CodeRabbit has launched its AI-driven code review functionality as a free feature within widely used code editors like Visual Studio Code, Cursor, and Windsurf, aiming to address the growing need for quality checks amid the rapid rise of AI-generated code.
The company, which has been developing automated code review tools using AI for the past two years, is now making its services directly available to developers at no cost. This marks a notable pivot from its original enterprise-centric focus to supporting individual users on the ground.
This rollout comes at a time when software teams are experiencing both the benefits and challenges of AI development tools. While productivity is soaring thanks to systems like GitHub Copilot, the resulting surge in code output has created new vulnerabilities and quality concerns that manual review processes can’t keep up with.
“Code reviews are the last fully manual component of the CI/CD pipeline, and they’re often a bottleneck,” said Gur Singh, CodeRabbit’s COO and co-founder. “By embedding our AI tools directly in the development environment, we’re closing that gap right at the point of creation.”
Solving Quality Challenges Introduced by AI Coding
In a recent discussion with The New Stack, CodeRabbit CEO Harjot Gill explained why integrating with IDEs is a natural evolution. With 75,000 active users already on board, the company has identified a widespread issue: AI-generated code is efficient, but not always accurate or secure.
“The AI tools generating code today are not flawless,” Gill said. “We saw an opportunity to use AI not just to write code but to ensure its quality as well.”
With tools like Copilot and Cursor becoming standard among developers, code generation is happening faster — but without effective safeguards, security flaws and logic errors often slip through. CodeRabbit is positioning its AI to act as a second layer of protection, filling in those oversight gaps.
Unlike rule-based code checkers, CodeRabbit provides feedback that mimics a human reviewer. Its system offers insights into intent, style, performance, and security practices, adapting to the context of the code rather than relying solely on static patterns.
According to analyst Michael Azoff at Omdia, this approach is resonating in the market. He noted that the combination of advanced language models and seamless IDE integration gives CodeRabbit a competitive edge, even as it faces off against tech giants that have added similar tools to their platforms.
Boosting Efficiency With Layered Review
CodeRabbit reports that its platform can reduce the time developers spend on code reviews by 60–70%. This is especially helpful for senior engineers, who often handle complex architecture and security checks.
Gill emphasized that while AI handles the more routine aspects of code review, human reviewers still have a role in higher-level oversight. “The AI filters out the common issues, allowing humans to focus on what really matters — understanding architectural decisions or product-specific logic,” he explained.
This forms a two-tier review approach: developers first run AI checks locally, then submit their code for peer review as part of the team workflow on platforms like GitHub.
Freemium Approach to Drive Adoption
Offering the tool for free within editors is part of a broader growth strategy. The company hopes that widespread use among individual developers will eventually lead to enterprise adoption for full CI/CD pipeline integration.
“This is our version of a freemium model,” Gill said. “We’re giving developers a powerful tool for free to build awareness and create pull for broader team-based deployments.”
So far, the strategy seems effective. CodeRabbit is seeing rapid growth, with a 30–40% monthly increase in both users and revenue. Gill describes the company as focused on addressing the challenges that have emerged from the first wave of AI-assisted coding.
Standing Out in a Crowded Market
Despite competition from established platforms like GitHub and AWS, CodeRabbit believes it stands apart due to its architectural design and deep technical features. The platform’s use of agent-based processing and sandbox environments is central to its differentiation.
Gill likens CodeRabbit’s role to that of best-of-breed tools in other areas of software infrastructure. “It’s the same pattern you’ve seen with companies like Datadog and Snowflake,” he said. “We’re not just another feature — we’re a purpose-built system with depth.”
As AI continues reshaping how software is built, CodeRabbit’s push into developer tools signals a growing demand for intelligent systems that can keep code quality in check. With code generation accelerating, having real-time AI review embedded in the development process could soon become a standard part of every developer’s workflow.
