AI Tool

Revolutionize Your Code Reviews with CodeRabbit AI

Automated pull-request comments with severity tagging

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1Cut review times from hours to seconds with intelligent automation.
2Enjoy comprehensive insights through context-aware code analysis.
3Integrate seamlessly with your favorite IDE for effortless workflows.

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overview

What is CodeRabbit?

CodeRabbit is an AI-powered code review tool designed to enhance your development process. By analyzing entire codebases, it helps teams identify issues that traditional tools overlook, ensuring higher quality code and faster deployment.

  • 1Automated reviews for GitHub, GitLab, and Azure DevOps.
  • 2Supports a flexible API for custom solutions.
  • 3Offers a free tier to get started without any upfront costs.

features

Key Features

CodeRabbit brings unparalleled efficiency and accuracy to your code review process. Our AI technology goes beyond simple pattern matching to catch critical issues like race conditions and architectural drift.

  • 1Real-time reviews directly in your IDE.
  • 2Sub-3% false-positive rates for optimized review cycles.
  • 3Agentic chat capabilities generate unit tests and create issues automatically.

use cases

Why Use CodeRabbit?

Whether you are a small team or a large enterprise, CodeRabbit enhances productivity and code quality. Developers can focus on more complex issues, while mundane tasks are handled automatically.

  • 1Ideal for teams looking to save time on code reviews.
  • 2Provides deep architectural insights for long-term maintainability.
  • 3Ensures compliance and security with enterprise-grade features.

Frequently Asked Questions

+What kind of support does CodeRabbit offer?

We provide comprehensive documentation and a flexible API to assist all users in integrating and utilizing CodeRabbit effectively.

+Is there a free version of CodeRabbit?

Yes, CodeRabbit offers a free tier that allows users to experience the benefits without any initial investment.

+How does CodeRabbit ensure code security?

CodeRabbit emphasizes privacy by using ephemeral containers and does not retain LLM prompts, ensuring that your code is secure during reviews.