Qodo、AIコーディング拡大に伴いコード検証で7000万ドルを調達
AIによるコード生成が普及する中、Qodoはコード検証の重要性に着目し、7000万ドルの資金調達に成功した。
キーポイント
AIコード生成の課題
AIが大量のコードを生成するようになったが、そのコードが実際に動作するかどうかの検証が新たな課題となっている。
Qodoの事業戦略
Qodoはこの課題に対応するため、コード検証技術に特化し、7000万ドルの資金調達を実施した。
市場のニーズ
AIによるコード生成のスケール拡大に伴い、コードの品質保証と信頼性確保への需要が高まっている。
影響分析・編集コメントを表示
影響分析
この記事は、AIによるコード生成が一般的になる中で、生成されたコードの信頼性確保が次の重要な課題となることを示している。Qodoの資金調達成功は、投資家がこの分野の成長可能性を認識している証左であり、AI支援開発ツール市場の成熟段階への移行を示唆している。
編集コメント
AIコード生成ツールの普及に伴い、生成コードの品質管理が次の大きなビジネスチャンスとなる可能性を示唆する重要なニュース。投資動向から市場の成熟度が読み取れる。
AIがソフトウェア開発に大量のコードをもたらす中、Qodoは真の課題は、そのコードが実際に機能することを保証することだと見据えています。
原文を表示
As AI coding tools generate billions of lines of code each month, a new bottleneck is emerging: ensuring that software works as intended. Qodo, a startup building AI agents for code review, testing, and governance, is betting that verification will define the next phase of software development.
The New York-headquartered startup has raised a $70 million Series B round led by Qumra Capital, bringing its total funding to $120 million. Maor Ventures, Phoenix Venture Partners, S Ventures, Square Peg, Susa Ventures, TLV Partners, Vine Ventures, Peter Welinder (OpenAI), and Clara Shih (Meta) also joined in the round.
Qodo is aiming to serve as a layer focused on improving trust in AI-generated code as enterprises accelerate adoption of tools like OpenClaw and Claude Code. Many are discovering that faster code output doesn’t necessarily translate into reliable or secure software.
While most AI review tools focus on what changed, Qodo focuses on how code changes affect entire systems, factoring in organizational standards, historical context, and risk tolerance to help companies better manage AI-generated code more confidently.
Itamar Friedman, who previously co-founded Visualead and led the machine vision business at Alibaba (which acquired Visualead), founded Qodo in 2022. He told TechCrunch that two key moments in his career — his time at Mellanox, which was later acquired by Nvidia, and building Visualead — inspired him to start Qodo, just months before the launch of ChatGPT.
At Mellanox, where he worked on automating hardware verification using machine learning, he realized that “generating systems and verifying systems require very different approaches (different tools, different thinking).” Later, at Alibaba’s Damo Academy, he saw AI evolve toward systems capable of reasoning over human language. By 2021-2022, just ahead of GPT-3.5, it became clear to him that AI would generate a large share of the world’s content — especially code — reinforcing his view that code generation and verification would require fundamentally different systems.
A recent survey shows that while 95% of developers don’t fully trust AI-generated code, only 48% consistently review it before committing, highlighting a gap between awareness and practice.
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“Code generation companies are largely built around LLMs. But for code quality and governance, LLMs alone aren’t enough,” Friedman said. “Quality is subjective. It depends on organizational standards, past decisions, and tribal knowledge. An LLM can’t fully understand that context. It’s like taking a great engineer from one company and asking them to review code at another — they lack the internal context.”
Companies such as OpenAI and Anthropic are helping shape the broader AI narrative, including in adjacent areas like code review, but they are largely focused on building features rather than end-to-end solutions, Friedman explained. Although there are other startups in the space, many remain early-stage and have yet to see widespread enterprise adoption, the CEO noted.
Qodo is leaning into performance to stand out in a crowded market. The startup recently ranked No. 1 on Martian’s Code Review Bench, scoring 64.3% — more than 10 points ahead of the next competitor and 25 points ahead of Claude Code Review. The benchmark highlights its ability to catch tricky logic bugs and cross-file issues without overwhelming developers with noise.
In the past month, it has launched Qodo 2.0, a multi-agent code review system now leading current benchmarks, and introduced tools that learn each organization’s definition of code quality.
The company is already working with major enterprises such as Nvidia, Walmart, Red Hat, Intuit, and Texas Instruments, as well as high-growth firms like Monday.com.
“Every year has had a defining moment — from Copilot to ChatGPT to full task automation,” Friedman said. “Now we’re entering a new phase: moving from stateless AI to stateful systems — from intelligence to ‘artificial wisdom.’ That’s what Qodo is built for.”
Kate Park is a reporter at TechCrunch, with a focus on technology, startups and venture capital in Asia. She previously was a financial journalist at Mergermarket covering M&A, private equity and venture capital.
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