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Square Peg joins $70m series B for AI code review startup Qodo
Qodo, a software firm that builds tools for automated code review and governance, has raised US$70 million in a series B round led by Qumra Capital, bringing its total funding to US$120 million, the company said.
Other investors in the round included Maor Ventures, Phoenix Capital Partners, S Ventures, Square Peg, Susa Ventures, TLV Partners, and Vine Ventures.
Qodo said the rise of AI coding agents has increased the volume of machine-written code and shifted the bottleneck to code review and code quality.
The company said it will use the new funding to scale its enterprise platform, including features it describes as a multi-agent review system, a context engine that learns from a codebase and pull request history, and a rules management layer for internal standards.
🔗 Source: Qodo
🧠 Food for thought
Implications, context, and why it matters.
The funding follows significant enterprise and developer traction
- Qodo hit US$1 million in annual recurring revenue three months after launching its teams offering 1.
- More than 1 million developers use the product, helped by a freemium plan that includes 30 free pull request reviews per month on the Developer tier 2.
- The company calls its product a “quality layer” that checks code written with other AI tools, including code generators like GitHub Copilot 1.
- Gartner named Qodo a Visionary in the 2025 Magic Quadrant for AI Code Assistants 3.
AI’s coding boom creates a new market for quality control
- Qodo’s funding tracks a second-order effect of generative AI. More AI-written code moves the bottleneck from creation to review and governance [summary].
- That shift opens space for AI governance tools that sit alongside code generators and apply an organization’s security and compliance rules through automated reviews and standards checks 3.
- At monday.com, Qodo flags over 800 potential issues each month, which supports wider use of AI-generated code while keeping risk in check 3.
- The developer tools market is moving toward agent-driven workflows where one AI writes code, then another AI validates it, instead of focusing only on code completion 3.
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