Clearly AI is a continuous threat modeling platform that automates the security review work that outpaces what your team can cover manually, so you can stop firefighting and actually get ahead of what ships.
Trusted by the companies you trust the most
Agentic context
Traditional threat modeling tools start with a blank whiteboard. First comes the kickoff meeting, then the architecture diagram, then the threat category setup, and days pass before a single finding appears. Clearly AI works the other way. Point it at a Jira ticket, a design doc, a GitHub repo, or a vendor questionnaire, and it gathers the context and builds a picture of the system on its own. It then delivers an accurate, structured assessment with findings pre-populated, sources cited, and gaps flagged. This isn't a faster version of the manual process. It doesn't replace your security engineers; it gives them a massive head start. Every conversation with your team and your developers starts from a sourced draft, not a blank page.
Threat models, privacy impact assessments, vendor risk reviews, and AI governance evaluations all run on the same agents, the same policies, and the same audit trail.
Determine whether an employee question, new code change, or new feature ticket needs security’s eyes. Give employees answers quickly and auto-resolve low-risk changes.
Ingest the information provided by the business and feed it into the right structured intake for your team. The enterprise context graph links the design docs, repos, tickets, and policies behind every system under review, so no one rebuilds the architecture from scratch.
Structured assessments, drafted by agents. Findings arrive pre-populated, with sources cited and gaps flagged. Engineers can review through configurable workflows, or bring Clearly AI into the IDE and AI coding tools over MCP.
Track every finding to a verified close. High-criticality findings open Jira tickets or post to Slack automatically. Clearly AI verifies that controls and remediations actually landed, then reports coverage to leadership and auditors.
Audit-ready accuracy
Every finding carries its source: the document, ticket, or code that supports it. Your reviewers can challenge it, push back, and sign it. Review templates are versioned, so results stay consistent and auditable against a specific project state. That's what makes the output defensible in an audit or a regulator conversation.
Centralize security and privacy
Security teams do more than just threat modeling. They review vendors, assess data flows, evaluate AI systems, and map controls against compliance frameworks. Most tools cover one of those things well and leave the rest to a separate process, a separate configuration, and a separate license.
Clearly AI covers the full scope: threat models, privacy impact assessments, vendor risk assessments, AI risk reviews, and compliance control evaluations, all in one platform running against your policies and frameworks.
When you use Clearly AI for threat modeling, your privacy team and GRC function benefit, too. One investment extends across functions that were previously siloed.
Automate threat modeling and design reviews. Ship secure features faster.
“With Clearly AI, we provided the documentation for the product and within a minute, here's all that documentation generated that would've taken developers weeks to create. We're seeing immediate impact with the threat modeling...weeks reduced down to minutes, literally.”
Security expertise
Clearly AI was founded by security engineers who ran hundreds of critical reviews at Amazon, and it has a security expert's domain depth, not generic AI retrained for security. It applies the judgment a senior engineer would: what's a real finding versus noise, what context is missing, and what the next step should be. The same rigor applies whether the methodology is STRIDE, ATT&CK, MAESTRO, OWASP, or your own.
Workflow-native
Reviews trigger automatically from Jira, GitHub, ServiceNow, Azure DevOps, and Linear, or run on a schedule, with no manual start required. Developers and their AI coding agents can reach Clearly AI in the IDE and over MCP. High-criticality findings create Jira tickets or post to Slack automatically, so findings route back to the tools where security and the business already work.
Proven outcomes
Customers see a ~90% reduction in time per review and 4x review capacity with the same team. That holds across threat modeling, privacy, and vendor risk workflows, not just one assessment type. When coverage expands that way, it's because the output is reliable enough to stake a decision on.
Fast to deploy
Upload or integrate your policies and control libraries, and they become live review templates in hours, not a six-month configuration project. HID Global onboarded 300+ products in under 3 months. Building a threat modeling tool in-house with AI means writing and maintaining the system indefinitely, with every new framework, regulation, or threat pattern costing another sprint. Clearly AI delivers expert-grade accuracy from day one and keeps pace with the threat landscape through exposure across all customers, so your engineers don't have to.
Enterprise-ready
Founded by security engineers who ran hundreds of critical reviews at Amazon, Clearly AI is SOC 2 Type II audited and never trains models on customer data. Choose multi-tenant SaaS, a dedicated single-tenant environment, or deployment in your own cloud.
90%
Reduction in review turnaround time
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
FAQ
Clearly AI is a continuous threat modeling platform for security, privacy, and GRC teams. Its agents gather context from design docs, code, tickets, and connected tools, then run structured reviews: threat models, privacy impact assessments, vendor risk reviews, and AI governance evaluations, with findings cited to source and gaps flagged. Teams use it both to triage many systems against baseline controls and to go deep on complex ones.
Product security, privacy, and GRC teams at mid-size and large enterprises, including Rivian, HID Global, and Ericsson. Security engineers, compliance analysts, and risk owners work on the same platform under the same license.
Continuous threat modeling means every change that ships gets a threat model, not just the fraction a team can review by hand. Reviews trigger automatically from Jira, GitHub, and other tools when work is created. Clearly AI gathers context from existing tickets, design docs, repos, and configs, then produces a structured threat model with findings, cited sources, and flagged gaps for engineers to review and sign.
No. Monitoring tools watch running systems for issues after deployment. Continuous threat modeling assesses design and code changes as they're created, so risks are found before they ship. Clearly AI runs a structured review each time something new needs evaluation, triggered from the tools where work already starts.
Traditional tools require manual architecture diagramming and configuration before they produce anything. Clearly AI starts from the artifacts you already have. It also goes beyond threat models: privacy, vendor risk, AI risk, and compliance reviews all run on the same platform and audit trail.
Clearly AI runs threat models against established methodologies such as STRIDE, OWASP, ATT&CK, and MAESTRO, along with custom frameworks built from your own policies and control libraries. The same engine runs privacy and compliance assessments against frameworks such as the EU Cyber Resilience Act and NY DFS Part 500.
You can, but you'd be writing and maintaining it indefinitely, and every new framework, regulation, or new threat vector would require another engineering sprint. Clearly AI delivers practitioner-grade accuracy from day one and improves from broad exposure to the threat landscape.
Every finding cites the document, ticket, or code that supports it, and answers are grounded in your own policies and standards. Reviewers can edit answers, add feedback, and regenerate individual answers. Every review runs against a specific version of the project and the template, so results stay consistent and auditable, and template changes can be tested against real projects before they go live.
Yes. Clearly AI connects to issue trackers (Jira, ServiceNow, Linear, Azure DevOps, Aha!), code repositories (GitHub, GitLab, Azure Repos, Bitbucket), document sources (Confluence, Google Drive, SharePoint, Notion), and governance and security tools such as OneTrust, Archer, Snyk, and Wiz. Reviews trigger automatically from Jira, GitHub, ServiceNow, Linear, and Azure DevOps, and results route back as tickets, comments, and Slack messages. MCP-compatible AI assistants and IDEs connect through Clearly AI's MCP server.
No. Clearly AI is an on-demand assessment platform. Each review is a point-in-time assessment of a specific project version, run when something new ships or changes. Reviews can be triggered from your existing workflow or run on a schedule; Clearly AI doesn't passively watch systems or dashboards.
A typical rollout connects your identity provider and source systems, loads your policies and standards, configures review templates to match your process, and tests a representative review against real sources. Most Clearly AI customers are up and running within days, and typically a pilot period shortcuts that further if you choose to do so. How long it takes depends on what you choose to review. HID Global, as an example, onboarded 300+ products in under 3 months.
Clearly AI doesn't use customer data to train or fine-tune models; reviews work from your sources through retrieval, not training. The platform is hosted on AWS, with multi-tenant, single-tenant, and private cloud deployment options, encryption in transit and at rest, and SAML SSO and SCIM. Enterprises can bring their own model provider keys, including Amazon Bedrock, and choose alternative data residency. The SOC 2 Type II report is available under NDA.
The continuous threat modeling platform for product security, privacy, and GRC teams.
