Qodo is rolling out AI-driven governance tools to ensure code quality, security, and compliance as AI-generated code moves into production more rapidly than human review can handle.

Beyond generation, Qodo offers end-to-end verification and governance, acting as a reliability layer that enforces security and standards in AI-assisted coding.

The latest funding round was oversubscribed and led by Qumra Capital, with participation from Maor Ventures, Phoenix Venture Partners, S Ventures, Square Peg, Susa Ventures, TLV Partners, Vine Ventures, and notable angels from OpenAI and Meta.

The investment underscores strong enterprise appetite for AI code-verification tools, backed by a roster of strategic backers from both VC and tech leadership.

Proceeds will support expansion of Qodo’s global enterprise operations, scaling engineering and product teams, and accelerating hiring at its Tel Aviv office.

Qodo is already collaborating with major enterprises and tech leaders such as NVIDIA, Walmart, Red Hat, Intuit, Texas Instruments, and high-growth firms like Monday.com and JFrog.

The company has raised a total of $120 million with a $70 million Series B led by Qumra Capital, building AI agents for code review, testing, and governance.

Qodo, based in New York, emphasizes its Series B as a milestone toward deploying agents for code review, testing, and governance across leading development ecosystems.

Qodo 2.2 introduces context engineering and a multi-agent review system that leverages full-repository signals to improve code evaluation.

Qodo has demonstrated performance leadership, ranking first on Martian’s Code Review Benchmark with an F1 score of 64.3%, and recently launched Qodo 2.0 with a multi-agent code review approach.

The platform analyzes broader repository effects and enforces organization-specific standards using historical decisions to guide AI-driven code governance.

Founder Itamar Friedman stresses that code generation and verification require different tools, incorporating internal context and standards beyond what a general LLM can provide.