CodeRabbit closed a $143 million Series C funding round at a $1.5 billion valuation and launched Agentic Change Management, a control layer designed to help product and engineering teams govern code written by both humans and AI agents. The company also committed more than $10 million to keep its AI code review tools free for open source projects over the next 12 months.
The round was co-led by Atomico and Smash Capital, with participation from BMW i Ventures, Datadog, Hirtle Callaghan, SineWave Ventures, Scenic Management, and existing investors. Atomico partner Luca Eisenstecken joins CodeRabbit's board.
"As AI becomes critical infrastructure for the global economy, organisations will increasingly need independent governance layers that can validate software regardless of which model produced it," Eisenstecken said. "CodeRabbit's independent review system and deep contextual understanding position it as the control layer for agentic software development."
The funding comes less than a year after CodeRabbit's $60 million Series B. Revenue grew more than 5x year-over-year as engineering teams adopted independent review and governance tools for AI-generated code. CodeRabbit now runs more than 2 million code reviews per week and serves more than 17,000 customers, including Adyen, BMW, Indeed, JFrog, NVIDIA, and Trivago.
How AI is changing software engineering
Traditional issue tracking systems like Jira assumed that teams would plan and prioritize work before any code existed. Engineering time was scarce, so managers curated a backlog of requests before assigning work to developers.
AI-native development flips that sequence. Developers, product managers, designers, background agents, issue trackers, and support tools can all generate code or open pull requests at any time. Code can exist before a team has agreed on priorities. The backlog is shifting from tickets to proposed code.
This pushes triage, planning, and governance downstream to the pull request. That moment becomes the auditable decision point where teams decide whether a change meets quality standards, how much risk it introduces, and whether it should ship.
"Code changes now originate across the software organization, including from developers and non-technical personnel as well as from coding agents," said Harjot Gill, co-founder and CEO of CodeRabbit. "We extended AI code review to give teams an independent system for validating work. Agentic Change Management expands that system to determine what deserves attention, explain each change's impact, and continue monitoring the codebase after it ships."
The platform for Agentic Change Management
CodeRabbit's Agentic Change Management turns the pull request into a central system for review, prioritization, explanation, and ongoing monitoring.
CodeRabbit Triage scores incoming pull requests by value, urgency, risk, dependencies, and reviewer fit. It routes high-risk changes directly to human reviewers, sends low-risk work into automated workflows, and filters out duplicate or unready changes.
CodeRabbit Change Stack replaces the standard alphabetical file listing with a guided view of contracts, domain behavior, integrations, tests, and migrations teams. Blast-radius and architecture analysis show how a change affects the larger system.
CodeRabbit Security extends the review layer beyond merge. It runs full-repository scans and continuous monitoring to find vulnerabilities in production code, verified findings, and sends fixes back through the pull request process.
CodeRabbit Security addresses new vulnerability risks
Large language models lower the cost and expertise needed to discover software bugs, letting defense and attackers rapidly examine more code and test more attack paths.
CodeRabbit Security uses a proprietary codegraph system fine-tuned for advanced review. It maps code bases into trust boundaries and reasons across the entire repository to identify vulnerabilities that static rules cannot express, including authorization bypasses, insecure direct object references, and business-logic flaws.
"Security now requires a continuous system that can reason across the repository, verify whether a threat is real, and move the fix back through the development workflow," said Brad Twohig, Founding Partner at Smash Capital.
Why this matters for product development
Product developers are now responsible for code that originates from multiple sources - human engineers, coding agents, support tickets, even monitoring alerts - often before the team has agreed verification or priority. CodeRabbit's Agentic Change Management turns the code review tool into a decision system that manages the traffic, explains impact, and watches production code for risk is opened automatically. For teams that already use generative code tools, this closes the loop when the source of change is no longer a single person but a steady stream of AI-generated proposals that require a repeatable governance that doesn't slow shipping.
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