CodeRabbit has closed a $60 million Series B financing round led by Scale Venture Partners with NVentures (NVIDIA’s venture capital arm) and returning investors CRV, Harmony Partners, Flex Capital, Engineering Capital, and Pelion Venture Partners also participating.
This latest funding brings CodeRabbit’s total funding to $88 million and adds Andy Vitus from Scale Venture Partners to the company’s board. The new capital will be used to hire engineers and product experts around the world, accelerate the development of new features, and expand the platform’s reach across developer toolchains.
As software teams embrace AI coding assistants, developers can generate snippets and entire functions almost instantly. That speed has created a new challenge: code is appearing faster than it can be checked for errors, security flaws, or style inconsistencies. Traditional reviews often involve waiting in a queue, hunting through pull requests, and manually switching contexts—slowing down delivery and undermining the benefits of AI-driven coding.
CodeRabbit addresses these delays by weaving context-aware AI code reviews directly into the tools engineers already use. Whether someone is working in a terminal, inside their favorite editor, or on a Git hosting site, CodeRabbit’s engine analyzes the code, references past changes and architectural notes, and delivers actionable feedback in real time. This seamless approach prevents errors from slipping into production without interrupting a developer’s flow.
The adoption of CodeRabbit has skyrocketed. Revenue has grown tenfold over the past year, and the headcount doubled in less than three months, with plans to double again by early 2026. More than 8,000 companies—including well-known names like Chegg, Groupon, Life360, and Mercury—now pay for the service. Over 100,000 open source projects also rely on CodeRabbit, making it the top–ranked AI application on the GitHub Marketplace.
Building on this momentum, CodeRabbit’s newest release brings AI-powered reviews into the command line interface, complementing existing integrations in integrated development environments and Git platforms. The company is also rolling out pre-merge checks that automatically suggest unit tests and enforce custom rules before code ever reaches a pull request. Later this year, a richer context client will become generally available, pulling in requirements documents, design diagrams, and ticketing system entries to give the AI even more insight into what each code change is intended to accomplish.
Under the hood, CodeRabbit relies on a context-driven engine that draws intelligence from multiple sources. It inspects code graphs to understand how different modules interact, reviews historical pull requests to learn common patterns, and references project documentation to align feedback with architectural goals. By combining machine learning with human-verified guidelines, the system can spot subtle bugs, suggest safer refactorings, and highlight security weaknesses that might otherwise go unnoticed.
CodeRabbit’s integrations span every stage of the development lifecycle. Engineers can invoke reviews directly in a terminal session, see inline comments in editors such as Visual Studio Code, Cursor, or Windsurf, and track review summaries in GitHub, GitLab, Azure DevOps, or Bitbucket. The platform also works alongside AI coding agents—whether it’s Cursor, Claude Code, or GitHub Copilot—creating a continuous loop of code generation, review, and refinement without forcing developers to switch contexts.
How the funding will be used: With this new funding, CodeRabbit plans to strengthen its global teams, deepen its AI capabilities, and bring its review technology to even more development environments. As software projects grow in complexity and teams lean on AI to keep up, CodeRabbit’s seamless, context-rich code review layer promises to let organizations move faster and more safely than ever before.
KEY QUOTES:
“CodeRabbit has emerged as the clear leader in AI code reviews, acting as the governance layer AI development desperately needs. They’ve built a code review system that works well even for large codebases while delivering the accuracy and rigor of a senior engineer.”
Andy Vitus, Partner at Scale Venture Partners
“AI-generated code is here to stay, but speed without a centralized knowledge base and an independent governance layer is a recipe for disaster. Code review is the most critical quality gate in the agentic software lifecycle, and you have to build AI agents that are context-aware so they can catch the bugs that are hardest to find. That’s exactly what we’ve built, and we are excited to partner with Scale Ventures given their pedigree in the AI dev tools space.”
Harjot Gill, co-founder and CEO of CodeRabbit
“CodeRabbit, one of the first to adopt GPT-5, is harnessing the model’s industry-leading reasoning capabilities to deliver state-of-the-art AI code reviews validated by their own benchmarks. As software teams generate more code than ever, code review solutions like CodeRabbit’s are critical to keep up the pace of shipping code.”
Shyamal Anadkat, Head of Applied Evals at OpenAI
“Groupon looked toward AI coding tools to speed up its feature delivery cycles in every aspect of the software lifecycle. After adopting CodeRabbit, our average code review-to-production time came down from a whopping 86 hours to just 39 minutes, greatly speeding up our release cycles.”
Tomas Zaruba, Technical Manager in the CEO’s office at Groupon
