CodeRabbit bags $143M to help companies get a grip on the explosion of AI-generated code
SiliconANGLE Mike Wheatley ● Covered by 3 sources
CodeRabbit just raised $143M to expand beyond AI code review. Now it wants to sort, explain and police code changes from humans and bots alike.
Based on reporting by SiliconANGLE, Mike Wheatley — read the original for the full story.
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CodeRabbit has pulled in $143 million in Series C funding and is using the moment to push past its original job: checking AI-generated code for mistakes as it is written.
The new money was led by Atomico and Smash Capital. BMW i Ventures, Datadog, Hirtle Callaghan and SineWave Ventures also joined in, along with existing backers CRV, Scale Venture Partners, Flex Capital and Pelion Venture Partners. The round even drew angel investors from senior ranks at Apple and Amazon.
Until now, the company’s pitch was pretty simple. Let its AI agents inspect freshly generated code in real time and catch syntax errors, logic bugs and security issues before developers move on. Useful, yes. But CodeRabbit argues that the rise of AI-native development has changed the problem entirely. Code is no longer coming only from software engineers. Product managers, designers, marketers, background agents and even support or observability systems can now generate pull requests, and teams are getting buried before they can decide what matters.
So the company is launching Agentic Change Management, a broader control layer for governing and prioritizing change. Harjot Gill, CodeRabbit’s co-founder and chief executive, says every change now creates a decision for the team. The new layer is built to validate incoming pull requests using repository-wide context and sandboxed test environments, while the existing review system keeps hunting for defects.
There are three pieces to the new setup. CodeRabbit Triage scores each pull request for value, dependencies, urgency, risk and reviewer fit, then routes the high-stakes ones to humans and the low-risk ones to automation. CodeRabbit Change Stack swaps out plain file lists for a view of how a change affects domain behavior, system dependencies and integration risk. CodeRabbit Security scans whole repositories, keeps watching after code ships and can send recommended fixes back through the pull-request loop if it spots logic vulnerabilities in production code.
My take — AI-written commentary, not fact-checked reporting
This is the right move, and also a sign of how messy AI coding has already gotten. If every team member, agent and dashboard can fire off code, then a simple review bot is basically a smoke alarm in a warehouse fire. The real product now is control, not just correction.
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