Kilo Code Raises $8M Seed Round to Scale Open-Source AI Coding Agent Platform
Kilo Code, a San Francisco–based startup building an open-source AI coding agent platform, has raised $8 million in seed funding as it accelerates growth in the competitive market for AI-powered developer tools. The funding marks a key milestone for the company, which has gained rapid traction since launching earlier this year by focusing on speed, openness, and flexibility for engineering teams.
The seed round was led by Cota Capital, a venture firm known for backing early-stage infrastructure companies, with participation from Breakers, General Catalyst, Quiet Capital, and Tokyo Black. The round was anchored by Cota Capital and supported by investors including Breakers and General Catalyst, signaling strong confidence in Kilo Code’s vision for AI-native developer tooling.
Kilo Code was founded by Scott Breitenother, previously the founder of Brooklyn Data, and Sid Sijbrandij, co-founder and executive chair of GitLab. The founders bring deep experience in data platforms and developer ecosystems, shaping the company’s goal of removing friction from AI-assisted software development. Their approach emphasizes giving developers direct control over the tools and models they use, rather than locking them into closed systems.
Since its launch, Kilo Code has seen rapid adoption within the developer community. The company reports more than 750,000 downloads of its platform and a top ranking on OpenRouter, highlighting strong demand for model-agnostic AI coding solutions. Kilo Code says its platform now processes more than 6.1 trillion tokens per month and provides access to over 500 AI models, allowing developers to choose the best tools for specific tasks.
The platform integrates directly into widely used development environments, including VS Code, JetBrains IDEs, the command line, and cloud services. Its capabilities include AI-powered code generation and review, parallel agents that can run multiple tasks at once, one-click deployment, cloud-based agents, and managed indexing. These features are designed to help teams reduce context switching and move from idea to production more quickly.
Kilo Code positions its product as a solution to what it calls “AI drag,” referring to the slowdown developers experience when AI tools impose downgraded models, rate limits, or unclear pricing. By remaining open-source and model-agnostic, the company aims to preserve flexibility and transparency, enabling developers to work with a wide range of AI providers without changing workflows.
The newly raised capital will be used to accelerate product development, expand integrations with AI model providers, and scale operations to support a growing user base. Kilo Code plans to continue investing in features that support agentic engineering, where AI systems play an active role throughout the software development lifecycle, from writing and reviewing code to deployment.
Investor backing from firms such as Cota Capital, Breakers, and General Catalyst reflects a broader shift toward AI-native infrastructure for developers. With strong early traction, experienced leadership, and fresh funding, Kilo Code is positioning itself to become a meaningful player in the evolving landscape of AI-driven software development.
