--- title: "Clearly AI vs Clover Security: a Clover alternative" description: "Compare Clearly AI and Clover Security. Clearly AI cites every finding to its source, flags missing context, and runs privacy and vendor reviews too." canonical: https://clearly-ai.com/compare/clover --- _Switch from Clover Security_ # The Clover Security alternative with findings your team can trust Clover Security uses AI agents to discover what's changing and automate security design reviews and threat modeling. Clearly AI does that core work too: diagrams, threat models, and design reviews built from the docs, tickets, and code your teams already write, triggered from the tools they already use. The difference is what you can do with the output. Clearly AI cites every finding to its source, flags missing context instead of guessing, and runs your privacy, vendor risk, and AI reviews on the same platform. - [Contact Enterprise Sales](https://clearly-ai.com/demo) - [Explore the platform](https://clearly-ai.com/platform) **Clearly AI vs Clover Security** Example agent activity for Acme Payments API: pulled ticket SEC-1482, read the design doc, analyzed repo acme/payments-api, checked 42 controls, drafted a threat model with 14 findings and 3 gaps flagged. Trusted by the companies you trust the most - HID - Ericsson - PayPal - Modern Health - Hagerty - Rivian - Infineon - Bastion _Why teams switch_ ## 3 reasons product security teams choose Clearly AI Some AI review tools are built to find everything: every change, every connected document, every possible finding. More context isn't always better context. When a tool pulls in documentation unrelated to the change, it writes findings about the wrong system, and reviewers spend their week sorting real risks from plausible ones. And once the design review is done, privacy, vendor, and AI reviews still run somewhere else. ### Findings with cited sources you can trust Clearly AI builds each review from the sources linked to the work and the systems your team has mapped, then cites the document, ticket, or code behind every finding. When the evidence isn't there, it flags the gap as an open question instead of guessing. Your team spends its time on the highs and criticals. [How tuning and accuracy work](https://clearly-ai.com/platform/quality) ### Your standards, versioned and testable Review templates are built by security engineers who have run hundreds of critical reviews, then tuned to your policies, control libraries, and risk catalog. Upload a policy or control spreadsheet and it becomes a live review template in hours, or build a custom review type of your own. Templates live as code, so every change is versioned and every review is tied to a specific project state. ### Every review, one platform Threat models, privacy impact assessments, vendor risk and AI risk reviews, compliance control evaluations, and custom reviews run on one platform, against your policies, with one audit trail. Your privacy and GRC teams use the same license. [Explore the platform](https://clearly-ai.com/platform) _Side by side comparison_ ## Clover Security vs Clearly AI Everything about Clover Security on this page comes from its public website, trust center, product announcements, and press coverage, current as of October 2026. That includes Kura, which Clover released in August 2026. If something here is out of date, tell us at marketing@clearly-ai.com and we'll fix it! | | Clearly AI | Clover Security | | --- | --- | --- | | Where a review starts | A Jira ticket, design doc, repo, vendor questionnaire, or chat request · Triggered automatically from your tools or run on demand | A discovery agent that gathers feature context and auto-triggers reviews · Autonomous or assisted design reviews | | Files it can read | PDF, with OCR · Word, PowerPoint, Excel, CSV, and TSV · Audio and video, transcribed · Images, for multimodal models · HTML · ZIP archives, unpacked and read file by file · Code, Markdown, JSON, YAML, XML, config files, and any other text file | Docs, tickets, and code | | Threat models and diagrams | Architecture and data flow diagrams with trust boundaries, generated from your evidence · Edited together in Draw.io, with the threat model updating to match | Data flow and sequence diagrams inferred from docs, tickets, and code · Attack trees and attack scenarios | | Threat knowledge | Frameworks like STRIDE, OWASP, MITRE ATT&CK, PASTA, LINDDUN, and MAESTRO · Review templates built by Clearly AI security engineers · Your policies, control libraries, and risk catalog | Frameworks like STRIDE and LINDDUN · Organization standards turned into requirements by a security policy agent | | How findings are produced | Specialized agents reason over your system's own evidence · Evaluated against your policies and controls · Every finding cited to its source, with missing context flagged as a gap | Agents infer architecture from your artifacts · A continuously updated threat model · Threat model shared as live context for coding agents | | Review types | Security design reviews and threat models · AI code review on PRs, including secrets scanning · Privacy impact assessments · Vendor risk and AI risk reviews · Compliance control evaluations · Custom reviews | Security design reviews and threat modeling · Secure agentic, spec-driven, and vibe-coded development | | Tailoring to your standards | Upload a policy or control spreadsheet · Live review template in hours · Custom review types built from your own templates · Templates as code, every change versioned | Security policy agent applies your standards · Checklists and questionnaires | | After the review | Each review versioned against a specific project state · Risk registry with accept, mitigate, transfer, or stop decisions · Two-way ticket sync with Jira, Linear, and ServiceNow · Remediation and control verification in code | Living risk registry · Export to PDF and TM-BOM | | Workflow integration | Auto-triggers from Jira, GitHub, ServiceNow, Azure DevOps, Linear, and Aha! · Context from Confluence, Google Drive, SharePoint, Notion, GitLab, Azure Repos, Bitbucket, Archer IRM, OneTrust, Snyk, and Wiz · Results route to Jira, GitHub, Linear, Azure DevOps, ServiceNow, Slack, OneTrust, Notion, Google Drive, and SharePoint · Intake from Slack, Microsoft Teams, and Microsoft Power Apps · CLI and REST API | Jira, Confluence, Notion, Google Drive, SharePoint, GitHub, GitLab, Bitbucket, and Azure · Slack | | AI coding agents | MCP server for coding agents, such as Claude Code, Codex, Cursor, Devin, Copilot, and Kiro · Security design guidance at plan time | Kura security context for coding agents · MCP agent · Visibility into coding agent activity | | Deployment and model control | Multi-tenant SaaS, single-tenant, or your own cloud · SAML SSO, OIDC, SCIM, customer-managed keys · Bring your own model from OpenAI, Anthropic, or Amazon Bedrock | SaaS on AWS · SSO, MFA, and role-based access control · SOC 2 Type 2 | ![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/home/figma/findings-animation-still-v4.webp) _Every finding shows the document, ticket, or code behind it._ _Enterprise-ready_ ## Your data stays yours. Your model stays your choice. Deploy Clearly AI as multi-tenant SaaS, a dedicated single-tenant environment, or inside your own cloud, with SAML SSO, OIDC, SCIM, and customer-managed keys. Bring your own model from OpenAI, Anthropic, or Amazon Bedrock. Clearly AI is SOC 2 Type II certified and never trains models on customer data. Every review is versioned against a specific project state, so you can show an auditor exactly what was reviewed, when, and why. [See how Clearly AI handles security and deployment](https://clearly-ai.com/platform/trust-security-and-deployment) - SOC 2 Type II compliant - GDPR - RSAC Innovation Sandbox Finalist 2026 - Amazon Bedrock Builders' Challenge winner 2025 _Proven outcomes_ ## More of what ships, reviewed. With your existing team. - **~90%** Reduction in time per review - **4x** Review capacity with the same headcount - **From 10 to 100%** Product coverage > “4x increase in team capacity. Clearly AI is by far the leader in this space.” > > — Jim Gregoire, Head of Privacy and AI Governance [Read the Rivian story](https://clearly-ai.com/customer-stories/rivian) _FAQ_ ## Answers to your top questions ### What is Clearly AI? Clearly AI is a continuous threat modeling platform for security, privacy, and GRC teams. It gathers context from the artifacts your team already works from and delivers structured threat models, privacy impact assessments, vendor risk reviews, and AI governance evaluations, with every finding cited to its source. It was founded by security engineers who ran hundreds of critical reviews at Amazon. [Explore the platform](https://clearly-ai.com/platform) ### How is Clearly AI different from Clover Security? Both use AI agents to automate security design reviews and threat models from your docs, tickets, and code. Clover centers its platform on product security agents and securing the agentic software development lifecycle. Clearly AI cites every finding to the document, ticket, or code behind it, flags missing context as an open question, and runs privacy, vendor risk, AI risk, compliance, and custom reviews on the same platform. [How tuning and accuracy work](https://clearly-ai.com/platform/quality) ### Isn't broader discovery better? Not if the extra findings aren't real. Broad discovery can pull in documents that aren't related to the change under review, and unrelated context produces findings about the wrong system. Clearly AI builds each review from the sources linked to the work and the systems you've mapped in the enterprise context graph. When it isn't sure a repo or document belongs to a feature, it suggests the link instead of assuming it, and you can auto-accept links above a confidence level you set. [See the enterprise context graph](https://clearly-ai.com/platform/enterprise-context-graph) ### Clover and Clearly AI both offer continuous threat modeling. Is it the same thing? Not quite. Clover describes a living threat model that re-evaluates as your system changes. With Clearly AI, every change that ships gets its own review, triggered from tools like Jira and GitHub, and each review is versioned against that project state. You get a record of what was reviewed, when, and against which policy version. [See continuous threat modeling](https://clearly-ai.com/solutions/continuous-threat-modeling) ### How does Clearly AI keep false positives down? Every finding has to point to evidence. Clearly AI's agents reason over your system's own documents, tickets, and code, evaluate them against your policies, and cite the source for each finding. When an existing control already mitigates a threat, Clearly AI marks it as not a finding and explains why. When the evidence isn't there, the review flags the gap as an open question. Your team can tune severity, wording, and depth in the review template. [How tuning and accuracy work](https://clearly-ai.com/platform/quality) ### Does Clearly AI find what needs a review on its own? Yes. Reviews trigger automatically from Jira, GitHub, ServiceNow, Azure DevOps, Linear, and Aha!, and an intake step triages each request so high-risk changes get a full threat model and low-risk ones get a lighter check. You decide which changes count, so reviewers see the work that needs them. [See how intake works](https://clearly-ai.com/platform/security-intake) ### Does Clearly AI work with AI coding agents? Yes. The Clearly AI MCP server connects to coding agents such as Claude Code, Codex, Cursor, Devin, Copilot, and Kiro, so developers and their agents get security design guidance while they plan and build, against the same templates your security team uses. [See IDE and MCP](https://clearly-ai.com/platform/ide-and-mcp) ### Can Clearly AI run privacy, vendor risk, and AI reviews too? Yes. Privacy impact assessments, vendor risk assessments, AI risk reviews, compliance control evaluations, and custom reviews run on the same platform as your threat models, with the same citations and audit trail. Clover's public product focuses on product security and secure development. [See vendor risk reviews](https://clearly-ai.com/solutions/third-party-risk) ### What happens to our existing Clover threat models? They carry forward. Export them from Clover and upload them, and Clearly AI uses them as review context alongside your design docs, tickets, and code. Clearly AI reads PDF exports and text formats like JSON, so there's nothing to redraw before your first review with Clearly AI. ### Can we run Clearly AI side by side with Clover? You could! Most teams start with a sandbox using their own documents and templates, then an integrated evaluation connected to tools like Jira, ServiceNow, GitHub, or Azure DevOps. Run the same tickets and design docs through both, and compare the findings to your best security engineer's. ### Which methodologies and standards does Clearly AI support? Clearly AI runs threat models against frameworks like STRIDE, MITRE ATT&CK, PASTA, LINDDUN, and MAESTRO, plus custom frameworks built from your own policies and control libraries. Upload a policy or control spreadsheet, and it becomes a live review template in hours. [See the frameworks Clearly AI supports out of the box](https://clearly-ai.com/solutions/continuous-threat-modeling#frameworks) ### Is continuous threat modeling the same as continuous monitoring? No. Continuous threat modeling means every change that ships gets a threat model, triggered from tools like Jira and GitHub or run on a schedule. Each review is a point-in-time assessment of a specific project version. Clearly AI doesn't passively watch running systems or dashboards. ### Where does our data live, and can we use our own model? Clearly AI runs as multi-tenant SaaS, in a dedicated single-tenant environment, or inside your own cloud. Yes, you can bring your own model from OpenAI, Anthropic, or Amazon Bedrock, and Clearly AI never trains models on customer data. [See security and deployment](https://clearly-ai.com/platform/trust-security-and-deployment) ### Does Clearly AI replace our security engineers? No. Clearly AI handles context gathering, drafting, and routing, so your engineers spend their time on risk decisions. Reviewers can challenge any finding, push back, and approve the result. ### When is Clover a better fit? If your top priority is governing AI coding agents and finding vibe-coded apps across your organization, Clover has built much of its product there. If you need cited, auditable reviews across everything that ships, or your team also runs privacy, vendor, and AI reviews, Clearly AI is built for that. ## See the difference on a system like yours Bring a design review your team ran in Clover to the demo. We'll show you how Clearly AI reviews a comparable system, with every finding cited, and how to set up a side-by-side evaluation on your own. - [Contact Enterprise Sales](https://clearly-ai.com/demo) Getting started with Clearly AI ## 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. Every risky change threat modeled.](https://clearly-ai.com/platform/ide-and-mcp) - [Verify what actually shipped](https://clearly-ai.com/platform/control-and-remediation-verification) - [A current threat model for everything that ships](https://clearly-ai.com/solutions/continuous-threat-modeling) - [Prove every product that ships meets your security bar](https://clearly-ai.com/solutions/product-security-assurance) - [Privacy reviews your team can stake decisions on](https://clearly-ai.com/solutions/privacy) - [Every vendor reviewed against your standards](https://clearly-ai.com/solutions/third-party-risk) - [Review every design before it's built](https://clearly-ai.com/solutions/design-and-architecture-reviews) - [Secure the AI you build, buy, and code with](https://clearly-ai.com/solutions/ai-agentic-security) - [Every regulation you answer to. One review process.](https://clearly-ai.com/solutions/compliance) - [Every product ready for the Cyber Resilience Act without growing your team](https://clearly-ai.com/solutions/compliance/cyber-resilience-act) - [Build vs. buy for security review automation](https://clearly-ai.com/compare/claude-chatgpt) - [The ThreatModeler alternative built from your own docs, code, and policies](https://clearly-ai.com/compare/threatmodeler) - [The Clover Security alternative with findings your team can trust](https://clearly-ai.com/compare/clover) - [The Prime Security alternative for every review your team runs](https://clearly-ai.com/compare/prime) - [Security and Privacy](https://clearly-ai.com/trust/security-privacy) - [Clearly AI Privacy Policy](https://clearly-ai.com/trust/privacy-policy) - [Clearly AI Subprocessors](https://clearly-ai.com/trust/subprocessors) - [AI Risk Reviews](https://clearly-ai.com/use-cases/ai-risk-reviews) - [Automate Triage](https://clearly-ai.com/use-cases/automate-triage) - [Privacy Impact Assessments](https://clearly-ai.com/use-cases/privacy-impact) - [Vendor Risk Assessments](https://clearly-ai.com/use-cases/vendor-risk) - [Threat Modeling](https://clearly-ai.com/use-cases/threat-modeling) - [Contact](https://clearly-ai.com/contact) - [Contact Enterprise Sales](https://clearly-ai.com/demo) - [Latest from the Clearly AI blog](https://clearly-ai.com/blog) - [In the news](https://clearly-ai.com/press) - [How Ericsson Enterprise Wireless Solutions cut review times by up to 80%](https://clearly-ai.com/customer-stories/ericsson) - [How HID Global reviews 300+ products for the Radio Equipment Directive with the team it already has](https://clearly-ai.com/customer-stories/hid-global) - [How Rivian scaled privacy and AI governance reviews 4x without adding headcount](https://clearly-ai.com/customer-stories/rivian) - [Part 2! Okay, privacy is different from security. Now what?](https://clearly-ai.com/blog/part-2-okay-privacy-is-different-from-security-now-what) - [How AI is rewiring our product engineering workflow](https://clearly-ai.com/blog/how-ai-is-rewiring-our-product-engineering-workflow) - [Good Data Scientists and Bad Outcomes, Part 1: What's the difference between security and privacy work?](https://clearly-ai.com/blog/good-data-scientists-and-bad-outcomes-what-s-the-difference-between-security-and-privacy-work) - [Why I Joined Clearly AI](https://clearly-ai.com/blog/why-vp-marketing-joined-clearly-ai) - [Skip the Marketing: Clearly AI for Technical People](https://clearly-ai.com/blog/clearly-ai-technical-explanation) - [Clearly AI Raises $8.4M Seed Round to Scale Product Security](https://clearly-ai.com/blog/seed-round) - [Why We Started Clearly AI](https://clearly-ai.com/blog/why-we-started-clearly-ai) - [Applying AI to Threat Modeling - Where AI Thrives, Survives, and Dies](https://clearly-ai.com/blog/applying-ai-to-threat-modeling) - [Why We Build in Public](https://clearly-ai.com/blog/why-we-build-in-public) - [Solving the Threat Modeling Bottleneck with AI Workflows](https://clearly-ai.com/blog/solving-the-threat-modeling-bottleneck-with-ai-workflows) - [Clearly AI Named Finalist in the 2025 Okta Startup Challenge](https://clearly-ai.com/blog/clearly-ai-named-finalist-in-the-2025-okta-startup-challenge) - [Security, SOC 2, & Startups](https://clearly-ai.com/blog/security-soc-2-startups) - [Building Reliable AI Systems for Security and Privacy Reviews](https://clearly-ai.com/blog/building-reliable-ai-systems-for-security-and-privacy-reviews) - [How to Automate Security and Privacy Reviews with Clearly AI](https://clearly-ai.com/blog/how-to-automate-security-and-privacy-reviews-with-clearly-ai) - [One Year of Clearly AI](https://clearly-ai.com/blog/one-year-of-clearly-ai) - [Navigating EU RED Compliance: Meeting the August 2025 Deadline](https://clearly-ai.com/blog/navigating-eu-red-compliance-meeting-the-august-2025-deadline) - [The AI Engineer Cheat Sheet](https://clearly-ai.com/blog/the-ai-engineer-cheat-sheet) - [Intelligent Vendor Risk Assessments](https://clearly-ai.com/blog/intelligent-vendor-risk-assessments) - [Clearly AI wins the AWS Bedrock Builder's Challenge](https://clearly-ai.com/blog/clearly-ai-wins-the-aws-bedrock-builder-s-challenge) - [Reviews, reviews, reviews!](https://clearly-ai.com/blog/reviews-reviews-reviews) - [Halfway through YC](https://clearly-ai.com/blog/halfway-through-yc) - [llms.txt — site overview for LLMs](https://clearly-ai.com/llms.txt) - [llms-full.txt — full site content for LLMs](https://clearly-ai.com/llms-full.txt) - [sitemap.xml — all public routes](https://clearly-ai.com/sitemap.xml) - [Documentation](https://docs.clearly-ai.com/docs) [Canonical page](https://clearly-ai.com/compare/clover)