CodeRabbit, an artificial intelligence code review startup backed by Nvidia, raised $143 million in a new funding round valuing the company at $1.5 billion, according to the company's announcement.
The round comes as enterprises deploy AI systems to write code and face pressure to catch defects before deployment. CodeRabbit's platform identifies flaws in pull requests and flags potential bugs across repositories. Development teams previously handled this layer of quality control through human review alone.
CodeRabbit was founded in 2023 and had previously raised funding from Nvidia's venture arm alongside other investors. The company competes in a segment that includes GitHub's Copilot code review capabilities and other AI-native testing tools now attracting capital as engineering teams deploy large language models. Startups addressing gaps in AI-generated software quality have drawn venture backing as teams weigh productivity gains against reliability risks.
The new round values CodeRabbit at a multiple of more than 10 times its funding amount. The company has also announced plans to introduce an agentic change management layer that would allow the tool to not just identify defects but recommend or execute fixes autonomously, reducing developer friction in code review cycles.
CodeRabbit's funding comes as Nvidia's venture investments in AI software tools have moved across infrastructure and application startups in training, inference, and post-deployment quality assurance. Startups working on code quality and testing represent one component of the broader expansion in AI operations and monitoring since 2023.
The $1.5 billion valuation places CodeRabbit above many AI infrastructure startups that closed Series A or Series B rounds in 2024 and 2025. Code quality assurance now competes with model training itself for investor capital. The company's valuation relative to its funding amount shows investor confidence in solutions addressing downstream risks in AI-driven development.
The document to watch is CodeRabbit's next disclosure of customer adoption metrics and revenue run rate, which would show whether the market for AI code review has translated into paying demand at scale.
