Qodo Secures $70M to Tackle AI Code Reliability
3 min read
As AI coding tools churn out massive amounts of code every month, a new challenge is taking center stage: making sure that code actually works. That’s where Qodo is stepping in, positioning itself as a key player in the next phase of software development.
The New York-based startup has raised $70 million in a Series B funding round led by Qumra Capital, pushing its total funding to $120 million. The round also saw participation from investors like Square Peg, Susa Ventures, TLV Partners, along with notable individuals such as Peter Welender and Clara Shih.
The Growing Problem With AI-Generated Code
AI-powered coding assistants are transforming how software is built, but speed comes with trade-offs. While tools like Claude Code and OpenClaw can generate code quickly, they don’t always guarantee reliability or security.
Qodo is betting that verification—not generation—will define the future of AI-driven development.
Instead of just reviewing what changed in a codebase, Qodo’s AI agents analyze how those changes impact the entire system. This includes factoring in company-specific standards, historical decisions, and risk tolerance—elements often overlooked by traditional tools.
Built on Real-World Experience
The company was founded in 2022 by Itamar Friedman, who previously co-founded Visualead and led machine vision efforts at Alibaba.
Friedman’s experience at Mellanox—later acquired by Nvidia—played a key role in shaping Qodo’s vision. He observed early on that generating systems and verifying them require completely different approaches.
As AI evolved, especially around the time of ChatGPT, Friedman saw a clear shift: AI would soon produce a large share of the world’s code. That realization drove him to build tools focused on trust and verification.
A Gap Between Trust and Practice
Recent data highlights a major disconnect in the industry. While 95% of developers say they don’t fully trust AI-generated code, only 48% consistently review it before deploying. This gap creates significant risks for companies relying heavily on AI tools.
“Code quality isn’t just about correctness—it’s contextual,” Friedman explained. “It depends on internal standards, past decisions, and team knowledge. That’s something generic AI models struggle to fully understand.”
Standing Out in a Competitive Space
While companies like OpenAI and Anthropic are advancing AI capabilities, they are mostly focused on building features rather than complete verification systems.
Qodo is differentiating itself through performance. The startup recently ranked No. 1 on Martian’s Code Review Bench, scoring 64.3%—well ahead of its competitors. Its system is designed to catch complex bugs and cross-file issues without overwhelming developers with unnecessary alerts.
The company also recently launched Qodo 2.0, a multi-agent review system that adapts to each organization’s definition of code quality.
Enterprise Adoption Already Underway
Qodo is already working with major organizations, including NVIDIA, Walmart, Red Hat, Intuit, and Texas Instruments. It also partners with fast-growing tech firms like Monday.com and JFrog.
The Next Phase: From AI to “Artificial Wisdom”
According to Friedman, the AI industry is entering a new stage—moving beyond simple automation toward systems that understand context and make smarter decisions.
“Every year has had a breakthrough moment—from Copilot to ChatGPT,” he said. “Now we’re shifting from stateless AI to stateful systems—from intelligence to what we call ‘artificial wisdom.’”
With fresh funding and growing enterprise demand, Qodo is betting that trust, not just speed, will define the future of AI-powered development.
