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Kodus AI
Summary
Most AI code review tools run on your data, on their infrastructure, with their model, at their price — and if any of those defaults don't fit your security posture, you're blocked. Kodus flips that assumption: you choose the model, you own the infrastructure, you control where the code goes.
Kodus runs as an agent that watches pull requests across GitHub, GitLab, Bitbucket, and Azure Repos, posts inline comments, and can convert unresolved suggestions directly into tracked issues in Jira, Linear, or Notion. You write review rules in plain language — no DSL, no YAML policy files — and the agent applies them on every diff. Because you supply your own API keys and can self-host the full stack via Docker Compose, token costs are billed directly to your LLM provider, not marked up through Kodus. The ceiling appears when your rules grow complex enough that plain-language enforcement becomes ambiguous; at that point, teams either tighten the rule wording iteratively or accept occasional false-positive comments that engineers learn to dismiss.
Bottom line: The right pick for a regulated-industry team that needs code review automation and cannot ship source code to a third-party SaaS — but a team that wants zero-config, managed, out-of-the-box AI review with no infrastructure overhead will find the self-hosting requirement a barrier, not a feature.
Pricing Plans
SubscriptionLast verified 2 days ago- Price
- $10/dev monthly or $8/dev annual
- Free Tier
- Up to 10 Kody Rules, Up to 3 Active plugins, Unlimited PRs using your own API key, Unlimited API key Users
Community
Self-hosted or hosted by Kodus
- Unlimited PRs using your own API key
- Up to 10 Kody Rules
- Up to 3 Active plugins
- Unlimited API key Users
- Kody Learnings and Memory
- Unlimited Quality Radar issues
- BYOK support
Teams
Hosted by Kodus, per developer monthly or annual
- Unlimited PRs using your own API key
- Unlimited Kody Rules
- Unlimited Active plugins
- Unlimited API key Users
- Priority queue for Kody Agents
- Engineering Metrics / Cockpit
- BYOK support
Enterprise
Self-hosted or hosted by Kodus with advanced features
- Unlimited PRs using Kodus AI Tokens
- Unlimited Kody Rules
- Unlimited Active plugins
- Unlimited API key Users
- Priority queue for Kody Agents
- Engineering Metrics / Cockpit
- SSO
- RBAC + audit logs + analytics
- SOC 2 in progress
- Private Discord + Email + up to 5h/month dedicated support
View full pricing on github.com →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- Bring-your-own-key model routing, so switching between OpenAI, Anthropic, or a local model when costs change is a configuration update, not a vendor conversation.
- Full self-hosted deployment via Docker Compose, so source code never leaves your infrastructure — which removes the blocker for teams with data-residency or compliance requirements that rule out third-party SaaS.
- Automatic issue creation from unresolved review comments, so technical debt surfaces in your existing tracker (Jira, Linear, Notion) instead of dying in a closed PR thread.
- Plain-language review rule definitions, so teams enforce custom standards without learning a DSL or maintaining a separate policy-as-code layer.
- Works across GitHub, GitLab, Bitbucket, and Azure Repos from a single deployment, so teams on non-GitHub platforms are not treated as second-class integrations.
Cons
Sign in to edit- Self-hosting requires Docker Compose setup and ongoing infrastructure maintenance; teams that want managed, zero-ops AI code review hit this wall on day one and frequently move to a fully-managed SaaS alternative instead.
- Plain-language review rules hit an ambiguity ceiling as rule sets grow — when a rule is broad enough to produce frequent false-positive comments, the only remedies are iterative rewording or engineering team tolerance, neither of which scales cleanly past a few dozen active rules.
- MCP-based integrations with Jira, Notion, and Linear add context to reviews but require configuration and ongoing credential management; teams that skip this setup get shallower spec-aware review and lose the primary workflow integration advantage Kodus advertises over simpler linting-layer tools.
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About
- Platforms
- GitHub, GitLab, Bitbucket, and Azure DevOps
- API Available
- Yes
- Self-Hosted
- Yes
- Last Updated
- 2026-06-01T01:57:32.494Z
Best For
Who it's for
- Teams wanting full control over LLM model choice and costs
- Organizations with data privacy or compliance requirements
- Engineering teams using GitHub, GitLab, Bitbucket, or Azure Repos
- Teams that want to deploy on your own infrastructure to ensure code never leaves their environment, which is a non-negotiable requirement for many financial, healthcare, and enterprise organizations
- Teams looking to define custom code review standards
What it does well
- Reads diffs, posts inline comments, and respects your existing review workflows
- Automatically turns unimplemented suggestions into issues, helping your team visualize and reduce technical debt over time
- Connect tools like Jira, Notion, or Linear so Kody can understand specs, tasks, and requirements while reviewing your code
- Enforce custom team standards in plain-language review rules
- Run reviews locally and in pipelines
Integrations
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Frequently Asked Questions
- Is Kodus AI free?
- Kodus AI is a paid tool ($10/dev monthly or $8/dev annual). A 14-day free trial is available.
- Is Kodus AI open source?
- Yes. Kodus AI is open source — the source repository is at https://github.com/kodustech/kodus-ai.
- Does Kodus AI have an API?
- Yes. Kodus AI exposes a developer API. See the official documentation at https://github.com/kodustech/kodus-ai for details.
- Can I self-host Kodus AI?
- Yes. Kodus AI supports self-hosting on your own infrastructure.
- What platforms does Kodus AI support?
- Kodus AI is available on: GitHub, GitLab, Bitbucket, and Azure DevOps.
Hours Saved & ROI Stories Community
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Curated lists that include this category
Kodus deploys as an agent that triggers on pull request events, reads the diff, applies your configured review rules, and posts inline comments — all without you intervening between the trigger and the result. It connects to your Git platform of choice (GitHub, GitLab, Bitbucket, Azure Repos) and optionally pulls context from project management tools via MCP integrations, so when it reviews a PR it can cross-reference the Jira ticket or Notion spec the change is supposed to satisfy. Unimplemented suggestions can be automatically filed as issues, giving teams a visible backlog of technical debt rather than comments that age and disappear.
The differentiating feature is full model and infrastructure control. You bring your own API key — OpenAI, Anthropic, a locally-run model, or anything else your team has access to — which means the LLM cost line on your cloud bill is transparent and negotiable, not bundled into a per-seat subscription markup. The Community edition is free and self-hostable via Docker Compose, so code never leaves your environment. For financial services, healthcare, or any team under data-residency obligations, that is a non-negotiable requirement that most SaaS-only competitors cannot satisfy.
Kodus fits best when you have a team willing to own the deployment and iterate on review rule definitions. It does not fit when your goal is a five-minute SaaS signup with no infrastructure to maintain — the self-hosted path requires Docker Compose setup and ongoing maintenance. Review rule quality is also proportional to how precisely you write them; the plain-language interface lowers the floor for getting started, but does not raise the ceiling on rule precision as fast as a structured policy language would for teams with mature review standards.