kodustech/kodus-ai

AI Code Review with Full Control Over Model Choice and Costs.

What it solves

Kodus AI provides an automated AI-powered code review system that integrates directly into the Git workflow. It helps engineering teams reduce technical debt, enforce architecture and security standards, and eliminate the repetitive manual feedback typically found in pull requests.

How it works

Kodus operates as a monorepo consisting of an API, a worker for review execution, a web dashboard, and a webhook service for Git providers. It integrates with GitHub, GitLab, Bitbucket, and Azure Repos to analyze pull requests. Users can connect their own LLM providers (BYOK) via an abstraction layer, allowing them to use models like Claude, GPT-5, Gemini, or Llama. The system uses "Kody Rules"—plain-language instructions—to apply specific organizational standards to reviews.

Who it’s for

Software engineering teams and organizations that want to automate code reviews, track delivery metrics, and maintain high code quality across multiple repositories without being locked into a specific LLM provider.

Highlights

  • Model Agnostic (BYOK): Support for multiple providers including OpenAI, Anthropic, and Google Gemini with no markup on token costs.
  • Kody Rules: Define custom review instructions in plain language to enforce security, testing, and architecture conventions.
  • Native Git Integration: Works directly within PRs across major platforms (GitHub, GitLab, Bitbucket, Azure Repos).
  • Kody Issues: Automatically tracks unimplemented suggestions from closed PRs and resolves them when fixes appear in future PRs.
  • Operational Cockpit: A dashboard to measure review effectiveness, repository health, and delivery metrics.
  • Flexible Deployment: Available as a cloud service, a self-hosted instance, or via a CLI for local and CI/CD pipeline reviews.

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