Qodo Unveils Top Deep Research Agent for Coding, Outperforming Leading AI Labs on Multi-Repository Benchmark

Qodo Aware Deep Research achieves 80% accuracy on new coding benchmark, surpassing OpenAI’s Codex at 74%, Anthropic’s Claude Code at 64%, and Google’s Gemini CLI at 45%

Qodo, the agentic code quality platform, announced Qodo Aware, a new flagship product in its enterprise platform that brings agentic understanding and context engineering to large codebases. It features the industry’s first deep research agent designed specifically for navigating enterprise-scale codebases. In benchmark testing, Qodo Aware’s deep research agent demonstrated superior accuracy and speed compared to leading AI coding agents when answering questions that require context from multiple repositories.

AI has made generating code easy, but ensuring quality at scale is now even harder. Modern software systems span hundreds or thousands of interconnected code repositories, making it nearly impossible for developers to maintain a comprehensive understanding of their organization’s entire codebase. While current AI coding tools excel at single-repository tasks, they cannot traverse the complex web of dependencies and relationships: the 2025 State of AI Code Quality report found that more than 60% of developers say AI coding tools miss relevant context. Qodo Aware addresses this limitation with a context engine that powers deep research agents that can automatically navigate across repository boundaries.

“Developers don’t typically work in isolation, they need to understand how changes in one service affect systems across their entire organization and how those systems evolved to their current state,” said Itamar Friedman, co-founder and CEO of Qodo. “Our deep research agent can analyze impact, dependencies and historical context across thousands of files and hundreds of repositories in seconds, something that could take a principal engineer hours or days to trace manually. This eliminates the traditional speed-quality tradeoff that enterprises face when adopting AI for development, while adding the crucial dimension of understanding not just what the code does, but why it was built that way.”

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Qodo Aware features three distinct modes, each powered by specialized agents for different use cases. The Deep Research agent performs comprehensive multi-step analysis across repositories, making it ideal for complex architectural questions and system-wide tasks. For quicker code Q&As, the Ask agent provides rapid responses through agentic context retrieval, and the Issue Finder agent searches across repos for bugs, code duplication, security risks, and other hidden issues. These agents can be used to get direct answers, or integrated into existing coding agents, like Cursor and Claude Code, as a powerful context retrieval layer, enhancing their ability to understand large-scale codebases.

Qodo Aware uses a sophisticated indexing and context retrieval approach that combines Language Server Protocol (LSP) analysis, knowledge graphs, and vector embeddings to create deep semantic understanding of code relationships. For enterprises, this means developers can safely modify complex systems without fear of breaking unknown dependencies, reducing deployment risks and accelerating release cycles. Teams report cutting investigation time for complex issues from days to minutes, even when working across massive, interconnected codebases with more than 100M lines of code.

Along with these capabilities, Qodo is releasing a new multi-repository dataset for evaluating coding deep research agents. The dataset includes real-world questions that require information that spans multiple open source code repositories to correctly answer. On the new DeepCodeBench benchmark, Qodo Aware achieved 80% accuracy, while OpenAI Codex scored 74%, Claude Code reached 64%, and Gemini CLI correctly solved 45%. Importantly, Qodo Aware Deep Research took less than half the time of Codex to answer, enabling faster iteration cycles for developers.

Qodo Aware has been integrated directly into existing Qodo development tools – including Qodo Gen IDE agent, Qodo Command CLI agent, and Qodo Merge code review agent – bringing context to workflows across the entire software development lifecycle.. It is also available as a standalone product accessible via Model Context Protocol (MCP) and API, enabling integration with any AI assistant or coding agent. Qodo Aware can be deployed within enterprise single-tenant environments, ensuring code never leaves organizational boundaries, while maintaining the governance and compliance standards enterprises require. It supports GitHub, GitLab, and Bitbucket, with all indexing and processing occurring within customer-controlled infrastructure.