About
What is kodus-ai?
kodus-ai is an AI code review tool designed to enhance code quality and streamline development workflows. It provides users with extensive control over model selection, supporting various LLMs like Claude, GPT-5, Gemini, Llama, GLM, Kimi, and any OpenAI-compatible endpoint, ensuring zero markup on LLM costs. The tool learns from your project's context, adapting to architecture, standards, and workflows, and allows for custom review rules defined in plain language. It prioritizes privacy and security, ensuring source code is not used for model training, data is encrypted, and self-hosted runners are supported. Kodus-ai integrates seamlessly with native Git workflows across GitHub, GitLab, Bitbucket, and Azure Repos, and is ready for both CLI and CI/CD environments, enabling local and pipeline-based reviews. It also helps track technical debt and delivery metrics.
Best used for
Ideal for developers who need to automate code reviews, enforce custom coding standards, and integrate AI seamlessly into their existing Git workflows. Especially valuable for teams seeking full control over their AI model choices and LLM costs while maintaining high privacy and security standards.
Common actions
workflowslow-code/no-codeopen-sourcedeepfake"AI Agents"github copilotface swappingautomated workflowcollaboration
Capabilities
Key features
- Model agnostic AI review
- Zero LLM cost markup
- Learns from project context
- Custom review rules
- Native Git workflow integration
- CLI + CI/CD ready
- Tracks operational impact
Integrations
githubgitlabbitbucketazure-repos
Pricing & Plans
Freemium · Paid · Enterprise
FAQs
What AI models does Kodus AI support?
Kodus AI is model agnostic, supporting Claude, GPT-5, Gemini, Llama, GLM, Kimi, and any OpenAI-compatible endpoint. This allows users to choose their preferred model and avoid vendor lock-in, while also controlling costs directly with model providers.
How does Kodus AI handle privacy and security?
Kodus AI ensures privacy and security by not using source code to train models. Data is encrypted both in transit and at rest. Additionally, it supports self-hosted runners, providing an extra layer of control for sensitive projects and environments.
Can I define custom code review rules with Kodus AI?
Yes, Kodus AI allows users to define custom review rules using plain language. This feature enables teams to enforce their specific architectural guidelines, coding standards, and workflow requirements directly within the AI review process.
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