Qodo (Formerly Codiumai) Raises $40 Million Amid Strong Adoption of Its Quality-Focused AI Coding Platform

The platform enables enterprises to boost software development efficiency and enhance code quality by embracing AI-empowered coding, testing, and reviewing

Qodo (formerly CodiumAI), the generative AI code integrity platform, today announced $40 million in Series A funding, bringing the company’s total funding to $50M. The oversubscribed round was led by Susa Ventures and Square Peg, with participation from Firestreak Ventures, ICON Continuity Fund, and Seed investors TLV Partners and Vine Ventures. Just 18 months since exiting stealth, Qodo’s solutions have already been used by over 1M developers, and its enterprise platform has been adopted by industry leaders including multiple Fortune 100 companies.

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The software development landscape is undergoing a radical transformation, with widespread adoption of AI-powered coding solutions and massive investment in the space. With AI rapidly gaining capabilities in code generation, developers will shift towards high-level tasks like defining business logic and system design. This trend has sparked excitement but also heightens concerns about code quality and the lack of necessary safeguards for successful enterprise-level implementation. As more code is AI-generated, ensuring its reliability becomes even more critical to prevent potential bugs that could impact millions of users.

Qodo’s approach to AI-empowered software development places a strong emphasis on code quality and reliability. The company’s comprehensive platform seamlessly integrates agentic AI into the environments where developers work, including popular IDEs, git platforms, and CLIs. Qodo assists with intelligent code generation, testing, thorough reviews, and documentation, prioritizing quality throughout the development lifecycle. Qodo has quickly gained strong enterprise traction with thousands of teams using its solution worldwide. Enterprise sales crossed $1M in ARR within three months of launching its enterprise offering in March of this year. Further, Qodo was recognized by Gartner last month as a Cool Vendor in AI-Augmented Development and Testing for Software Engineering, and was accepted earlier this month into AWS’ Generative AI Accelerator.

“As we shift towards AI-native code development, success won’t come from rushing to automate everything,” said Itamar Friedman, CEO and co-founder of Qodo. “Instead, we need to carefully integrate AI tools to enhance human expertise, focusing on quality and adaptability rather than just speed. Through comprehensive testing and reviewing, embedded into each stage of the software development lifecycle, we will be able to rely on AI agents as an integral part of the team, dramatically reducing fear of bugs or hallucinations.”

“Recent outage events highlight the devastating potential of errors within software,” said Jenna Zerker at Susa Ventures. “This affirms that enterprises absolutely cannot risk embracing a high degree of AI autonomy in software development without having the proper validation and safeguards in place first. We invested in Qodo because they’re taking on code development from the necessary quality-first mindset. Their approach mitigates risks and improves the reliability of code, providing immediate ROI for enterprises while unlocking tremendous value in enabling agentic software development.”

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“AI agents play an increasingly pivotal role in software creation, and we believe a quality-first approach is key for their widespread adoption at the enterprise. Devs at the enterprise don’t ‘start from scratch,’ their code needs to work in harmony with tens of thousands of lines of code that are already there,” said Yonatan Sela at Square Peg. “The impressive grassroots adoption of Qodo paves the way for safer, more reliable AI-driven software development.”

Qodo’s traction comes on the heels of the release of its enterprise code integrity platform earlier this year. Central to Qodo’s enterprise solution is its advanced code analysis and indexing, using Retrieval Augmented Generation (RAG) techniques that enable context-aware code generation, testing and reviewing. Additionally, a dynamic best practices database enables adherence to each organization’s specific coding standards. The deep understanding of the unique context of each company’s code and knowledge of company-specific conventions, allows Qodo’s agents to provide more accurate, customized suggestions. Qodo’s enterprise platform also validates code correctness through an automated test-driven process where generated code is iteratively checked and fixed.

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