--- title: "Product security assurance" description: "Clearly AI assesses each product against your policies, guardrails, and risk thresholds, and gathers the evidence itself from the design docs, code, infrastructure as code, and tickets your teams already have." canonical: https://clearly-ai.com/solutions/product-security-assurance --- _Product security assurance_ # Prove every product that ships meets your security bar Clearly AI assesses each product against your policies, guardrails, and risk thresholds, and gathers the evidence itself from the design docs, code, infrastructure as code, and tickets your teams already have. Product security gets an assessment it can sign. GRC gets evidence an auditor can trace. - [Contact Enterprise Sales](https://clearly-ai.com/demo) - [See how control verification works](https://clearly-ai.com/platform/control-and-remediation-verification) Trusted by the companies you trust the most - HID Global - Ericsson - PayPal - Modern Health - Hagerty - Rivian - Infineon - Bastion _The assurance gap_ ## How do you know every product meets your policy? The evidence exists. Collecting it is the job. Most of what proves a product meets your guardrails is already written down somewhere: a design doc, a Terraform file, a ticket, a repo. The hard part is pulling it together. Today that means chasing engineers for screenshots, booking meetings with product and IT owners, and walking through each control one at a time. Every assessment turns into days or weeks of back-and-forth, so most teams formally assess only 10–15% of what ships. The rest goes out without a documented assessment, or with a self-attestation no one checked. By the time an auditor asks, the screenshots are months out of date. Product security and GRC often chase the same evidence for different reports, months apart. ![Two timelines across a quarter: dozens of products shipping, and only three assessed against policy, leaving the rest with no documented assessment.](https://clearly-ai.com/solutions/product-security-assurance-gap.svg) ## Whatever your team calls it Enterprise policy assessments. Technical controls assessments. IT guardrails assessments. Baseline security controls. Security assurance. Different names, same job: checking that a product has the controls your company requires before it ships. Clearly AI runs all of them against your own policy, under whatever name your program uses. _How it works_ ## From policy to proof, for every product 1. **Load your guardrails** Upload your security policies, guardrail standards, or control spreadsheets, one per domain if that's how your program runs. Each becomes a review template in hours, not a six-month configuration project. 2. **Gather the evidence** Point Clearly AI at a product, or let a Jira ticket or GitHub change trigger the review. Agents read the design docs, code, infrastructure as code, and tickets behind it, pull findings from connected tools like Wiz and Snyk, and match evidence to each control. 3. **Assess every domain at once** A workflow branches one product review into every guardrail assessment that applies and runs them in parallel. Each control is marked compliant, partially compliant, noncompliant, missing info, or not applicable, with the source that supports it. Your team reviews, adjusts, and signs. 4. **Close the gaps** Publish noncompliant and partially compliant controls to the risk registry with an owner and due date, and open a ticket in Jira, Linear, or ServiceNow. When the fix is in, re-run the assessment to confirm the control is in place. ![A Clearly AI policy assessment showing each control's result and the evidence that supports it.](https://clearly-ai.com/solutions/product-security-assurance-how-it-works-v2.svg) _Guardrail domains_ ## One product review. Every guardrail domain. Teams run guardrail assessments across domains like application, cloud, network, storage, data, endpoint, mobile, browser, collaboration tools, identity and access management, asset inventory, and AI and AI agent security. Build the workflow once, and every product that comes through gets assessed against every guardrail that applies, without a separate kickoff for each. ![A Clearly AI workflow branching one generated review into twelve guardrail assessments, from AI agent security to storage security.](https://clearly-ai.com/solutions/product-security-assurance-domains-v2.svg) [How workflows work](https://clearly-ai.com/platform/workflows) _Agentic evidence gathering_ ## Evidence gathered from where it already lives The evidence your assessments need already lives in design docs, repos, Jira epics, and infrastructure as code. Clearly AI's agents go get it, then match what they find to each control in your guardrails. Every verdict points to the file and line, tool finding, policy section, screenshot, or link that supports it. Product and IT owners only hear from security when evidence genuinely isn't there, and Clearly AI asks for just that piece, no meeting required. Example: The agent’s steps on Acme Payments hypothetical API, from the first ticket to matched control evidence Clearly AI's agent steps on Acme Payments hypothetical API: it pulled ticket SEC-1519, read the Acme Payments v2 design doc, analyzed the payments-api repo, read payments-api/main.tf, imported Wiz posture findings, and matched evidence to 42 of 46 controls with 4 missing info. [How the enterprise context graph works](https://clearly-ai.com/platform/enterprise-context-graph) _Your policy, your bar_ ## Assessed against the bar your company sets Every company draws the line in a different place, and often in a different place for a customer-facing app than for an internal tool. Clearly AI evaluates against the guardrails you already have, not a generic checklist. ### Your control library, live in hours Upload a policy, baseline standard, or control spreadsheet and it becomes a versioned review template. ### Your definition of compliant Set what passes for each control, then decide in the risk registry whether a gap is accepted, mitigated, transferred, or stops the launch. ### Your controls, mapped to the standards Map internal controls to frameworks and regulations like the [EU Cyber Resilience Act](https://clearly-ai.com/solutions/compliance/cyber-resilience-act) and NY DFS Part 500, so one assessment answers both. ### Different products, different baselines Apply a stricter template to products that handle customer data and a lighter one to internal tools. [How tuning and customization work](https://clearly-ai.com/platform/quality) _Audit-ready accuracy_ ## Every verdict shows its work A “compliant” with no evidence behind it is just another self-attestation. Every Clearly AI verdict cites the document, ticket, line of code, or config that supports it. Reviewers can challenge it, change it, and sign it. Every answer keeps its history: what Clearly AI generated, what new context it used, and who changed the status and why. When an auditor asks how you know a product meets AUTH-STD-04, the answer is already on the record, with its evidence and sign-off. ![A Clearly AI threat model finding opened from the findings list, with its cited source, reasoning, review history and the Publish to Risk Registry action.](https://clearly-ai.com/solutions/product-security-assurance-findings-still.webp) [How Clearly AI ensures quality](https://clearly-ai.com/platform/quality) _Product security meets GRC_ ## One assessment for product security and GRC Product security asks, “Is this product built safely?” GRC asks, “Can we prove it meets our controls?” They're usually answered by different teams, in different tools, months apart. Clearly AI answers both in the same review. ### For security engineers Findings, gaps, and remediation tickets, in the tools they already use. ### For GRC Control-level evidence mapped to your frameworks, sent to the risk and GRC tools you already run, like Archer and ServiceNow. ### For everyone One record, so the security sign-off and the audit evidence never drift apart. ### Why not just collect attestations in your GRC tool? GRC platforms track whether a control was attested; they don't read the design doc. Security scanners find vulnerabilities in code; they don't check it against your policy. Clearly AI does both jobs from the same evidence, and the same license covers your privacy, vendor risk, and AI governance reviews too. ![Product security, Privacy and GRC feeding one Clearly AI Risk Registry, which syncs both ways with Jira, Linear and ServiceNow and sends risks to Archer and Wiz.](https://clearly-ai.com/solutions/product-security-assurance-grc.svg) [How Clearly AI supports compliance programs](https://clearly-ai.com/solutions/compliance) _Security expertise_ ## Triage the whole portfolio. Go deep where it counts. Not every product needs a full threat model. Every product does need to meet your baseline. Clearly AI checks the full portfolio against baseline controls, then shows which products carry enough risk to warrant a deeper review. It applies the judgment of a senior security engineer: what's a real gap versus noise, when an existing control already covers a requirement, and what context is missing. High-risk products move straight into a threat model or security architecture review on the same platform, using the evidence already gathered. [How continuous threat modeling works](https://clearly-ai.com/solutions/continuous-threat-modeling) _Workflow-native_ ## Built into how products ship Policy assessments trigger automatically from Jira, GitHub, ServiceNow, Azure DevOps, and Linear, or run on a schedule, so a product doesn't skip assessment because no one remembered to start one. Noncompliant controls open tickets in Jira, Linear, or ServiceNow, or post to Slack, with the policy reference attached. When the fix is in, re-run the assessment and the record updates, so coverage reporting reflects what's actually built. ![Clearly AI targeted reviews: your standards set the bar, design docs, code, architecture diagrams and Jira tickets trigger reviews for AWS, Google Cloud, Azure, on-prem, privacy, AI and web apps, and the output is a readiness summary, control gaps, and findings with suggested remediation.](https://clearly-ai.com/solutions/product-security-assurance-workflow.svg) [See control and remediation verification](https://clearly-ai.com/platform/control-and-remediation-verification) ## Assurance from design to release ### [Secure by Design](https://clearly-ai.com/platform/ide-and-mcp) Policy-aligned security requirements before the first line of code, delivered to developers and their coding agents. ### [Security architecture reviews](https://clearly-ai.com/solutions/design-and-architecture-reviews) Deep, structured reviews of high-risk designs, built from the docs and diagrams your teams already have. ### [Policy assessments](#how-it-works) Check every product against your internal policies and baseline controls, with evidence cited for each verdict. ### [Drift detection](https://clearly-ai.com/solutions/continuous-threat-modeling) Catch when what was built no longer matches what was designed, approved, or required. ### [Control verification and reporting](https://clearly-ai.com/platform/control-and-remediation-verification) Confirm controls and fixes actually landed, then report coverage to leadership and auditors. _Proven outcomes_ ## From 10% coverage to 100%, against your own controls - **~90%** Reduction in time per review - **4x** Review capacity with the same headcount - **From 10 to 100%** Product coverage > “As soon as we started using Clearly AI, we saw an immediate reduction in the amount of time that not only my team was spending on the reviews, but that the business owners were actually spending having to give us the answers for the assessments.” > > — Ashley Haynes, Senior Director of Privacy, Trust and AI Governance [See Ericsson’s story](https://clearly-ai.com/customer-stories/ericsson) > “4x increase in team capacity. Clearly AI is by far the leader in this space.” > > — Jim Gregoire, Head of Privacy and AI Governance [See Rivian's story](https://clearly-ai.com/customer-stories/rivian) > “Weeks to minutes, literally.” > > — William Brown, Sr. Director of Product Security and Privacy [Read the HID Global story](https://clearly-ai.com/customer-stories/hid-global) _Enterprise-ready_ ## Built by security engineers. Held to the same bar. Founded by and made up of the best security nerds in the business, tackling security at scale at companies like Amazon, Google, Airbnb, Twilio, Lyft, NetSPI, Microsoft, Meta, Apple, Palo Alto Networks, GitLab, and more. Clearly AI is SOC 2 Type II certified and never trains models on customer data. Deploy it as multi-tenant SaaS, a dedicated single-tenant environment, or inside your own cloud, with SAML SSO, SCIM, customer-managed keys, and your own model provider keys, including Amazon Bedrock. - SOC 2 Type II compliant - RSAC Innovation Sandbox Finalist 2026 - Y Combinator - Amazon Bedrock Builders' Challenge winner 2025 [Visit the Trust Center](https://clearly-ai.com/trust/security-privacy) _FAQ_ ## Answers to your top questions ### What is product security assurance? Product security assurance is the practice of confirming that each product meets your company's required security controls, across domains like identity and access, cloud, network, data, and application security. Teams also call it policy assessment, technical controls assessment, IT guardrails assessment, or baseline security controls review. Clearly AI, the continuous threat modeling platform, automates it by gathering evidence and checking each product against your own controls, with a cited source for every result. ### How is a policy assessment different from a threat model? A policy assessment asks whether a product has the controls your company requires. A threat model asks what could go wrong given how the product is designed. Clearly AI runs both from the same gathered context, so teams often assess every product against baseline controls and run full threat models on the highest-risk ones. ### Can Clearly AI assess products against our internal security policies? Yes. Upload your policy, baseline standard, or control spreadsheet, and Clearly AI converts it into a review template in hours. You decide what counts as compliant, and you can apply different templates to different product types. [Learn about tuning and customization](https://clearly-ai.com/platform/quality) ### What kinds of controls can Clearly AI check? Any control you can define and find evidence for in your documentation, code, tickets, or configs. Customers run guardrail assessments across application, cloud, network, storage, data, endpoint, mobile, browser, collaboration tools, identity and access management, asset inventory, and AI and AI agent security. When evidence is missing, Clearly AI marks the control missing info instead of guessing. ### Where does the evidence come from? From the artifacts your teams already maintain: design docs in Confluence, Google Drive, SharePoint, or Notion; code and infrastructure as code in GitHub, GitLab, Azure Repos, or Bitbucket; tickets in Jira, ServiceNow, Linear, Azure DevOps, or Aha!; findings from connected security tools like Wiz and Snyk; and screenshots or links your team provides. Every verdict cites the specific source behind it. [See all integrations](https://clearly-ai.com/integrations) ### Do we still need evidence meetings? Far fewer. Clearly AI pulls evidence directly from the documents, code, tickets, and tools where it already lives, and cites each source. Screenshots still count when a setting only lives in a console, and Clearly AI reads them for what the control requires. Product and IT owners are asked only about what's genuinely missing, through a short conversation instead of a meeting or a long form. [Learn about conversational intake](https://clearly-ai.com/platform/conversational-intake) ### Does Clearly AI replace our GRC platform? No. Clearly AI produces the control-level evidence your GRC program needs and sends it to tools like Archer and ServiceNow. Your GRC platform stays the system of record for the control framework; Clearly AI is how each product gets assessed against it. ### Is this continuous control monitoring? No. Clearly AI doesn't watch running systems or cloud dashboards. Each assessment is a point-in-time review of a specific product version, triggered when something new ships or changes, or on a schedule. It assesses design, code, and configuration before release, which complements runtime monitoring tools rather than replacing them. ### How do we show auditors that a product meets a control? Share the assessment record. Each verdict links to its supporting source, and every answer keeps a history of what Clearly AI generated, what context it used, and who changed the status and why. Every assessment is tied to the template version it ran against. ### Can we map our controls to frameworks like the EU Cyber Resilience Act? Yes. You can map internal controls to industry standards and regulations, including the EU Cyber Resilience Act and NY DFS Part 500. HID Global onboarded 300+ products in under 3 months as it prepared for the Cyber Resilience Act. [Read the HID Global story](https://clearly-ai.com/customer-stories/hid-global) ### Can we build this ourselves with an LLM? You can, but you'd be writing and maintaining it indefinitely, and every new policy revision, framework, or regulation would need another engineering sprint. Clearly AI delivers practitioner-grade accuracy from day one, with versioned templates, cited evidence, and workflow integrations already built. Build vs. buy: the real cost ## Bring your security policy to the demo We'll show how a policy like yours becomes a review template, then walk through an assessment on a sample product, with every result cited to source. - [Contact Enterprise Sales](https://clearly-ai.com/demo) - [See how Clearly AI ensures quality](https://clearly-ai.com/platform/quality) ## Learn more - [Secure everything that ships](https://clearly-ai.com) - [We built the tool we wished we had](https://clearly-ai.com/about-us) - [One platform. From intake to remediation.](https://clearly-ai.com/platform) - [Know everything that needs a review. Skip the 300-question form.](https://clearly-ai.com/platform/security-intake) - [Ask only what matters. Get it right the first time.](https://clearly-ai.com/platform/conversational-intake) - [Every finding, tracked to a decision](https://clearly-ai.com/platform/resolve/risk-registry) - [Show leadership and auditors exactly what security reviewed](https://clearly-ai.com/platform/resolve/reporting) - [Security reviews you can stand behind, every time](https://clearly-ai.com/platform/quality) - [Threat models built from the tools you already use](https://clearly-ai.com/integrations) - [Threat models that know about today's attacks](https://clearly-ai.com/platform/threat-intelligence) - [Automate every step around the review](https://clearly-ai.com/platform/workflows) - [Threat models your teams can work on together](https://clearly-ai.com/platform/collaboration) - [Understand the system before the review starts](https://clearly-ai.com/platform/enterprise-context-graph) - [Trust, security, and deployment](https://clearly-ai.com/platform/trust-security-and-deployment) - [Every plan reviewed. 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Okay, privacy is different from security. 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