Qodo, a startup specializing in AI-powered code review, testing, and governance, has raised $70 million in a Series B funding round led by Qumra Capital. The fresh capital brings the company's total raised to $120 million, positioning it as a frontrunner in the rapidly growing code verification market.
The round also saw participation from Maor Ventures, Phoenix Venture Partners, S Ventures, Square Peg, Susa Ventures, TLV Partners, and Vine Ventures. Notable individual investors include Peter Welender of OpenAI and Clara Shih of Meta.
The investment comes at a time when AI coding tools are generating billions of lines of code every month, raising urgent questions about software reliability and security. Qodo aims to serve as a trust layer for AI-generated code as enterprises rapidly adopt tools like OpenClaw and Claude Code. Many companies are finding that faster code production does not automatically mean safer or more dependable software.
A recent industry survey underscores the problem: while 95% of developers say they do not fully trust AI-generated code, only 48% consistently review it before pushing it into production.
How Qodo Works
Unlike most AI review tools that focus on what changed in a code commit, Qodo analyzes how changes affect entire systems. The platform takes into account organizational coding standards, historical context, and risk tolerance to deliver more accurate and relevant code reviews.
CEO and founder Itamar Friedman told TechCrunch that code generation companies are largely built around large language models, but LLMs alone are not enough for code quality and governance. He emphasized that quality depends on each organization's internal standards and institutional knowledge — factors a general AI model cannot fully understand on its own.
Benchmark-Topping Performance
Qodo recently claimed the number one position on Martian's Code Review Bench with a score of 64.3%, finishing more than 10 points ahead of the nearest competitor and 25 points ahead of Claude Code Review. The benchmark tests a tool's ability to detect complex logic bugs and cross-file issues without generating excessive false positives.
The company also launched Qodo 2.0 in the past month — a multi-agent code review system — along with new tools that learn each organization's specific definition of code quality.
Founder's Background
Friedman founded Qodo in 2022, months before the launch of ChatGPT. His career path uniquely prepared him for this venture. At Mellanox, which was later acquired by Nvidia, he worked on automating hardware verification with machine learning and concluded that generating systems and verifying them are fundamentally different disciplines requiring different tools.
He previously co-founded Visualead, an Israeli startup acquired by Alibaba. During his time at Alibaba's research academy, he observed AI moving toward the ability to reason over human language, convincing him that AI would eventually produce a large share of the world's code — and that verification would need its own dedicated infrastructure.
Major Enterprise Clients
Qodo has already secured a strong enterprise footprint. Its client roster includes NVIDIA, Walmart, Red Hat, Intuit, and Texas Instruments, as well as high-growth technology companies like Monday.com and JFrog.
Industry Context
Friedman noted that while companies like OpenAI and Anthropic are shaping the broader AI narrative, including in adjacent areas like code review, they remain focused on building features rather than delivering end-to-end verification solutions. He added that other startups in the space are still largely in early stages and have yet to achieve widespread enterprise adoption.
What's Next
Friedman described the current moment as a turning point for the industry. He sees a shift underway from stateless AI to stateful systems — from raw intelligence to what he calls "artificial wisdom" — and said Qodo is built specifically for this new era.
With $120 million in total funding, top benchmark performance, and a growing list of major clients, Qodo appears well-positioned to define the future of AI code verification at a time when the industry needs it most.
