CodeRabbit AI

freemium

CodeRabbit is an AI-first pull request reviewer with context-aware feedback, line-by-line suggestions, and real-time chat. Trusted by 10,000+ teams. Try free.

Coding & Development

AI Coding Agents

Code Review Tools

About

CodeRabbit is the leading AI code review platform trusted by over 10,000 customers and used across 2 million repositories, having surfaced 75 million defects to date. It acts as an always-on reviewer that catches bugs, security issues, and code quality problems that humans commonly miss — without the noise of false positives. CodeRabbit works directly in the pull request workflow, offering line-by-line suggestions, PR summaries, architectural diagrams, and an interactive chat interface where developers can give natural-language feedback to refine future reviews. The platform pulls from 40+ linters and security scanners, integrates with Jira and Linear for issue context, and supports MCP servers for extended external context. Beyond reviewing, CodeRabbit can generate unit tests, create docstrings, run custom pre-merge quality checks, and produce automated standup and sprint reports. It is fully customizable through a YAML configuration file, allowing teams to encode their own coding guidelines and style rules. Reviews are also available directly in popular IDEs and via CLI — not just at the PR stage. With SOC 2 Type II certification, end-to-end SSL encryption, and a zero-data-retention policy post-review, CodeRabbit is architected for security-conscious engineering teams. It offers a free trial with no credit card required and scales from individual developers to enterprise organizations.

Key Features

Agentic PR Reviews: Automatically reviews every pull request with context-aware, line-by-line feedback, catching bugs and issues that human reviewers often miss.
Codebase Intelligence: Uses a codegraph and custom guidelines to understand complex file dependencies and surface the true impact of changes across the entire codebase.
Adaptive Learning: Learns from developer feedback given in natural language, continuously improving the quality and relevance of future code reviews.
Pre-Merge Checks & Code Generation: Runs custom quality checks, generates missing unit tests, and creates docstrings to ensure code is truly ready to ship before merging.
Multi-Environment Reviews: Reviews code at the PR stage, directly inside IDEs, and via CLI — fitting seamlessly into any developer workflow.

Use Cases

Engineering teams using GitHub or GitLab who want automated, high-quality code reviews on every pull request without slowing down development velocity.
Security-conscious organizations that need code review tooling with enterprise-grade compliance, encryption, and zero data retention guarantees.
Teams adopting AI coding tools (like Copilot or Cursor) who need a quality gate to catch errors introduced by AI-generated code before it merges.
Engineering managers who want automated standup reports, sprint reviews, and PR summaries to streamline team communication and visibility.
Open source projects or startups that need consistent code quality standards enforced across contributors without relying solely on human reviewers.

Pros

Deep Contextual Awareness: Pulls in dozens of context signals — linked issues, web queries, 40+ linters, and codebase graphs — for reviews that genuinely understand the change.
Fast, 2-Click Setup: Installs on GitHub or GitLab in two clicks with no credit card required, making onboarding extremely low-friction for teams.
Enterprise-Grade Security: SOC 2 Type II certified with end-to-end encryption and zero data retention post-review, suitable for security-sensitive organizations.
Highly Customizable: Teams can define their own coding standards, review styles, and custom pre-merge checks via a simple YAML configuration file.

Cons

Cost at Scale: Pricing for large engineering teams or enterprises can become significant, especially for organizations with many active repositories.
AI Review Limitations: While highly capable, AI reviews may still miss nuanced architectural decisions or domain-specific context that experienced human reviewers would catch.
Requires GitHub or GitLab: Native integration is built around GitHub and GitLab; teams using other VCS platforms may face limitations.

Frequently Asked Questions

CodeRabbit installs in two clicks on GitHub or GitLab and automatically begins reviewing pull requests. It also works in IDEs and via CLI, so it fits into your workflow at every stage of development.

Yes. CodeRabbit is SOC 2 Type II certified, uses end-to-end SSL encryption, and retains zero data after the review is complete, ensuring your code remains private.

Absolutely. You can define custom coding guidelines, style rules, path-based instructions, and pre-merge quality checks using a YAML configuration file. You can also train the AI with natural-language feedback directly in PR comments.

Yes, CodeRabbit offers a free trial with no credit card required. Paid plans are available for teams and enterprises that need more advanced features and higher usage limits.

CodeRabbit detects bugs, security vulnerabilities, code quality issues, and style violations using 40+ linters and security scanners, while filtering out false positives to reduce noise.