
CodeAnt AI
CodeAnt AI is an agentic security platform for engineering teams: its agents reason across code, infrastructure and runtime to prove what is actually exploitable, review every pull request, and propose fixes — offensive testing alongside defensive scanning.
What is CodeAnt AI?
CodeAnt AI presents itself as an exploit-based agentic security platform: AI agents that reason across code, infrastructure and runtime to prove what is exploitable and fix it. Instead of stacking separate scanners, it builds a single graph over repositories, infrastructure-as-code, dependencies, secrets, endpoints, cloud configuration and commit history, then reasons over that graph. The platform openly has two halves: a defensive layer that analyses a change before it merges, and an offensive layer that tries to break what is already running. Five product lines sit on top — AI Pentesting, AI Code Review, Code Security, Code Quality and Dev Metrics — with Developer 360 as the reporting layer. AI Code Review works at pull-request level with full repository context: inline comments, PR summaries, sequence diagrams, AI Learnings that absorb team conventions, an AI chat, reproduction steps, a CI/CD review hook and quality gates. Code Security bundles SAST, attack-path analysis, cloud misconfiguration detection, SCA, secret scanning, EPSS prioritisation, IaC checks, SBOM generation and security gating. Code Quality runs more than 30,000 code-smell checks, flags complex functions, dead code and duplication, generates docstrings in bulk and tracks test coverage, with the option to enforce it and block a merge. Dev Metrics and Developer 360 report DORA metrics, productivity, PR cycle time, SLA tracking and CSV or PDF audit exports. AI Pentesting comes in three depths — Blackbox on the publicly reachable surface, Whitebox, and Graybox with Code Memory — covers the OWASP Top 10, simulates exploits and maps attack paths. More than 30 languages and formats are analysed, from Java, Python, Go and Swift to Terraform, Kubernetes and Docker, and on to legacy stacks such as COBOL, ABAP, RPG and JCL. It plugs into GitHub, GitLab, Bitbucket and Azure DevOps, into VS Code, Cursor, Windsurf and IntelliJ, and pushes tickets to Jira, Azure Boards or Linear with alerts in Slack, Teams or email. A documented REST API is available. Deployment is SaaS, inside the customer's own AWS, GCP or Azure VPC, or fully on-premises. The headline numbers are the vendor's own: 80% less PR review time, over a million pull requests a month, more than a billion lines scanned and 87.6% F1 on security patches from an in-house benchmark. Its research team has disclosed over 100 CVEs, including CVE-2026-29000 in pac4j-jwt at CVSS 10.
What it does
- Run an autonomous AI pentest and get an audit-grade PDF report within 48 hours.
- Review every pull request with whole-repository context, inline comments and an automatic summary.
- Apply a suggested fix in one click, or open it in your IDE with the prompt already loaded.
- Scan for SAST issues, hardcoded secrets, IaC misconfigurations, vulnerable dependencies, SBOM contents, EPSS scores and end-of-life packages.
- Detect cloud misconfigurations and map them to real attack paths.
- Block a merge with quality gates and policy or test-coverage thresholds.
- Produce engineering metrics: DORA indicators, PR cycle time, SLA tracking and per-developer impact.
When to use CodeAnt AI / When not to
A quick filter to help you decide if CodeAnt AI is the right fit.
When to use CodeAnt AI
- Engineering organisations of 100 developers and up, working across many repositories, that want one platform instead of the four or five review, quality, security and coverage tools they run today.
- AppSec and application security teams needing SAST, secret detection, IaC checks, SCA, SBOM, cloud posture and agentic pentesting from a single console.
- Startup CTOs and engineering leads, who can claim the startup discount or the 100% waiver granted to open-source projects.
- Teams with an audit to satisfy, who need an audit-grade PDF report mapped to SOC 2 or ISO 27001 controls for their own auditors within 48 hours.
- Organisations under strict confidentiality constraints that must keep source code inside their own AWS, GCP or Azure VPC, or entirely on-premises, with SSO, RBAC and audit logs.
When not to use CodeAnt AI
- Solo developers on a closed personal project: billing is per developer per month and the product is positioned for teams of 100 engineers and up.
- Teams hoping for a permanently free commercial tier: outside open source, the High and Critical pentest findings only unlock once you pay.
- Squads of fewer than ten people, since the Premium Code Quality and Code Security plans start at a ten-seat minimum.
- Anyone whose work sits outside software development: the entire product revolves around source code held in a Git repository.
- Developers after an in-editor coding assistant: CodeAnt AI reviews and scans rather than autocompleting code, ships no mobile app, and publishes its interface and documentation in English only.
How to use CodeAnt AI
A typical end-to-end flow, from setup to results.
- Start the 14-day free trial on app.codeant.ai; no credit card is required.
- Sign in with your Git provider: GitHub, GitLab, Bitbucket or Azure DevOps.
- Select the repositories to analyse and configure the analysis in the Scan Center.
- Let the first full repository scan run, not just the open pull requests.
- Open a pull request: CodeAnt AI posts a summary, inline comments and a sequence diagram.
- Apply a fix in one click, or open it in your editor through the VS Code, Cursor, Windsurf or IntelliJ extension.
- Define quality gates and custom rules, then roll them out across several repositories at once.
- Wire the review hook into your CI/CD pipeline and push findings as tickets to Jira, Azure Boards or Linear.
- Launch an AI pentest from the pentesting form, collect the PDF report within 48 hours, then run Reverify once the fixes are in.
- Track the security and DORA dashboards; for VPC or on-premises deployment and SSO, go through the sales team.
Pros & Cons
Pros
- Consolidation: the vendor claims the platform replaces four to five separate tools covering review, quality, security and coverage.
- An offensive layer that is rare at this price point: agentic pentesting, DAST and cloud posture checks sitting next to static analysis.
- SOC 2 Type II certified and HIPAA compliant, with a public trust centre listing controls, policies and subprocessors.
- Zero data retention as a design commitment: no code storage, ephemeral scan environments, LLM requests handled in memory.
- On-premises or own-VPC deployment on AWS, GCP or Azure, with SSO and RBAC.
- Technical credibility that is documented rather than claimed: over 100 CVEs disclosed, CVE-2026-29000 in pac4j-jwt at CVSS 10, and a Gartner Cool Vendor 2026 badge.
- Low-friction entry: a 14-day trial without a credit card, free access for open source and a startup discount.
Cons
- The pricing table is rendered in JavaScript and never appears in the served HTML; only the site's structured data exposes a figure, a floor price of USD 20.
- Published amounts disagree between pages: USD 20 in structured data, USD 24 per user per month in the product content, USD 24-30 per user per month on the comparison pages.
- The Premium Code Quality and Code Security plans require a minimum of ten seats.
- High and Critical pentest findings stay locked behind payment.
- A young company: started in June 2023, Y Combinator W24, with a USD 2 million seed round in May 2025.
- No mobile application, and no EU representative designated under Article 27 of the GDPR.
- A generic privacy policy with no effective date shown, and no dedicated legal or data-protection mailbox — everything goes through support@codeant.ai.
Pricing & Plans
A 14-day free trial is offered without a credit card, and a limited free entry point exists: one full AI pentest scan is included, Low and Medium findings remain free, and open-source projects are granted a 100% discount. The lowest paid price the site publishes is USD 20.00 per user per month, taken from the structured pricing data on the home and pricing pages. Published figures vary from page to page: the comparison pages quote USD 24-30 per user per month for code review and USD 150 per 10 users per month for the security and quality platforms, while the site's own content mentions a Basic plan at USD 24 per user per month and a Premium plan starting at a ten-seat minimum for USD 200 per 10 users per month. The pricing table itself is rendered in JavaScript and is absent from the served HTML, so these amounts should be confirmed on the vendor's pricing page. Enterprise pricing is quoted on request, and the product can also be purchased through AWS Marketplace and Microsoft Marketplace.
- one full scan included
- Low and Medium findings always free
- High and Critical findings unlocked on payment
- with exploit simulation
- attack-path mapping
- step-by-step remediation and OWASP Top 10 coverage.
- quoted at USD 24 per user per month on monthly billing in the site's own content
- and at USD 24-30 per user per month on the comparison pages.
- ten-seat minimum
- quoted at USD 200 per 10 users per month
- including AI SAST covering OWASP and CWE
- IaC
- SCA
- secret scanning
- SBOM
- EPSS and end-of-life detection.
- Contact Sales. On-premises or VPC deployment
- SSO and RBAC
- audit logs
- guided onboarding and a dedicated Success Manager.
- free
- through a 100% discount.
- the Compare Plans table on the pricing page loads in JavaScript and is missing from the served HTML
- the amounts differ between pages
- and the structured data declares a floor price of USD 20.00 — check each figure on the vendor's own page.
Data, GDPR & hosting
A consolidated view of how CodeAnt AI handles your data.
GDPR overview
GDPR implementation is documented, not merely asserted. The demo page states "SOC 2, GDPR compliant", and a dedicated Data Processing Agreement is published and billed as GDPR-ready. It defines controller, processor and processing by direct reference to Regulation 2016/679, incorporates controller-to-processor and processor-to-processor standard contractual clauses for transfers to third countries, commits CodeAnt AI to assist with data-subject requests through the service controls, requires notification of security incidents without undue delay, and promises audit reports from an annual independent audit under ISO 27001 or an equivalent standard — a contractual audit commitment, not a certification the vendor holds. Two gaps stand out: no Article 27 EU representative is named and no EU address is given; and the privacy policy itself never mentions the GDPR, saying only that using the service implies consent to transfers outside your country of residence. Services are not intended for under-16s.
Who owns the data?
Under its Data Processing Agreement, CodeAnt AI, Inc. acts as a processor on the customer's instructions, while the customer stays controller of the repository data it submits. The trust centre states the code is never stored: each scan runs in an isolated, ephemeral environment. Customers can request the return or deletion of their data through the service controls at any time and for up to 90 days after termination, and can delete it from CodeAnt's network themselves. One licence runs the other way: CodeAnt AI may display a customer's name and logo in its marketing, revocable in writing to contact@codeantai.com within twenty business days. Formal notices go to support@codeant.ai.
Reuse rights
CodeAnt AI states plainly that it does not train on customer code: the models it serves are trained only on publicly available data, and LLM requests are ephemeral, processed in memory and neither logged nor retained by CodeAnt AI or by its model provider. Access is limited to the data that code review, quality and security analysis actually require, and nothing beyond. The findings, reports and suggested fixes the platform produces are the customer's to use inside its own engineering and audit workflows without asking permission. On the vendor's side, personal data serves to deliver and improve the service, fight fraud, communicate with users, meet legal obligations and measure traffic through Google Analytics; the privacy policy rules out sharing with third parties for direct marketing without consent and states that Do Not Track signals have no declared effect. Subprocessors are covered by a general authorisation, with a published list and thirty days' notice before a new one is added — notice a customer can object to by terminating, stopping the affected service, or having its data moved to another Region.
Data retention & training
Hosting summary
CodeAnt AI, Inc. is a United States company headquartered at 355 Bryant St, San Francisco, and its privacy policy states that using the service implies consent to information being transferred outside your country of residence, including to the United States. The trust centre publishes a subprocessor list: GCP, AWS and Microsoft Azure for IT infrastructure, plus Stripe, HubSpot, Slack and eight others. The three infrastructure subprocessors are declared as processing in the United States, the United Kingdom and India. For GDPR-covered data going to a third country, the DPA relies on standard contractual clauses, and it lets a customer objecting to a new subprocessor have its data moved to another Region. The trust centre also states that code is not stored at all: scans run in isolated, ephemeral environments and LLM requests are handled in memory and never logged. Enterprise customers can deploy inside their own AWS, GCP or Azure VPC, or entirely on-premises, where no data ever leaves their network. One technical caveat: the public IP the domain resolves to is an anycast CDN node in Amsterdam — content delivery, not a data-hosting jurisdiction.
Things to keep in mind
Risks and trade-offs to weigh before adopting CodeAnt AI.
- Sending source code to a third party: even with zero retention claimed, the SaaS mode means your code transits outside your own network, and the on-premises option is reserved for the Enterprise plan.
- Dependence on infrastructure subprocessors — GCP, AWS and Microsoft Azure — with processing declared in the United States, the United Kingdom and India.
- Over-trusting an automated reviewer: human review and developer vigilance quietly erode when a bot is expected to catch everything.
- Security false negatives: a clean report is not proof of safety, and no tool guarantees exhaustive coverage.
- Individual metrics: Developer 360 and per-developer impact scores can be repurposed for staff appraisal, with the managerial drift that follows.
- Costs that climb with seats and modules, with a ten-seat minimum on the Premium plans.
- A thin privacy policy with no effective date, and a single mailbox — support@codeant.ai — handling legal questions, data protection and support alike.
Setup & Integrations
Technical difficulty
Straightforward for its audience, which is technical by definition. Sign up for the 14-day trial on app.codeant.ai with no credit card, connect your Git provider over OAuth, pick repositories and let the first scan run; nothing is installed on a server. IDE extensions come from the VS Code, Open VSX and JetBrains marketplaces. Expect real configuration work afterwards: scan settings, custom rules, quality gates and the CI/CD review hook. On-premises or VPC deployment with SSO and RBAC is a genuine infrastructure project, reserved for Enterprise and handled through sales.
Deployment
Integrations
Supported languages
Behind CodeAnt AI
Fundraising
Social
Resources
All the official URLs gathered for verification and reference.
Alternatives
Tools that compete with or complement CodeAnt AI.
Frequently asked questions
Does CodeAnt AI store my source code?
Is my code used to train the models?
Is there a zero-retention policy?
Can I keep my code inside my own network?
Is there a free trial?
Which certifications does CodeAnt AI hold?
Which repositories and IDEs are supported?
Is there an API?
Is there a minimum age?
Is it free for open-source projects?
Should you pick CodeAnt AI?
CodeAnt AI's distinctive move is to put both halves of code security in one place: the defensive layer that analyses a change before it merges, and the offensive layer — agentic pentesting, DAST, cloud posture — that tries to break what is already running. Most tools in this space pick a side. Doing both from a single graph over repositories, dependencies, secrets, endpoints and cloud configuration is what backs the claim of replacing four or five separate products. The security posture is unusually verifiable for a company this young: SOC 2 Type II and HIPAA compliance are stated on a public trust centre alongside 50+ controls, 40+ policies and a named subprocessor list. The zero-retention claim and the on-premises or own-VPC option answer, concretely, the one objection that stops most engineering teams from sending source code to a vendor. Technical credibility is documented rather than asserted: over 100 CVEs disclosed, a CVSS 10 finding in pac4j-jwt, a Gartner Cool Vendor 2026 badge. The main reservation is commercial rather than technical. The pricing page renders its table in JavaScript, so the served page shows no figures at all, and the amounts that do appear elsewhere on the site disagree with each other: a floor price of USD 20 in the structured data, USD 24 per user per month in the product content, USD 24-30 on the comparison pages. Anyone budgeting for this should have the numbers confirmed in writing. The company is young too — founded in June 2023, a USD 2 million seed, a reported USD 60 million valuation in January 2026 — though funded and documented. It suits engineering organisations of a hundred developers and up working across many repositories, and teams with an audit to satisfy.
- Choosing a selection results in a full page refresh.
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