies help Bead Technologies Inc. learn how well the Sites and Services perform. Bead Technologies Inc. also uses cookies to understand, improve, and research products, features, and services, including to create logs and record when you access our Sites and Services from different devices, such as your work computer or your mobile device. ## What third-party cookies does Bead Technologies Inc. use? You can find a list of the third-party cookies that Bead Technologies Inc. uses on our sites along with other relevant information in the cookie list below. Bead Technologies Inc. does its best to keep this list updated, but please note that the number and names of cookies, pixels, and other technologies may change from time to time. ## How are cookies used for advertising purposes? Cookies and other ad technology such as beacons, pixels, and tags help Bead Technologies Inc. market more effectively to users that may be interested in the Services. They also help with aggregated auditing, research, and reporting. ## What can you do if you don’t want cookies to be set or want them to be removed? You can opt out of cookies being used via the banner shown on your first visit to our website ([https://usebead.ai](https://usebead.ai/)). To change your answer later, use the **Cookie settings** link in the site footer. You can also manually delete any cookies you do not want to be stored. ## Cookies List ### Strictly Necessary Cookies These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but that will cause some parts of the site to not work. These cookies do not store any personally identifiable information. Framer Domains: .usebead.ai Cookie names: \_ga\* First party ### Other Cookies These cookies allow Bead Technologies Inc. to count visits and traffic sources, errors and preferences. They help us improve the experience of the product, know which pages are the most and least popular and report errors encountered by users. If you do not allow these cookies you will be able to use the product but might restrict certain functionality. Bead Domains: .app.usebead.ai Cookie names: stytch*session*\* First party ### Third Party Website Cookies When using our website, you may be directed to other websites for such activities as surveys, to make payment, for job applications, and to view content hosted on those sites such as an embedded video or news article. These websites may use their own cookies. We do not have control over the placement of cookies by other websites you visit, even if you are directed to them from our website. ## How To Control and Delete Cookies ### Using Your Browser Many of the cookies used on our website and through emails can be enabled or disabled through our consent tool or by disabling the cookies through your browser. To disable cookies through your browser, follow the instructions usually located within the “Help,” “Tools” or “Edit” menus in your browser. Please note that disabling a cookie or category of cookies does not delete the cookie from your browser unless manually completed through your browser function. ### Cookies Set in the Past Collection of your data from our analytics cookies can be deleted. If cookies are deleted, the information collected prior to the preference change may still be used. However, we will stop using the disabled cookie to collect any further information from your user experience. For our marketing cookie, when a user opts out of tracking, a new cookie is placed to prevent users from being tracked. --- --- title: "Privacy Policy" description: "How Bead AI collects, uses, stores and deletes personal data, the rights you have over it, and who to contact about a request." url: "https://usebead.ai/legal/privacy-policy" --- # Privacy Policy Bead takes your privacy seriously where we deal with your personal data. This means information that identifies you personally, such as your name and contact details, or data that can be linked to such information to identify you, directly or indirectly. References to “Bead”, “Bead AI”, “we”, “us”, or “our” in this privacy notice are to Bead Technologies Inc. We are the Controller of your personal data (this means we are responsible for how it is used). Please read this privacy notice carefully as it contains important information on who we are and how and why we collect, store, use, and share your personal data. It also explains your rights regarding your personal data and how to contact us or the relevant authorities if you have a complaint. This privacy notice does not cover any personal data processed by us or any of our clients in relation to the Bead Audit Platform. Please contact the relevant Bead client for information on the use of personal data in relation to the audit platform. ## Your Personal Data and How We Use It We collect personal data about you, either directly from you, from a third-party source or by automated means (when you use our website for example). Under data protection law we can only use your personal data where we have a lawful basis (justification), and this can be either “to carry out a contract with you or to take steps on your instruction prior to entering into a contract with you”; “where we have a legal obligation”; “where you have given us your consent”; or “where it is necessary for our legitimate interests” (this means that we have a business or commercial interest in using your personal data). The table below sets out clearly how we collect and use your personal data and the lawful bases we rely on for using your personal data. Where we have said that using or keeping your personal data is “necessary for our legitimate interests”. Please note that if you choose not to provide personal data requested by us, or refuse our use of your personal data, we may not be able to provide you with the services you have requested where this personal data is necessary or these services may be delayed. ## Information you give us ### Access to Audit Platform You give us personal data about you when you request access to our audit platform. This is generally information including your work email, details of company/business (including current audit setup), and specific areas of business interest. Legitimate interest: We use your personal data to provide you with access to our audit platform where you have requested this, including determining if our platform is suitable for your company/business and contacting you concerning your request. ### Marketing Communications and Updates We may use your personal data to send you marketing communications and updates about our progress and what we are up to. This is generally information including your email address and your marketing preferences. Consent: We rely on your consent to use your personal data to send you marketing communications via email. We will only do this in line with your marketing preferences and you can opt-out of receiving these communications at any time by selecting the unsubscribe link in any email we send you, or by contacting us. ### Suppliers/Partners and Representatives You give us personal data about you when you enter into a supplier/partnership agreement or relationship with us or are a representative of a supplier/partner. Performance of a contract/legitimate interest: We use your personal data to contact you and to manage our relationship with you and/or your company where you are a supplier/partner or the representative of a supplier/partner with whom we have a business relationship. ### Recruitment You give us personal data about you when you express interest or apply for a job role with us on our website or otherwise. This is generally information including name, email, phone number, current company name, current job role, job role applied for, CV, education history, job expectations, assessment results and interview notes. Performance of a contract/Taking steps to enter into a contract: We use your personal data for the purposes of managing our recruitment for job roles in our organisation, including reviewing job applications, setting up and conducting interviews and tests for applicants, evaluating and assessing the results thereto, and as is otherwise needed in the recruitment and hiring processes. Legal obligation: We use your personal data for the purposes of complying with any legal requirements involved in the recruitment process (e.g. making reasonable adjustments for candidates). ### Contacting Us You give us personal data about you when you contact us or otherwise interact with us, including via phone, email, post or social media. Performance of contract/legitimate interest: To respond to your inquiries and fulfil your requests, for example, when you send us questions, suggestions, compliments or complaints, or when you request information about our customer services platform or other offerings. We may also take this information into account when improving our platform, products and services. ## Information we collect automatically ### Visiting our Website We collect personal data about you automatically when you visit and interact with our website. Our servers keep an activity log unique to you that collects certain administrative and traffic information including your device details, device location, source IP address, time of access, date of access, web page(s) visited, language use, software crash reports and type of browser used. Legitimate interests: We use your personal data to make sure you are able to use our website, to monitor how our website is being used, to help us discover and fix any problems with our website and to determine what country you are in when you use our website. ## Information provided by third parties ### Prospecting – Public Professional Networks We may collect personal data about you from your public profile on professional networks (e.g. LinkedIn) where it is lawful to do so and we think you or your company may be interested in our offerings and services. This is generally information contained in your public profile such as name, email and current job role. Legitimate interests: To contact you with sales communications about our customer service offerings which we think will be of interest to you and/or your company. We will only do this where we are sure that our customer service offerings are relevant to you, and you can opt-out of receiving these communications at any time by selecting the unsubscribe link in any email we send you, or by contacting us. ### Recruitment – Referrals, Job Boards and Public Professional Networks We may collect your personal data where you have been referred to us by a third party for potential employment (e.g. a recruiter or a friend of yours who is an employee) or from your public profile on job boards or professional networks (e.g. LinkedIn) where it is lawful to do so and if we think you may be a good fit for a job role at Bead. This is generally information including your name, email, phone number, company name, job role and CV related information. Legitimate interest: To contact you in relation to job roles at Bead where we think you will be a good fit for our recruitment process. When you visit or log in to our website, cookies and similar technologies may be used by our online data partners or vendors to associate these activities with other personal information they or others have about you, including by association with your email. We (or service providers on our behalf) may then send communications and marketing to these email. You may opt out of receiving this advertising by visiting [https://app.retention.com/optout](https://app.retention.com/optout). ## How We Share Your Personal Data We share your personal data for the following purposes and in line with this privacy notice: ### General sharing We share your personal data with trusted third parties who perform functions on our behalf and help us provide you with the services we offer and also in operating and maintaining our website. Third parties such as service providers (including website and cloud providers, database management providers, business communication providers, email distribution providers, direct marketing and data collection providers, data storage and analysis providers, and customer service support providers), business consultants, and professional advisors (including lawyers and accountants). These third parties comply with similar and equally stringent undertakings of privacy and confidentiality. We share your personal data if we are under a duty to do so, in order to comply with (or where we reasonably believe we are under a duty to comply with) any legal obligation, or in order to enforce any agreement we have in place with you; or to protect the rights, property, safety, or security of Bead, third parties, users of our services or the public. As we continue to develop our business, we may sell or purchase assets. If another entity acquires us or merges with us your personal data will be disclosed to such entity. We share your personal data where you give us express permission to do so in the course of your relationship with us from time to time. ### Recruitment Specific Sharing During the recruitment stage, we share your personal data with our online recruitment service providers and with your third party recruiter (if you have used one) to progress your application, and for the purposes of communicating with you about your application. If you successfully pass the recruitment stage and we hire you, we share your personal data with our internal HR systems providers for the purposes of your employment with us. ## International Transfers We are located in the United States (US) and generally store your personal data on servers within the US. If you require further information on transfers and the safeguards we have in place please contact us using our details below. ## AI Sub-Processors Our platform uses third-party large language models (“LLMs”) and generative AI services as sub-processors to deliver its AI-assisted features. When content is submitted to the platform, the relevant text and documents — which may contain personal data — are transmitted to these providers solely to generate the outputs requested (for example, audit analysis and testing). These providers process this data only on our instructions, do not use it to train their foundation models, and do not retain it beyond what is necessary to return a response. Our current AI sub-processors are: - Amazon Web Services, Inc. — Amazon Bedrock. Hosted foundation-model inference used to process submitted content and generate AI outputs. Processing occurs in the United States. Inputs and outputs are not used to train AWS or third-party model-provider models and are not retained by the service after a request is served. - Google LLC — Google Gemini (via Google Cloud Vertex AI). Generative AI inference used to process submitted content and generate AI outputs. Data is not used to train Google’s models, is not subject to human review, and is not retained beyond the request lifecycle. A current list of our sub-processors is maintained at our Trust Center ([trust.usebead.ai](http://trust.usebead.ai/)). ## Authentication We use Stytch, Inc. as our authentication provider to verify user identities and manage secure sign-ins and sessions for our platform. To do this, Stytch processes account identifiers such as your work email address, along with authentication tokens, session data, and related device/IP information, on our behalf and on our instructions. Stytch processes this data solely to authenticate users and secure access to the platform, and not for its own purposes. Processing occurs in the United States. ## Personal Data Retention We will retain your personal data for as long as needed or permitted considering the purpose(s) for which it was obtained and consistent with applicable law. The criteria we use to determine our retention periods include: The length of time we have an ongoing relationship with you; Whether there is a legal obligation to which we are subject; Whether retention is advisable in light of our legal position (such as in regard to applicable statutes of limitations, litigation or regulatory investigations); and Any guidelines issued by relevant legal and data protection authorities. ## Your Data Rights By law, you have a number of rights (subject to certain conditions and exceptions) when it comes to your personal data and can exercise any of these rights by contacting us. You have the right to object to us using your personal data where we rely on our “Legitimate Interest” as a lawful basis for using it ( See the “How We Use Your Personal Data” section above) or use it to send you any kind of direct marketing (i.e. if you no longer want to receive marketing newsletters, updates and other marketing communications from us). ### The Right To Be Informed You have the right to be provided with clear, transparent and easily understandable information about how we use your personal data and your rights. This is why we are providing you with the information in this privacy notice. ### The Right of Access You have the right to ask us to see all your personal data that we hold about you and information on how we use it. ### The Right To Rectification You have the right to ask us to correct your personal data when it is inaccurate or incomplete. ### The Right To Erasure You have the right to ask for deletion or removal of your personal data where there is no compelling reason for us to keep using it. This is not a general right to erasure there are exceptions which may mean we are unable to comply with your request. ### The Right To Restrict Processing You have the right to ‘block’ or suppress further use of your personal data. When processing is restricted, we can still store your personal data, but not use it further. ### The Right To Data Portability You have the right to ask us to give you (or another company you choose) all the personal data we have collected from you directly in a structured and machine readable format (a format easy for computers to use and understand). ### The Right To Lodge A Complaint If you have concerns about how we handle your personal data, please contact us using the details below and we will work to resolve them. Depending on where you live, you may also have the right to raise the matter with the applicable state regulator or Attorney General. ### The Right To Withdraw Consent You have the right to withdraw your consent at any time where we rely on your consent as a lawful basis for processing your personal data (See “Your Personal Data and How We Use It” section above). ## Changes To This Privacy Notice We may periodically make changes to this privacy notice. We will notify you of any significant changes where we have a relationship with you and otherwise post updated versions here. We recommend that you revisit this Privacy Policy regularly. ## How to Contact Us If you wish to exercise any data subject rights or have any questions about this privacy notice or our information practices, please feel free to contact as [privacy@usebead.ai](mailto:privacy@usebead.ai) --- --- title: "Security Addendum" description: "The contractual security commitments behind Bead AI: certifications, data hosting, encryption, access controls, incident response and audit rights." url: "https://usebead.ai/legal/security-addendum" --- # Security Addendum This Security Addendum is part of Your Terms with Bead AI. Any capitalized terms used but not defined in this Security Addendum have the meaning set forth in the Terms. The computing services utilized to offer the Service are cloud-based and provided to Bead AI via one or more cloud service providers and represent our “Cloud Environment.” 1. Bead AI Audits and Certifications. 1.1. The information security management system used to provide the Service will be assessed by independent third-party auditors as described in the following audits and certifications (“Third-Party Audits”) on not less than an annual basis. SOC 2 Type II 1.2. Third-Party Audit reports are made available to You as described in Section 10.1. 1.3. To the extent that Bead AI decides to discontinue a Third-Party Audit, Bead AI will adopt an equivalent, industry-recognized framework. 2. Hosting Location of Customer Data and Content 2.1. Customer Data and Content will be stored and processed by Bead AI and its vendors in data centers located in the United States of America. 3. Encryption. 3.1. Bead AI encrypts Customer Data and Content at-rest using AES 256-bit (or better) encryption. Bead AI uses Transport Layer Security 1.2 (or better) for Customer Data and Content in-transit over public or untrusted networks. 3.2. We rotate encryption keys at least annually and utilize hardware security modules to safeguard critical encryption keys. Bead AI logically separates encryption keys from Customer Data and Content. 4. System and Network Security. 4.1. Bead AI personnel access to our Cloud Environment is with a unique user ID and is consistent with the principle of least privilege. Access requires a secure connection, multi-factor authentication, and passwords meeting or exceeding reasonable length and complexity requirements. 4.2. Bead AI personnel will not access Customer Data or Content except (i) to provide or support the Service or (ii) to comply with the law or a binding order of a governmental body. 4.3. In accessing our Cloud Environment, our personnel will use company-issued laptops which utilize security controls that include encryption and that also include endpoint detection and response tools to monitor and alert for suspicious activities, malicious code, and vulnerability management as described in Section 4.7. 4.4. Our Cloud Environment leverages industry-standard threat detection tools with daily signature updates, which are used to monitor and alert for suspicious activities, potential malware, viruses and/or malicious computer code (collectively, “Malicious Code”). Bead AI does not have an obligation to monitor Customer Data or Input for Malicious Code. 4.5. Bead AI engages an independent third party to conduct penetration tests of the Service at least annually. Summary results of such penetration tests can be made available to You as described in Section 10.1 at Your request, and contain, at a minimum: (i) name of penetration testing organization, (ii) date(s) of penetration test, (iii) scope of penetration test, (iv) mode of test / testing approach, and (v) brief summary of the findings. 4.6. Bead AI uses automated tools to scan publicly available vulnerability databases (e.g. National Vulnerability Database (NVD) or similar) for vulnerabilities in software that may be utilized by us. We score vulnerabilities according to an internal rating system that takes into account the likelihood of an exploit and the potential impact of an exploit, similar to CVSS. We timely address vulnerabilities. Those in the “critical” category are addressed within a maximum of 7 days, in the “high” category within 30 days, and in the “medium” category within 90 days. 4.7. Bead AI will engage a third party to conduct web application-level security assessments on the Service at least annually. Such assessments include tests for relevant security vulnerabilities identified in the Open Web Application Security Project (OWASP), including cross-site request forgery, cross-site scripting (XSS), SQL injection (SQLi), authentication and authorization vulnerabilities, and other. 5. Administrative Controls. 5.1. Bead AI maintains security awareness and training programs for its personnel including at time of on-boarding and at least annually thereafter. Such security awareness training includes the following topics: (i) individual responsibilities in terms of information security and data privacy, (ii) understanding of our IT security policies and standards, (iii) guidance on how to protect information from existing and emerging cyber threats such as phishing emails, and (iv) requirements for maintaining the security of their devices, credentials, and accounts. 5.2. Bead AI trains all software developers on secure development practices appropriate to their role at least annually. Training content is adjusted depending on the evolving threat landscape and may include threat modeling, secure design principles, prevention of authentication and authorization bypass attacks, prevention cross-site scripting attacks, prevention of cross-site request forgery attacks, and prevention of the use of vulnerable libraries. 5.3. Bead AI personnel are required to sign confidentiality agreements and are required to acknowledge responsibility for reporting security incidents involving Customer Data and Content. 5.4. Bead AI removes access to critical systems (including systems containing Customer Data and Content) for all separated personnel within 1 day and removes access to all systems within 3 days. Bead AI additionally reviews the access privileges of its personnel to its cloud environment at least quarterly. 5.5. Bead AI reviews external threat intelligence, including US-Cert vulnerability announcements and other trusted sources of vulnerability reports. U.S.-Cert announced vulnerabilities rated as critical or high are prioritized for remediation in accordance with Section 4.6. 5.6. Bead AI will conduct the following background screening checks for all personnel with access to Customer Data and Content, to the extent permitted under applicable law: (i) ID check, (ii) right to work check, and (iii) criminal history check. 5.7. Bead AI reviews all highly-privileged accounts (“administrator” or “root” accounts) in systems that contain or have access to Customer Data and Content at least quarterly and reduces administrative access if it is no longer needed (in other words, the least privilege principles are followed). 6. Vendors and Sub-Processors. 6.1. Bead AI ensures that any of its vendors that process Customer Data or Content maintain security measures consistent with our obligations under this Security Addendum. 7. Physical Data Centre Controls. 7.1. Our Cloud Environment is maintained by one or more cloud service providers. We ensure that our cloud service providers data centers have appropriate controls as audited under their third-party audits and certifications. Each cloud service provider will have SOC 2 Type II annual audit and ISO 27001 certification, or industry recognized equivalent frameworks. Such controls include: Physical access to facilities are controlled at building ingress points; Visitors are required to present ID and must be signed in; Physical access to servers is managed by access control devices; Physical access privileges are reviewed regularly; Facilities utilize monitor and alarm response procedures; Facilities utilize CCTV; Facilities have adequate fire detection and protection systems; Facilities have adequate back-up and redundancy systems; and Facilities have appropriate climate control systems. 7.2. Bead AI does not maintain physical offices other than for limited corporate and executive purposes. Under no circumstances is Customer Data or Content stored or hosted at such offices. 8. Incident Detection and Response. 8.1. If Bead AI becomes aware of a breach of security leading to the destruction, loss, alteration, unauthorized disclosure of, or access to Customer Data or Content (a “Security Incident“), Bead AI will notify You without undue delay, and in any case, within 48 hours after becoming aware. You will be notified at the security notice email address indicated on Your currently operative order form or as otherwise determined appropriate by Bead AI. 8.2. In the event of a Security Incident as described above, Bead AI will promptly take reasonable steps to contain, investigate, and mitigate any Security Incident. Any logs determined to be relevant to a Security Incident, will be preserved for at least one year. 8.3. Bead AI will provide You with timely information about the Security Incident, including the nature and consequences of the Security Incident, the status of our investigation, and a contact point from which additional information may be obtained. Bead AI will also share information about the measures taken or proposed by Bead AI to mitigate or contain the Security Incident after the investigation into the Security Incident has concluded. Customer acknowledges that because Bead AI personnel may not have visibility to the content of Customer Data and Content, it may be the case that we are unable to provide detailed analysis of the type of Customer Data and Content impacted by the Security Incident. Communications in connection with a Security Incident will not be construed as an acknowledgment by Bead AI of any fault or liability with respect to the Security Incident. 9. Audit Logging. 9.1. Bead AI will create, protect, and retain information system audit records to the extent needed to maintain integrity, and will enable the monitoring, analysis, investigation, and reporting of unlawful, unauthorized, or inappropriate information system activity. Actions of human information system users can be uniquely traced to those users. 9.2. Audit logs are retained for the minimum of 1 year, and may be retained up to a maximum of 10 years. Audit logs are protected against tampering. 10. Customer Audit Rights. 10.1. Upon request, and at no additional cost to You, Bead AI will provide You and/or Your appropriately qualified third-party representative (collectively, the “Auditor“) access to reasonably requested documentation evidencing our compliance with our obligations under this Security Addendum in the form of, as applicable, (i) Bead AI’s SOC 2 Type II audit report , plus relevant penetration test summaries and data flow diagrams as well as a statement of applicability (collectively with Third-Party Audits, “Audit Reports”). Where an Auditor is a third-party, such third party will be required to execute a separate confidentiality agreement with Bead AI prior to any audit, penetration test, or review of Audit Reports, and Bead AI may object in writing to such third party if in Bead AI’s reasonable opinion the third party is not suitably qualified. Any such objection will require You to appoint another third party to review such Audit Reports. Bead AI is not responsible for any expenses incurred by an Auditor in connection with any review of Audit Reports. 10.2. Once a year, You may submit reasonable security questionnaires (not to exceed 100 questions total) and requests for updated security documentation, and Bead AI commits to provide results within a timely fashion and at Bead AI’s own cost. 10.3. In the event of a Security Incident involving Customer Data or Content, Bead AI commits that it will engage an independent forensic specialist or similar firm at its own cost, and to the extent that Your Customer Data or Content is impacted, Bead AI will provide the results of such a report to You in a timely fashion. 11. Customer Responsibilities. 11.1. It is Your responsibility to ensure that You are authorized to use any Input or Customer Data with the Service and that Your usage complies with relevant legal and regulatory obligations. 11.2. You are responsible for managing and securing Your methods to access the Service (for example, password, SSO connections, email inboxes for email-code-authentication, etc.). User credentials must be kept confidential and may not be shared with unauthorized parties. A single account may not be shared among multiple persons. You must promptly report any suspicious activities related to Your account(s) (such as when You reasonably believe that credentials have been compromised). 11.3. You are responsible for keeping Your relevant IT systems (such as the browser You use to access the Service) up-to-date and appropriately patched. 12. Business Continuity and Disaster Recovery. 12.1. Bead AI maintains business continuity plans that detail how operations will be maintained during an unplanned disruption in service. This includes contingencies for business processes, assets, human resources, and business partners, and cover key information, system, and services. Continuity plans are approved by senior management and reviewed and tested annually. --- --- title: "Terms of Service" description: "The contract terms for using the Bead AI platform: permitted use, ownership of Customer Data, warranties, limitation of liability and termination." url: "https://usebead.ai/legal/terms-of-service" --- # Terms of Service 1. Important Terms. 1.1. These evaluation terms of service (this “Agreement”) are between Bead AI and You and govern Your use of the Service. If You are using the Service on behalf of another entity (such as your employer), You must have the authority to accept these Terms on their behalf. 1.2. By using the Service, the parties are agreeing to this Agreement, our Acceptable Use Policy, our Service Terms, and our Security Addendum, which are collectively referred to as the “Terms” and which are enforceable like any written contract. 1.3. Bead AI may update the Terms by posting updated Terms on our website. All changes become effective when posted. Such changes are not retroactive, but Your continued use of the Service after any such changes means You agree to such changes. Notwithstanding the above, in no event may Bead AI alter these Terms in a way that meaningfully detracts from its obligations with respect to Confidential Information, Customer Data, or Customer Content as agreed to in these Terms without express written authorization from You. 1.4. The Service is an automation tool. The Output of the Service is partially AI-generated, and may contain errors and misstatements or may be incomplete. 2. Definitions. The definitions in Section 11 (Defined Terms) apply to these Terms. All terms in quotation marks in the body of this Agreement are also defined terms. 3. Usage. 3.1. You may access, and we grant You the non-exclusive right to use, the Service pursuant to the Documentation. Access credentials are specific to the user to whom they are issued and may not be shared, including within the same organization. You will take reasonable steps to prevent unauthorized use of the Service. 3.2. Your usage of the Service is governed by these Terms. You will interact with the Service by providing Input to the Service and receiving Output from the Service. You and Your users may only use the Service for Your business purposes. 3.3. You may not (a) use the Service in a way that infringes, misappropriates, or violates any person’s rights; (b) access or use the Service from within any Embargoed Countries; (c) attempt to reverse engineer or attempt to discover the source code or engineering of the underlying model and systems of the Service or Bead AI’s subcontractors; or (d) attempt automated means to scrape content or Output from the Service. 3.4. To the extent that You provide us with any Feedback, we may freely use and incorporate any Feedback into our products and services. Bead AI may not utilize Feedback in a way that identifies, or could be used to identify, Customer, its users, Customer Data, Your Content, or Customer’s Confidential Information. 3.5. Any third party software, services, or other products You use in connection with the Service (for example, Your internet browser) are subject to their own terms, and we are not responsible for such third party products. 4. Content. 4.1. You may provide Input to the Service and receive Output from the Service. As between the parties, You own Your Content. 4.2. You may provide Input that is similar or identical to a third party’s user’s Input or may receive Output that is similar or identical to Output provided to other third party users. Queries that are requested by other third party users and responses provided to other third party users are not Your Content. 5. Customer Data. 5.1. To utilize certain features, You may be required to upload documents (“Customer Data”) into the Service for the purpose of enabling certain features. 5.2. As between the parties, You retain all right, title and interest (including any and all intellectual property rights) in and to the Customer Data. You grant to Bead AI and its Affiliates a non-exclusive, worldwide, royalty-free right to process the Customer Data and Your Input to the extent necessary to provide the Service to You, to prevent or address service or technical problems with the Service, or as may be required by applicable law. 5.3. Your use of the Service and all Customer Data will comply with applicable laws, government regulations, and any other legal requirements, including but not limited to, any data localization or data sovereignty laws, regulations, and any other third-party legal requirements applicable to You. You are responsible for the accuracy, content and legality of all Customer Data. 6. Fees and Payments. You are utilizing the Service via an authorized free trial, and You agree that You will do so in accordance with Your instructions from Bead AI. If we believe that You are not using the free trial in good faith, we may immediately terminate Your access to the Service. We reserve the right to limit the resources and features available to free trial users. 7. Term and Termination. 7.1. These Terms take effect when You first use the Service and remain in effect until terminated. You may terminate these Terms at any time by discontinuing the use of the Service and providing notice to us. We may similarly terminate upon notice at any time. 7.2. Upon termination, You will stop using the Service, and You will promptly return, or if instructed by us, destroy any Confidential Information. The sections of these Terms that customarily would survive such an agreement will survive (for example, provisions around confidentiality, obligation to pay unpaid fees, etc.). 7.3 Within 30 days of termination, Bead AI will securely delete any remaining Customer Data or Content unless otherwise instructed by You. 8. Warranty and Disclaimer. 8.1. You warrant that You have the necessary rights in Your Customer Data and Input to use it with the Service and that Your use of the Service will comply with all applicable laws and regulations. 8.2. The Service is provided on an as-is and as-available basis. Bead AI makes no representations or warranties of any kind, implied or expressed, with respect to the Service including warranties of merchantability, title, non-infringement, or fitness for a particular purpose, which are disclaimed. Bead AI does not represent or warrant that the use of the Service will be uninterrupted or error-free. 9. Limitation of Liability. 9.1. In no event will either party be liable to the other party or any third party for any indirect, incidental, special, exemplary, punitive, or consequential damages, including loss of income, data, profits, revenue, or business interruption, or the cost of substitute services or other economic loss, arising out of or in connection with these Terms, whether such liability arises from any claim based on contract, warranty, tort (including negligence), strict liability or otherwise, and whether or not such party has been advised of the possibility of such loss or damage. 9.2. Other than for claims based on liability which, by law, cannot be limited (for example, tort claims for gross negligence and intentional misconduct), in no event will either party’s total liability to the other party or any third party for all claims in the aggregate (for damages or liability of any type) in connection with these Terms exceed $1,000 (the “Liability Cap”). 10. General Terms. 10.1. Assignment. Neither party may assign these Terms without the advance written consent of the other party, except that Bead AI may (a) assign these Terms in their entirety to any Affiliate or (b) assign these Terms in connection with a consolidation, merger or sale of all or substantially all of our assets. 10.2. Subcontracting. Bead AI may use subcontractors and other third-party providers in connection with the performance of its activities under these Terms as it deems appropriate, provided that it remains responsible for the performance of any such subcontractors or third-party providers. 10.3. Severability and Interpretation. If a court of competent jurisdiction holds any provision of these Terms to be unenforceable or invalid, that provision will be limited to the minimum extent necessary so that these Terms will otherwise remain in effect. 10.4. Open Source Software. We warrant that we will not use any software in the Service that would cause Your software to become subject to an open source license that would require, as a condition of use, Your software to be disclosed or distributed in source code form or would give others the right to modify Your software. 10.5. Confidentiality. Each party (as the “Receiving Party”) will use the same degree of care that it uses to protect the confidentiality of its own confidential information of like kind (but not less than reasonable care) to: (a) not use any Confidential Information of the other party (the “Disclosing Party”) for any purpose outside the scope of these Terms; and (b) except as otherwise authorized by the Disclosing Party in writing, limit access to Confidential Information of the Disclosing Party to those of its and its Affiliates’ employees and contractors who need that access for purposes consistent with these Terms and who are bound by confidentiality obligations to the Receiving Party containing protections not materially less protective than this section. If the Receiving Party is required by applicable law or court order to disclose Confidential Information, then the Receiving Party will, to the extent legally permitted, provide the Disclosing Party with advance written notification and cooperate in any effort to obtain confidential treatment of the Confidential Information. The Receiving Party acknowledges that disclosure of Confidential Information would cause substantial harm for which damages alone would not be a sufficient remedy, and therefore that upon any such disclosure by the Receiving Party, the Disclosing Party will be entitled to seek appropriate equitable relief in addition to whatever other remedies it might have at law. 10.6. Usage Data. Bead AI may collect and use Usage Data to develop, improve, support, and operate the Service. Bead AI may not share Usage Data that includes Your Confidential Information with a third party (for example, auditors) except (a) in accordance with Section 10.5 (Confidentiality) of this Agreement, or (b) to the extent the Usage Data is aggregated and anonymized such that You cannot be identified. 10.7. No Training. Bead AI will not train any AI models using Your Content or Customer Data. Subprocessors will not train any AI models using Your Content or Customer Data. Subprocessors will not retain or log for human review Your Content or Customer Data. 10.8. Privacy Policy. Your users will be subject to our Privacy Policy to the extent not in conflict with these Terms in using the Service. 10.9. Governing Law. These Terms will be governed by the laws of the State of Delaware and the United States without regard to conflicts of laws provisions thereof, and without regard to the United Nations Convention on the International Sale of Goods. 10.10. Arbitration. Any dispute, claim or controversy arising out of or relating to this Agreement or its breach, including the determination of the scope or applicability of this Agreement to arbitrate, will be determined by arbitration in San Francisco. For matters with a disputed amount in controversy of more than $250,000, the matter will be heard before a panel of three arbitrators subject to JAMS’ Comprehensive Arbitration Rules and Procedures for other matters before a single arbitrator subject to JAMS’ Streamlined Arbitration Rules and Procedures. Judgment on the Award may be entered in any court having jurisdiction. This clause will not preclude parties from seeking provisional remedies in aid of arbitration from a court of appropriate jurisdiction. 10.11. Notice. All notices must be in writing (in English) and addressed to the parties via email: (i) for Bead AI, notice must be sent to [founders@usebead.ai](mailto:founders@usebead.ai); and (ii) for You, to the email address associated with Your user account. Notices will be deemed given upon receipt. Either Party may change its email address for notices under these Terms by providing the other Party written notice in accordance with this section. 10.12. No Waiver. No waiver will be implied from conduct or failure to enforce or exercise rights under these Terms, nor will any waiver be effective unless in a writing signed by the waiving party. 10.13. Entire Agreement. These Terms are the complete and exclusive statement of the mutual understanding of the parties in connection with Your use of the Service and supersede and cancel all previous written and oral agreements, understandings, and communications relating to the subject matter in these Terms. Each party represents that, in connection with the Service, it has not relied on any term or representation not contained in these Terms. 10.14. Export Control. The parties agree to comply with all export and import laws and regulations of the United States and other applicable jurisdictions. The Service may not be used in or for the benefit of, exported, or re-exported (a) into any U.S. embargoed countries or that has been designated by the U.S. government as a “terrorist supporting” country (collectively, the “Embargoed Countries”) or (b) to anyone on the U.S. Treasury Department’s list of Specially Designated Nationals, any other restricted party lists (existing now or in the future) identified by the Office of Foreign Asset Control, or the U.S. Department of Commerce Denied Persons List or Entity List, or any other restricted party lists. You represent and warrant that You are not located in any Embargoed Countries and not on any such restricted party lists. 10.15. Force Majeure. Neither party will be liable to the other for any delay or failure to perform any obligation under these Terms if the delay or failure results from any cause beyond such party’s reasonable control that could not have been prevented through the use of commercially reasonable safeguards, including acts of God, labor disputes, or other industrial disturbances, systemic electrical, telecommunications, or other utility failures, earthquake, storms or other elements of nature, blockages, embargoes, riots, public health emergencies (including pandemics and epidemics), acts or orders of government, acts of terrorism, or war. 11. Definitions. 11.1. “Acceptable Use Policy” means Bead AI’s policy governing the use of the Service as located at usebead.ai/legal. 11.2. “Affiliate” means any entity that directly or indirectly controls, is controlled by, or is under common control with the subject entity where “control,” for the purposes of this definition means direct or indirect ownership or control of more than 50% of the voting interests in the subject entity. 11.3. “Agreement” has the meaning set forth on the cover page. 11.4. “Basic Service” is the basic functionality of the Service made available to You under these Terms in which users provide Input and receive Output, and which does not include features such as Data Room/Vault, Customer-trained models, workflows, and certain research modules (such functionality is covered by an addendum or other writing that expressly references such functionality). 11.5. “Confidential Information” means all information that is identified as confidential at the time of disclosure by the Disclosing Party or reasonably should be known by the Receiving Party to be confidential or proprietary due to the nature of the information disclosed and the circumstances surrounding the disclosure. Content specific to You and Customer Data are Your Confidential Information. 11.6. “Content” means Input and Output collectively. 11.7. “Bead AI” means Bead Technologies Inc., a Delaware corporation as well as all of its Affiliates. 11.8. “Customer Data” has the meaning set forth in Section 5.1. 11.9. “Disclosing Party” has the meaning set forth in Section 10.5. 11.10. “Documentation” means the technical and other documents regarding usage of the Service as may be made available to You. Bead AI may update the Documentation from time-to-time. 11.11. “Embargoed Countries” has the meaning set forth in Section 10.15. 11.12. “Feedback” means any suggestions, enhancement requests, recommendations, corrections, or other feedback provided to Bead AI by You relating to our offerings. 11.13. “Input” means the query provided by a user to the Service. 11.14. “Liability Cap” has the meaning set forth in Section 9.2 11.15. “Output” means the output provided by the Service to a user in response to such user’s Input. 11.16. “Privacy Policy” means Bead AI’s policy governing the privacy provisions related to the Service as located at usebead.ai/legal. 11.17. “Receiving Party” has the meaning set forth in Section 10.5. 11.18. “Security Addendum” means Bead AI’s addendum governing the security provisions located at usebead.ai/legal. 11.19. “Service” means the software-as-a-service offering made available by Bead AI at [https://app.usebead.ai](https://app.usebead.ai/). 11.20. “Service Terms” means the additional terms that govern the use of preview features as well as other optional offerings and features of the Service as located at usebead.ai/legal. 11.21. “Subprocessor” means any subcontractor or vendor of Bead AI that has access to or otherwise processes Customer Data or Your Content. 11.22. “Terms” has the meaning set forth in Section 1.1. 11.24. “Usage Data” means information reflecting the access, interaction, or use of the Service by or on behalf of Customer including frequency, duration, volume, features, functions, visit, session, click through or click stream data, and statistical or other analysis, information, or data based on, or derivative works of, the forgoing. Other than as strictly required for billing purposes, Usage Data does not include Your Content, Customer Data, or Customer Confidential Information. 11.26. “You” or “Your” means either (1) in the case of an individual, the person contracting for the use of the Service; or (2) in the case of a legal entity, the organization contracting for the use of the Service. 11.27. “We” or “we” or “Our” or “our” means Bead AI. --- --- title: "Website Terms" description: "The terms that govern use of usebead.ai: acceptable use of the site, intellectual property, disclaimers and governing law." url: "https://usebead.ai/legal/website-terms" --- # Website Terms ## 1\. Introduction 1.1 These terms and conditions apply to the entire contents of [https://usebead.ai](https://usebead.ai/) (the “Website”) and contain important information explaining your rights to access and use the Website (“Website Terms”). The Website is operated by Bead Technologies Inc. (“we”, “our” or “us”). Please read these Website Terms carefully before using the Website. You should pay particular attention to the “Disclaimer of liability” section as this excludes or limits our legal liability in connection with your use of the Website. By accessing or using the Website you agree to be legally bound by these terms and conditions. If you do not wish to be bound by these terms and conditions then you may not use the Website. If you breach any of these Website Terms, your permission to use the Website automatically terminates and you must immediately destroy any downloaded or printed extracts from the Website. ## 2\. Changes to Website Terms 2.1 We may make changes to these Website Terms at any time without notice by updating these pages. You agree to review this section of the Website periodically to determine whether the Website Terms have been changed. Your access to or use of the Website (or any part of it) at any time shall constitute your agreement to the latest published version of the Website Terms. If you do not agree to any change to the Website Terms then you must immediately stop using the Website. Certain provisions of these Website Terms may be amended or superseded by legal notices or terms located on particular pages of the Website or on materials that are downloadable from the Website. ## 3\. Using the Website 3.1 This Website is a place for you to find out more about us. If you want to subscribe to our web-based customer service tool, click here, use of which is governed by our Terms of Service. Unless otherwise specified all content and materials published on the Website are presented solely for your private, personal and non-commercial use. The information and products shown on the Website are not intended for distribution to, or use by, any person or entity in any jurisdiction or country where such distribution or use would be contrary to law or regulation. If accessing the Website or using of any material or content on the Website infringes any applicable law in your jurisdiction(s), you are not authorised to access or use the Website and you must exit immediately. ## 3.2 We reserve the right to terminate your access to the Website at any time without notice. To find out how we process your personal data, please refer our Privacy Policy. ## 4\. Modifications to Website We reserve the right to make changes or corrections, alter, suspend or discontinue any aspect of the Website or the content or services available through it, including your access to the Website, with or without notice to you. Unless explicitly stated to the contrary, any new features including new content, will be subject to these Website Terms. You confirm that we will not be liable to you or any third party for any changes to or permanent or temporary withdrawal of the Website. ## 5\. Misuse of Website 5.1 You may use the Website for lawful purposes only. You must not misuse the Website, including, without limitation, by introducing viruses, Trojans, worms, logic bombs or other material which is malicious or technologically harmful. In particular, you must not access without authority, interfere with damage or disrupt the Website or any part of it; any equipment or network on which the Website is stored; any software used in connection with the provision of the Website; or any equipment, software or website owned or used by a third party. You must not attack the Website via a denial-of-service attack. Without prejudice to our other rights or remedies, we reserve the right to take legal proceedings against you for reimbursement of all costs or losses (on an indemnity basis) resulting from your breach of this section of the Website Terms, and to disclose such information to law enforcement agencies as we reasonably believe is necessary. ## 6\. Copyright 6.1 The contents of the Website are protected by international copyright laws and other intellectual property rights. All intellectual property rights in the contents of the Website (including, without limitation, all text, graphics, logos, names, artwork, photographs and videos) are owned by us or our licensors. All product and company names and logos mentioned on the Website are the trade marks, service marks or trading names of their respective owners. All rights are reserved. You may not modify, copy, reproduce, republish, upload, post, transmit or distribute, by any means or in any manner, any material or information on or downloaded from the Website including but not limited to text, graphics, video, messages, code and/or software without our prior written consent. 6.2 Any commercial use or exploitation of the Website or its content is strictly prohibited. ## 7\. Linked websites 7.1 Where the Website contains links to third party websites and resources, these links are provided for your information only. We have not reviewed these websites and are not responsible for their availability, accuracy or content or for any loss or damage that may arise out of your use of them. When you access any other Website you understand that it is independent from us and that we have no control over the content or availability of that website. Access to third party websites is entirely at your own risk. You should read any terms and conditions applying to the use of any third party website that you visit and address any complaints or queries relating to such websites to the operator of that website. Please be aware that a link to any other website does not mean that we endorse or approve of or accept any responsibility for the content, or the use of, such a website. You may not use any part of the Website on any other website or link any other website to the Website without our prior written permission. ## 8\. Disclaimer of liability 8.1 All content, materials and information on the Website are provided on an “as is” basis and “as available” basis, for information purposes only and without any conditions, warranties or other terms of any kind. You assume total responsibility and risk for your use of the Website and use of all information contained within it. We undertake no obligation to update the Website or to correct any inaccuracies which may become apparent, but reserve the right to do so without notice to you. 8.2 We will not be liable for any loss or damage caused by a distributed denial-of-service attack, viruses or other technologically harmful material that may infect your computer equipment, computer programs, data or other proprietary material due to your use of the Website or to your downloading of any material posted on it, or on any Website linked to it. ## 9\. Applicable Law 9.1 These Website Terms and any dispute or claim arising out of or in connection with them or their subject matter, whether of a contractual or non-contractual nature, shall be governed by and construed in accordance with the laws of the State of Delaware, without regard to its conflict of laws principles. You irrevocably agree that the courts of the State of Delaware shall have non-exclusive jurisdiction to settle any dispute regarding these Website Terms and any and all dealings between us and you. The Website has been approved for access in the US. We do not warrant or otherwise represent that the Website, use of the Website or these Website Terms (in whole or in part) are in compliance with laws or available for use in locations outside this territory. If you choose to access the Website from locations outside this territory, you do so at your own initiative and are responsible for compliance with local laws. ## 10\. Replacement These terms and conditions replace all other terms and conditions previously applicable to the use of the Website. --- --- title: "Deployment: Cloud, Private Cloud or On-Prem" description: "Run Bead AI as managed cloud, in a dedicated VPC in your own AWS region, or fully on-premises — same SOC 2 controls and zero-retention LLM inference." url: "https://usebead.ai/platform/deployment" --- # Deploy on your terms Choose the deployment model that fits your security requirements: from managed cloud to running inside your own network. ## Deployment options ### Cloud Managed multi-tenant with database RLS policies, S3 access points, and dedicated compute. ### Private Cloud Dedicated infrastructure in your own AWS region. Full network and data isolation, and custom data residency. ### On-Premises Bead AI runs inside your network. All data, infrastructure, and results stay on-prem. | | Cloud | Private Cloud | On-Premises | | --- | --- | --- | --- | | Managed by | Bead AI | Bead AI | Shared | | Tenant isolation | Logical | Dedicated VPC | Full network isolation | | Data residency | US | Any AWS region we support | You control | | Zero-retention LLM inference | Included | Included | Included | | Dedicated infrastructure | — | Included | Included | | Custom SLA | — | Included | Included | ## Common questions & Answers **Is data going to leave the environment?** In Cloud and Private Cloud, your data stays within Bead's SOC 2 audited infrastructure. For On-Premises, all data stays inside your network. In every deployment model, inference runs on Amazon Bedrock and Google Cloud Vertex AI inside Bead's own cloud account under zero-data-retention terms: only the minimum context a test needs is sent, nothing is stored or logged, and your evidence never reaches the companies that build the models. **Can I switch deployment model later?** Yes. You can migrate from Cloud to Private Cloud or On-Premises as your needs evolve. Our team handles the migration with zero downtime. **What compliance certifications apply?** SOC 2 Type II certification covers all deployment models. Our AI development is guided by ISO/IEC 42001 and NIST AI RMF frameworks. Penetration testing results are available under NDA. ## Not sure which option fits? Book a call and we'll walk through it. [Book a call](https://usebead.ai/contact) --- --- title: "MCP server: connect your AI tools to Bead" description: "Bead's MCP server connects Claude, ChatGPT, Gemini or Copilot to control testing: upload evidence, start tests and get answers, within your permissions." url: "https://usebead.ai/platform/mcp" --- # Bead inside your AI tools Connect Claude, ChatGPT, Gemini or Copilot to live control-testing data. Upload the evidence, start tests, generate working papers, or get answers about it, all inside your enterprise AI tool. [Book a call](https://usebead.ai/contact) Works with Claude, ChatGPT, Gemini, Microsoft Copilot, Cursor ## What you can do from your AI tool ### Upload evidence Attach files in the chat and they land on the right control test, checked on arrival like any other upload. ### Start tests Start a test against your existing plan. Agents run it over the full population and report back when it is done. ### Generate working papers Ask for the working paper and get it in your own template, with linked evidence and exception narratives. ### Check status Which controls are untested, which are with a reviewer and which have exceptions, as of the moment you ask. ### Explain a conclusion Read the decision log behind any result: the sample, the evidence and the judgment at each step. ### Compare periods Put quarters side by side to see which exceptions recur and where coverage has drifted. ## See it in action "Which key controls are still untested for Q3, and who owns them?" ## Security and permissions Your permissions, unchanged MCP follows the roles and permissions set in Bead. Approved per person, per assistant Connections are explicitly approved. An administrator can revoke connections. Every action under your name Uploads, test starts and working papers are recorded as your actions with a detailed [audit trail](https://usebead.ai/security). Zero-retention inference Inference runs on Amazon Bedrock and Google Vertex AI inside Bead's own accounts under zero-retention terms. SOC 2 Type II The same certified controls cover the MCP server as the rest of the platform. Penetration testing results are available under NDA. Runs where your data lives Available in every [deployment model](https://usebead.ai/platform/deployment): managed cloud, a private cloud in your own AWS region, or on-premises. ## What MCP is MCP, the Model Context Protocol, is an open standard for connecting an AI assistant to a product. A product supports it once, and any assistant with MCP support can read from it and act in it, under the permissions of the person who connected them. No vendor owns the standard, so if your organisation moves from one model to another, the Bead connection moves with it. ## Common questions & answers **Do I need a developer to set this up?** No. Connecting Bead works like connecting any other tool to your AI assistant. Open its connector settings, paste one address, and approve the request when Bead asks you to sign in. It takes about a minute and you do it yourself. **Can the assistant change anything in our audit?** Within your permissions, yes. An assistant can upload evidence, start a test or generate a working paper wherever you could do the same in Bead, and each action is recorded under your name. Anything you cannot do in the product, it cannot do either. **Can it see things I am not allowed to see?** No. Requests run as you. Bead applies the same permissions it applies when you use the product directly, so your assistant sees the controls, evidence and organisations you already have access to and nothing else. **Does our evidence end up training somebody else's model?** No. Inference runs under zero-data-retention terms in Bead's own cloud account, so nothing you ask about is stored or logged by the companies that build the models. Your own assistant is covered by a separate agreement between your company and that vendor. Check what it retains before you connect it. **Which AI assistants does it work with?** Any assistant that supports the Model Context Protocol, which today includes Claude, ChatGPT, Microsoft Copilot, Gemini and Cursor. MCP is an open standard, so a tool that adds support later works with Bead without any change on our side. **Can we turn it off for the organisation?** Yes. Access is granted per person and per assistant, so an administrator can revoke one connection or the whole integration, and it stops immediately. Nothing is cached outside Bead. ## See it on your own controls Book a call and we will connect an assistant to a working programme. [Book a call](https://usebead.ai/contact) --- --- title: "SOX Automation ROI Calculator" description: "A vendor-neutral calculator: enter control counts, testing hours, co-sourcing share and blended rates to see annual savings and payback period." url: "https://usebead.ai/roi" --- # Economics of Agentic SOX testing Calculate savings for your team by adjusting the values. Target positive payback in 4-6 months. Interactive calculator for the model described below, with every input adjustable. ## The model at its defaults The calculator estimates what testing with AI agents saves a SOX program in its first year. It prices a baseline from your control mix, testing hours and blended rates, applies automation and quality factors to testing and evidence-gathering work, then nets the cost of the software and implementation. These are its default assumptions, and every one is adjustable above. ### Default control mix | Control type | Controls | Hours per control | | --- | --- | --- | | ITGCs (Access, change mgmt, ops) | 35 | 6 | | Manual business-process (Journal review, approvals) | 80 | 10 | | Automated app controls (System-enforced) | 25 | 2 | | Key reports & IPE (Reports relied upon) | 30 | 8 | | Management review (MRCs, judgment-heavy) | 20 | 12 | | Entity-level (Tone, oversight) | 10 | 5 | ### Other defaults The defaults assume two testing cycles a year, an in-house rate of $150/h, and a co-sourcing rate of $325/h covering 40% of testing. Evidence gathering runs at 1× testing hours, priced at $100/h, with 25% of requests reworked. Vendor subscription $100,000 a year with no one-time implementation fee. The subscription default is a placeholder for the quote you are evaluating, not Bead's price. ### What the defaults produce | Result | At the defaults | | --- | --- | | Baseline testing and evidence effort | 6,758 hours a year | | Baseline annual cost | $1,057,350 | | Annual savings from automation | $335,681 | | First-year software and implementation cost | $114,080 | | Net first-year impact | $221,601 | | Simple payback | 4.1 months | --- --- title: "Security at Bead AI: SOC 2 Type II, Zero Retention" description: "SOC 2 Type II, US data residency, AES-256 at rest, tenant isolation, zero-retention inference. Evidence never reaches a model provider or trains a model." url: "https://usebead.ai/security" --- # How Bead AI protects your audit evidence Audit begins and ends with trust. We built Bead AI with that principle from day one. ## Our approach Our customers rely on Bead AI to process their most sensitive audit data. We treat every piece of evidence as if it were our own: with encryption, isolation, and access controls designed for the most demanding enterprise environments. Our platform is managed, standardized, externally audited, and built on the principle that security is never an afterthought. ## Your Data, Your Control No Model Training Customer data is never used to train or improve any AI model. Period. Never Sent to Model Providers Your evidence is never sent to the companies that build the models. Inference runs on Amazon Bedrock and Google Cloud Vertex AI inside our own cloud account under zero-data-retention terms, with only the minimum context a test needs. Nothing is stored or logged for human review. On-premises, nothing leaves your network. US Data Residency Customer data is stored and processed in the United States by default. A dedicated deployment can run in another AWS region where the services it depends on are available. ## Data Protection Encryption in transit and at rest TLS 1.2+ in transit. AES-256 at rest via AWS KMS. All backups encrypted and versioned Tenant Isolation Each customer environment is logically isolated with dedicated resources and unique credentials. SSO, MFA & RBAC SAML 2.0 single sign-on, multi-factor authentication, and role-based access control. Secure Deletion NIST-compliant sanitization on termination. Data export available prior to deletion upon request. ## Controls at a glance Every row below is a commitment in our[Security Addendum](https://usebead.ai/legal/security-addendum), which forms part of the contract.
Audit and attestationSOC 2 Type II, audited annually
Data locationData centres in the United States
EncryptionTLS 1.2+ in transit, AES-256 at rest, keys in HSMs and rotated at least annually
Vulnerability remediationCritical within 7 days, high within 30, medium within 90
Independent testingPenetration test and OWASP web application assessment, each at least annually
Breach notificationWithin 48 hours of Bead AI becoming aware
Audit log retentionBetween 1 and 10 years, protected against tampering
Access revocation on separationCritical systems within 1 day, all systems within 3
Your security reviewsUp to 100 questionnaire questions a year, answered at our cost
## Certifications and attestations - SOC 2 Type II, independently audited. The report is available through our [Trust Center](https://trust.usebead.ai/). - Penetration testing by an independent third party at least annually, plus an annual OWASP-based web application assessment. Summary results are available on request. ## Frameworks we build to - We signed the [CISA Secure by Design Pledge](https://www.cisa.gov/securebydesign/pledge): security is built in, not added afterwards. - Our AI development is guided by ISO/IEC 42001 and the NIST AI Risk Management Framework. We are not certified against ISO/IEC 42001. See our [AI Policy](https://usebead.ai/legal/ai-policy). ## Common questions **Is Bead AI SOC 2 Type II certified?** Yes, and independently audited. The report, the subprocessor list and the security FAQs are available through our Trust Center at trust.usebead.ai. **Is our audit evidence used to train AI models?** No, and it never reaches the companies that build the models. Inference runs inside Bead’s own cloud account on Amazon Bedrock and Google Cloud Vertex AI, neither of which passes inputs or outputs to the model provider behind the model, or keeps them after the request. Your evidence trains no model, ours or anyone else’s. On-premises, nothing leaves your network. **Which services process our data?** Amazon Bedrock, in the same AWS account and US region as the workload, and Google Gemini through Google Cloud Vertex AI. Both are our subprocessors, both run under zero-data-retention terms, and neither forwards your evidence to the model provider behind the model or trains on it. The current list is in our Privacy Policy. **Where is our data stored?** In data centres in the United States by default. A dedicated single-tenant deployment can run in another AWS region instead, wherever the services it depends on — including the inference services — are available there. Ask us about a specific region before you commit to it. **How quickly are vulnerabilities fixed, and how fast would we hear about a breach?** Critical vulnerabilities within 7 days, high within 30 and medium within 90. You would be notified of a security incident within 48 hours of us becoming aware of it. Both commitments are contractual, in our Security Addendum. **Can we have a dedicated environment rather than a shared one?** Yes. Large customers run in a dedicated single-tenant AWS account with its own network and infrastructure isolation, across three availability zones. Shared deployments separate tenants at the database level with row-level security. **Can our security team audit Bead AI?** Yes. On request we provide the SOC 2 Type II report, penetration test summaries and data flow diagrams at no cost, and once a year we answer up to 100 security questionnaire questions at our own cost. ## Talk to us about your review We answer security questionnaires at our own cost, and can walk your team through the SOC 2 report, our[deployment options](https://usebead.ai/platform/deployment) and the[Security Addendum](https://usebead.ai/legal/security-addendum) on a call. [Book a security review →](https://usebead.ai/contact) [Or visit the Trust Center](https://trust.usebead.ai/) ## Reporting If you’ve identified a potential security flaw in our infrastructure or software, please let us know at[security@usebead.ai](mailto:security@usebead.ai). We’ll triage the issue and get back to you. --- --- title: "About Bead AI: Our Manifesto for AI-Era Audit" description: "Why Alexey Zanin and Tobi Otte started Bead AI, what we believe about AI in assurance, and the CAEs advising and backing the company." url: "https://usebead.ai/why" --- # Automated Assurance Human Brilliance ## Why we decided to build Bead AI Long nights stitching evidence packets, version-controlled chaos, and seven-figure invoices. Audit has a reputation for being all about compliance and manual work. It’s simultaneously mission-critical, resource-starved, and error-prone. Today’s model treats audits as static check-boxes and auditors as compliance historians instead of risk navigators, burning them out and starving the industry of desperately needed talent. But something is coming to change this. The great AI wave is gathering speed, taking more and more shares of daily workloads, quietly shouldering the grind and data wrangling, leaving people free to focus on curiosity, judgment, and the stories only humans can tell. That’s what convinced us that right now is the time to start Bead. To give audit its overdue moonshot. Bead is an engine to power audit in a world where humans intervene only when judgment is needed, not getting lost digging for data scattered across email threads and workbooks. A world without tool silos and swivel chairs. Where intelligent agents create on-demand evidence graphs, where always-on connectors watch full-population data feeds, providing continuous assurance and surfacing failures as they happen. This world needs Bead AI. ## Our Pledge We are here to enhance auditors with superpowers. Making audits better and faster, not just cheaper. Augmentation over replacement. People’s skepticism, ethics, and contextual insight remain irreplaceable. Transparency first. Every step and conclusion is traceable back to the source or action logs. Community-driven. We will follow IIA standards and collaborate with regulators, governing bodies, and audit leaders to shape open protocols for AI-enabled assurance. ## Call to Action CAEs, if you believe assurance should be living, evidence should be self-assembling, and auditors should be strategic advisors, join us. Reject the status quo. Help us build a future where assurance keeps pace with innovation. Together, we can turn internal audit from a cost center into a control intelligence hub. Continuous, collaborative, and boldly data-driven. Because the companies you protect, and the investors who trust them, deserve nothing less. ## About the team ![Alexey Zanin](https://usebead.ai/images/team-alexey-zanin.png) ### Alexey Zanin Product Lead for Compliance Meta, driving compliance with GDPR, CPRA, DMA and others. Multiple ex-founder. ![Tobi Otte](https://usebead.ai/images/team-tobi-otte.png) ### Tobi Otte 15 years building and scaling tech startups. Has built successful agentic AI systems at scale. Multiple ex-CTO. ![Experienced CAEs](https://usebead.ai/images/team-advisors.png) ### Experienced CAEs Some of the most experienced CAEs are our exclusive advisors and investors. Book a call to learn more.