CodeAnt AI addresses the natural consequence of the AI coding boom: as writing code becomes faster and easier than ever, reviewing that code becomes the bottleneck. The company has built an agentic platform for AI code review and application security designed to give developers instant, actionable feedback on every change, helping teams maintain quality and security even as code volume explodes.
The platform is built for real-world engineering workflows. CodeAnt plugs directly into the major code hosts — GitHub, GitLab, Bitbucket, and Azure DevOps — so feedback arrives where developers already work, in the pull request. It supports more than 30 programming languages, making it viable for polyglot organizations with diverse codebases rather than a single-language tool.
CodeAnt's scope spans both code quality and application security. Beyond catching bugs, style issues, and maintainability problems, the platform functions as an agentic security layer, surfacing vulnerabilities and security anti-patterns during review. This combination targets the dual pressures modern teams face: shipping fast while keeping software secure, especially when much of the new code is AI-generated and may carry subtle flaws.
The company was founded by Amartya Jha and Chinmay Bharti, who built CodeAnt to make code review scalable in an era where humans can no longer manually review everything machines produce. By automating the first pass of review across quality and security dimensions, CodeAnt aims to let engineers focus their attention where human judgment matters most.
CodeAnt AI raised $2 million in seed funding at a $20 million valuation. The round was led by Y Combinator, VitalStage Ventures, and Uncorrelated Ventures, with participation from DeVC, Transpose Platform, Entrepreneur First, and several marquee angel investors. The capital supports the company's growth as automated, agentic code review becomes essential infrastructure for AI-accelerated development.