Y Combinator-backed startup brings AI to code reviews, helping engineering teams cut manual code review time and bugs by over 50%
SAN FRANCISCO, Calif. – AI might be great at helping engineers write code, but it’s creating a new problem – all that code still needs to be reviewed by humans. CodeAnt AI is stepping in with a solution that uses AI to tackle the review process itself, raising $2 million in seed funding to help engineering teams move faster without sacrificing quality or security.
The funding, CodeAnt AI’s first institutional round, values the company at $20 million. It will be used to expand the engineering and business development teams and to scale CodeAnt AI’s code quality and application security platform. For engineering teams already feeling the pressure to ship faster, the investment comes at the perfect time.
The funding round was led by Y Combinator, VitalStage Ventures, and Uncorrelated Ventures, and with participation from DeVC, Transpose Platform, Entrepreneur First, and a number of marquee angel investors.
“As AI-driven coding becomes widespread, the real bottleneck isn’t writing code — it’s reviewing it,” said Amartya Jha, Co-founder and CEO of CodeAnt AI. “Today, when a developer submits a change request, it often sits idle for hours or even days waiting for peer review. And even when a reviewer does pick it up, they rarely have full context of the code change. This is a critical risk point: most software bugs and vulnerabilities slip through at the peer review stage, where issues could have been caught early and cheaply.”
CodeAnt AI’s platform plugs right into GitHub, GitLab, Bitbucket, and Azure DevOps, giving developers instant feedback on their code across more than 30 programming languages. More impressively, it doesn’t just find problems – it suggests fixes that developers can apply with a single click, turning reviews that used to take hours into proactive quick, five-minute sessions. For companies racing to get products out the door, this means fewer delays and higher quality code. It also means cost savings – fixing problems during code reviews costs 10x less compared to fixing them later during CI/CD or after production deployments.
“We now have a new team member: CodeAnt AI. It sees our entire codebase in seconds, catches what linters miss, and suggests optimizations, refactors, even typos. It’s fully integrated into our on-prem GitLab — and the whole team adopted it instantly” said Michel Naud, Head of IT Solutions, Autajon Group. While, Sundaraman Venkataramani, Tech Lead at Motorq added:“At Motorq, speed, quality and precision are paramount. CodeAnt AI’s Agile team mirrors our fast-paced environment, delivering rapid iterations and responsive support. Their AI-driven code reviews, real-time feedback and robust security features have streamlined our development process allowing us to focus on core domain challenges. With CodeAnt AI, We’ve already been able to enhance code quality, security and are pushing our boundaries of innovation”.
The company was founded by Amartya Jha and Chinmay Bharti, who both saw the same problem from different angles. Jha worked on scaling infrastructure at Zeta and ShareChat, where he noticed how easily critical bugs slipped through when reviews weren’t thorough. Bharti, with a master’s specialising in AI from IIT Bombay, faced similar issues while building high-frequency trading software at Blu Analytics – where a single bug could have serious financial consequences. Together, they built CodeAnt AI and were accepted into Y Combinator.
What makes CodeAnt AI different is the technology under the hood. The company built a proprietary language-agnostic AST engine that actually understands how different parts of a codebase connect, letting it spot issues that isolated code reviews would miss. The platform also pulls in data from major security databases and lets companies set up their own rules based on their specific needs. For security-conscious organizations, CodeAnt AI can run entirely within their own infrastructure, ensuring code never leaves their environment.
“In today’s AI-driven environment, enterprises need solutions that either replace aging systems or deliver clear productivity gains,” added Amartya Jha. “CodeAnt AI is built to do both — helping companies move faster and stay competitive without compromising on security or code quality.”
Tom Blomfield, Partner at Y Combinator added: “With more and more code being generated by AI, code review has never been more important. CodeAnt fits into your CI/CD pipeline and ensures that only high-quality code makes it into production. Not AI-generated slop!”
Pricing starts at $10 per developer per month for the basic AI code review features, with a full package including code quality, security, and compliance tools available for $40 per developer per month.
As AI continues to transform how code gets written, CodeAnt AI is positioning itself as the bridge to a future where code can be both rapidly created and confidently deployed. The founders envision a world where AI doesn’t just help developers write code faster, but also ensures that every line shipped to production is secure, efficient, and ready for the real world – giving engineering teams the confidence to move at the speed their businesses demand.
Meanwhile, early investor at Hubspot Brian Shin, Managing Partner for VitalStage Ventures, commented: “CodeAnt AI is redefining one of the most critical — and often overlooked — parts of modern software development: the code review. In a world where AI is rapidly democratizing code generation, the bottleneck has shifted to validation. CodeAnt’s platform slashes review time by over 50%, ensuring not just speed, but quality, security, and reliability at scale. This leap forward empowers engineering teams to ship faster while catching issues earlier — a foundational advantage in today’s software-driven economy.”
