How much does CodeAnt AI cost?

AI Code Review is $30 a user a month, or $24 billed yearly, after a 14 day trial with 100 pull request reviews; Code Security and Code Quality each cost $250 a month per 10 users, or $200 yearly, and Dev Metrics $25 a user, or $20 yearly. The first full AI pentest is free, later runs and the unlocking of high and critical findings use credits with no listed price, and gray box and white box pentests are quoted. Enterprise is custom, open source projects are free, and teams over 100 developers get custom pricing.

What are the best alternatives to CodeAnt AI?

Based on documented capability coverage across the Agentic Index 14 point taxonomy, the closest alternatives to CodeAnt AI among security and SOC agents are Dropzone AI, BlinkOps, Command Zero, Drata. Each is graded on the same public evidence, and no vendor pays for placement.

Does CodeAnt AI support MCP and tool calling?

Full under the Agentic Index verification standard. CodeAnt AI publishes public evidence of Model Context Protocol (MCP) support, tool calling, and API or SDK extensibility for connecting agents to external tools. Evidence basis: A REST API with bearer tokens scoped by role and repository publishes an OpenAPI file of 29 POST endpoints for analyses, agent scans, dismissals, teams, metrics, audit events, containers and the hotlist, though none starts a pentest. The co. Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

Does CodeAnt AI have SOC 2, SSO and role based access control?

Full under the Agentic Index verification standard. CodeAnt AI publishes public evidence of enterprise security and identity controls, covering a compliance posture such as SOC 2 or ISO 27001, single sign on (SSO or SAML), and role based access control (RBAC). Evidence basis: CodeAnt holds a SOC 2 Type II report and a HIPAA attestation, published through a Sprinto trust center. Access runs through Member, CI/CD and Admin roles plus custom roles scoped by repository or team, and Enterprise adds single sign on wit. Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

Can CodeAnt AI be self hosted or run in a private VPC?

Full under the Agentic Index verification standard. CodeAnt AI publishes public evidence of self hosted or private VPC deployment, along with data residency options for controlling where agent data is processed and stored. Evidence basis: The service runs as SaaS in a region the customer chooses, including the EEA, with processing in the US, UK and India. Enterprise customers can deploy on premises, in a VPC, in a private cloud or in their own data center, and the CLI and CI. Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

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CodeAnt AI

Also known as: CodeAnt, CodeAnt AI, Inc., codeant.ai

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Security / SOC agentindependentVerified 2026-11-08

Entry priceAI Code Review Premium at $30 a user a month, or $24 billed yearly; Code Security and Code Quality at $250 a month per 10 users, or $200 yearly; first AI pentest free.Full pricing detail

CodeAnt AI is a security platform from CodeAnt AI, Inc. of San Francisco that pairs AI pentesting agents with AI code review. Its agents run black box tests against a customer's exposed apps and APIs and white box exploitation from source code, chaining findings into proven attack paths, while the code half reviews every pull request, runs SAST, SCA, secrets and IaC checks, scans clouds and containers, and gates merges. Code review costs $24 a user a month billed yearly, and the first pentest is free.

CodeAnt AI, Inc., a Delaware company in San Francisco founded in 2023 by Amartya Jha and Chinmay Bharti and backed by Y Combinator, sells what it calls continuous cyber defense: AI pentesting, application and cloud security scanning, and AI code review in one platform. Phunware, Commvault, 11x, HockeyStack, NRG and Akasa Air are among its published customer stories, and it works with GitHub, GitHub Enterprise Server, GitLab, Bitbucket and Azure DevOps.

Pentesting comes in three forms. A black box test starts from the dashboard against a verified domain, discovers and enumerates the attack surface, validates exploits and chains them into breach paths over a few hours to two days, and white box AI exploitation reads the customer's code to build and confirm attack paths; CodeAnt's security researchers review each critical finding before it reaches the report, and gray box testing is a private engagement run by that team.

On the code side, AI Code Review comments on every pull request with fixes a developer commits or hands to Cursor or Claude Code, writes descriptions and labels, learns from dismissed suggestions, and can approve low risk pull requests on GitHub behind a shadow mode, a risk threshold and a confidence floor. SAST, SCA, secrets, IaC and SBOM scans, DAST that confirms exploits, posture checks across AWS, Google Cloud and Azure, container scanning and quality gates with pass or fail status checks round out the platform, and a Frontend QA agent that drives a real browser is open to selected GitHub customers.

AI Code Review costs $30 a user a month, or $24 billed yearly, after a 14 day trial with 100 reviews, while Code Security and Code Quality each cost $250 a month for 10 users, or $200 yearly, and Enterprise is quoted with single sign on, audit logs and on premises or VPC deployment. The first full AI pentest is free, later runs use credits, and high and critical findings unlock on payment. CodeAnt holds SOC 2 Type II and HIPAA attestations, offers preset and custom roles scoped by repository or team, keeps immutable audit events for 180 days, lets customers choose their data region, and does not train on customer data.

CodeAnt fits engineering and security teams that want pentesting, code scanning and pull request review from one vendor, priced so smaller teams can start without a services contract. It fits less well for buyers who need to know which AI models run their reviews, published prices for each pentest credit, or a reviewer that writes and pushes fixes on its own.

Vendor details

Canonical URL

https://www.codeant.ai

Subcategory

AI pentesting agents and continuous application, code and cloud security, with AI pull request review and quality gates

Funding status

Venture backed; a $2M seed in 2025 after Y Combinator's Winter 2024 batch.

Company status

independent

Use cases & customers

Primary use cases

black box and white box AI pentesting of apps and APIsAI review of every pull requestSAST, SCA, secrets, IaC and DAST scanningcloud and container security posture checksquality and security gates in CI

Target customers

engineering teams on GitHub, GitLab, Bitbucket or Azure DevOpssecurity teams that want AI pentesting without a services contractstartups preparing for SOC 2, HIPAA or customer security reviewsenterprises that need on premises or VPC deployment

Deployment options

CodeAnt cloud with a customer chosen region, including the EEAOn premises, VPC, private cloud or data center deployment on EnterpriseCLI, IDE extensions and a local MCP server on the developer's machinePublished outbound IPs for allowlisting pentest traffic

Integrations

GitHub and GitHub Enterprise Server, GitLab including self hosted, Bitbucket and Bitbucket Data Center, and Azure DevOps for reviews, labels, approvals and status checks; GitHub Actions, GitLab CI, Bitbucket Pipelines, Azure Pipelines, Jenkins and CircleCI; Jira, Linear and Azure Boards; Slack and Microsoft Teams; AWS, Google Cloud and Azure through read only roles; Checkov, ESLint, Pylint and Semgrep; VS Code, Cursor, Windsurf, JetBrains and Visual Studio; a REST API, CLI and MCP server.

In practice

A startup verifies its domain and starts a black box pentest from the dashboard; hours later the agents have chained an exposed admin endpoint and a weak token check into a confirmed account takeover, and the report shows the requests that proved it.

An engineering team turns on AI Code Review across its GitHub organization, runs automatic approval in shadow mode for two weeks, then lets it approve low risk pull requests while a person commits every suggested fix.

A platform engineer connects AWS with a read only role, runs weekly posture scans, and fails CI when new secrets or critical SAST findings appear in a pull request.

Sources & related URLs

Related / legacy domains

https://docs.codeant.ai https://www.codeant.ai/pricing https://www.codeant.ai/pentesting https://codeantai.trust.site

Research sources

Agentic Index coverage score

12.0 / 14 capabilities · 86%

Integrations & Tool Calling	Full
Review comments, pull request descriptions and labels land on GitHub, GitHub Enterprise Server, GitLab, Bitbucket and Azure DevOps, an approving review goes onto low risk GitHub pull requests, and status checks attach to CI runs. Teams create Jira and Linear tickets from findings, sprint reports go to Slack, and cloud scans reach AWS, Google Cloud and Azure through read only roles. Pentest and DAST agents send live requests and exploit attempts to the verified apps and APIs in scope. Sourcedocs.codeant.ai/pull_request/features/auto_approve_prread 2026-11-08
Workflow Orchestration	Full
White box AI exploitation reads the customer's code, chains individual vulnerabilities into attack paths and validates which ones are exploitable, and a black box run moves through discovery, enumeration, validation, breach chaining and retesting. The agent scan explores code with a model and filters false positives through a reflection step before results are posted, and a separate policy agent weighs each pull request's risk before any automatic approval. Sourcedocs.codeant.ai/pentesting/white_boxread 2026-11-08
Knowledge Grounding & RAG	Partial
Each review builds a static call graph of the repository and reads related files for context, and black box and DAST runs discover subdomains and services before testing them. An organization wide hotlist ranks open findings across repositories. Code and syntax trees are deleted when each scan or review completes, so no searchable index of the customer's code persists from one run to the next. Sourcedocs.codeant.ai/blog/superhuman-contextread 2026-11-08
Human Oversight & Guardrails	Full
Black box and DAST testing require proof of domain ownership by DNS or file, rules of engagement fix targets, windows and methods, destructive tests need written approval, and testing against production pauses on request. Automatic pull request approval runs first in a shadow mode, applies a risk threshold and an 80 percent confidence floor, and fails closed, while suggested fixes wait for a developer to commit them. The MCP server stays read only until a team switches writes on. Sourcedocs.codeant.ai/pull_request/features/auto_approve_prread 2026-11-08
Security, Identity & Governance	Full
CodeAnt holds a SOC 2 Type II report and a HIPAA attestation, published through a Sprinto trust center. Access runs through Member, CI/CD and Admin roles plus custom roles scoped by repository or team, and Enterprise adds single sign on with SAML. Model providers are contractually barred from training on customer data or keeping prompts, work runs in isolated short lived environments, data moves over TLS 1.2 or later and rests under AES 256, and breaches are reported within 24 hours. Sourcecodeantai.trust.siteread 2026-11-08
Observability & Auditability	Full
An immutable audit event log, read through the API, keeps 180 days of activity. DAST results carry request logs, routes, checks and evidence and export to XLSX or PDF, pentest reports show the discovered attack surface, each finding with its proof and the history of every reverification, and Frontend QA keeps screenshots and recordings. Dashboards, hotlist exports and PDF executive reports summarize the rest for security and engineering leads. Sourcedocs.codeant.ai/api-reference/audit-logs/list-audit-eventsread 2026-11-08
Memory & State Persistence	Full
Replying to dismiss a review suggestion creates a learning that CodeAnt applies to matching files in later reviews, and an organization can view, edit and delete each learning in its settings. Dismissals and severity overrides are kept with their reasons and reachable through the API, and saved Frontend QA sessions are stored encrypted and refreshed. Findings, pentest evidence and custom prompts stay for the contract term and are returned or deleted within 90 days after it ends. Sourcedocs.codeant.ai/pull_request/features/learningsread 2026-11-08
Deployment & Data Residency	Full
The service runs as SaaS in a region the customer chooses, including the EEA, with processing in the US, UK and India. Enterprise customers can deploy on premises, in a VPC, in a private cloud or in their own data center, and the CLI and CI integrations point at a self hosted base URL. Pentest traffic leaves from published IP addresses that the customer can allowlist. Sourcecodeant.ai/privacy-policyread 2026-11-08
Prebuilt Agents / Templates / Packs	Full
Four agent personas cover maintainability, performance, pentesting and design critique, and rule libraries span the OWASP Top 10 across more than 25 languages beside an infrastructure security database. Compliance mappings cover SOC 2, HIPAA, ISO 27001 and 27002, PCI DSS v4.0, RBI guidelines, GDPR, MISRA C and C++ and AUTOSAR C++14, and a Claude Code plugin with skills packages reviews for coding agents. Sourcedocs.codeant.ai/llms.txtread 2026-11-08
Triggers & Channel Coverage	Full
Pull and merge request webhooks start reviews, as do an @codeant-ai review comment, commits in the IDE, the CLI and CI steps. API calls start an analysis or an agent scan, DAST scans recur from daily to monthly, cloud posture scans run weekly by default, Frontend QA starts on a GitHub deployment status event, and pentests start from the dashboard. A local MCP tool can also start scans once writes are switched on. Sourcedocs.codeant.ai/scan_center/code_security/dastread 2026-11-08
Model Flexibility & Routing	Not documented
Reviews and scans run on large language models from third party providers and on models CodeAnt operates itself, none of them named, and the EU AI Act statement still carries an unfilled placeholder where the providers belong. Customers cannot choose a model or bring their own key, and policy checks run on CodeAnt's managed provider without drawing on AI credits. Sourcedocs.codeant.ai/compliance/eu-ai-act-statementread 2026-11-08
APIs / SDKs / MCP Extensibility	Full
A REST API with bearer tokens scoped by role and repository publishes an OpenAPI file of 29 POST endpoints for analyses, agent scans, dismissals, teams, metrics, audit events, containers and the hotlist, though none starts a pentest. The codeant CLI wraps it, and a local MCP server with 24 read tools adds tools that start scans, resolve pull request comments and call the API for writes when its read only mode is turned off. Sourcedocs.codeant.ai/cli/mcp-serverread 2026-11-08
Testing, Debugging & Optimization	Full
Quality gates on secrets, duplicate code, SAST findings and coverage return a pass or fail result on each pull request, and CI status checks for SAST, SCA and code review can block a merge when they fail. DAST suppresses findings it cannot confirm and labels the rest as confirmed exploits, white box testing offers a high precision mode, and CodeAnt publishes benchmark results for its own review agent. Sourcedocs.codeant.ai/llms.txtread 2026-11-08
Browser / Computer-use	Partial
The Frontend QA agent opens a real browser on a deployed preview, signs in with a saved Playwright session and records screenshots and video, but it is open only to selected GitHub customers. Pentest and DAST agents work through HTTP requests and responses, with curl commands to reproduce each finding, rather than by driving a browser or a desktop. Sourcedocs.codeant.ai/pull_request/features/frontend_qaread 2026-11-08

The Agentic Index coverage score grades every vendor Full, Partial or Not documented against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded

Pricing

AI Code Review Premium at $30 a user a month, or $24 billed yearly; Code Security and Code Quality at $250 a month per 10 users, or $200 yearly; first AI pentest free.

Per user a month for AI Code Review and Dev Metrics, per block of 10 users a month for Code Security and Code Quality, billed monthly or yearly, plus credits for pentest runs and for unlocking high and critical findings.

Free tierTrial available

Included quota

Premium covers unlimited pull request reviews, SAST on pull requests, Jira and Azure Boards, Slack support and SOC 2, HIPAA and VAPT reports; the first full AI pentest is included free, with low and medium findings always visible.

What is public

Per user and per 10 user prices for code review, security, quality and metrics modules, the free first pentest and the credit mechanics, with Enterprise and gray and white box pentests by contact.

Billing mechanics

Module subscriptions per user or per 10 users billed monthly or yearly, plus pentest credits.

Cost watchouts

High and critical pentest findings stay locked until paid for, credit prices are not published, and an unattributed ten seat minimum appears on the pricing page.

Variable cost rationale

Code review and scanning are flat per user or per 10 users, but pentest runs and access to high and critical findings are bought in credits with no listed price, and black box testing is described as a flat annual price per application.

Additional watchouts

Pentest costs are not published as dollar amounts.

Overage / add-ons

Each pentest run after the first uses one credit and unlocking its high and critical findings uses another; credits expire a year after the last purchase and no credit price is listed.

Sales call required

Mixed (some tiers require a call)

Free / trial

A 14 day AI Code Review trial with 100 pull request reviews and unlimited seats, one free full AI pentest, and free use for open source projects.

Lowest paid plan

AI Code Review Premium at $30 a user a month, or $24 billed yearly

Commercial notes

CodeAnt AI, Inc. sells self serve modules and a free first pentest, with Enterprise and deeper pentests through sales.

Key ambiguities

Pentest pricing is described three ways, as unpriced credits, a flat annual price per application and no charge without a critical finding, and llms.txt still lists older, lower prices.

Cancellation / refund

Self serve plans bill monthly or yearly; Enterprise runs on a custom MSA.

Support SLA / resale

Enterprise adds a dedicated success manager and a staff engineer, single sign on, audit logs and on premises or VPC deployment.

Missing data

Pentest credit prices, Enterprise pricing and gray box engagement pricing.

Agentic Index verified 2026-11-08

Official pricing page Docs

Related vendors

Alternatives to CodeAnt AI

The closest documented capability profiles to CodeAnt AI among security and SOC agents tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.

Dropzone AI11.0 / 14Adds documented Model Flexibility & Routing
BlinkOps10.5 / 14Fuller documented coverage on Knowledge Grounding & RAG
Command Zero10.5 / 14Fuller documented coverage on Knowledge Grounding & RAG
Drata10.5 / 14Fuller documented coverage on Knowledge Grounding & RAG
Snyk11.5 / 14Adds documented Model Flexibility & Routing
Tines11.5 / 14Adds documented Model Flexibility & Routing

Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded

Compare CodeAnt AI with other vendors →Compare all security and SOC agents →See where CodeAnt AI ranks →AI agents for software development →

Data confidence: high