Qodo is releasing Qodo 3.0, the next generation of its AI Code Quality and Governance Platform, expanding its quality infrastructure to enterprises building agentic software factories, automatically connecting agent workflows to enterprise codebase knowledge, architectural standards, and governance requirements.
According to Qodo, as enterprises build software factories that orchestrate agents across the software development lifecycle, many organizations are struggling to maintain quality and governance at the pace agents now produce code. Qodo 3.0 addresses this by injecting quality controls throughout the agentic SDLC, guided by Qodo’s Wisdom Base that provides agents with a continuously updated understanding of an organization's codebase, standards, architecture, and pull request history.
“Every enterprise will build its software factory around its own systems, tools, and ways of working,” said Itamar Friedman, CEO and co-founder of Qodo. “That factory becomes trustworthy when agents can draw on the organization’s accumulated knowledge and operate within its standards.”
With Qodo 3.0, quality is embedded into code generation before a pull request exists by surfacing an organization's coding standards into an agent's workspace and running Qodo's review engine on code before it is committed, Qodo said.
Once an agent's pull requests reach review, Qodo’s PR Triage groups them into a single work package, giving a reviewer visibility into everything the task touches and its priority relative to other work. A reviewer can claim a work package to establish ownership and prevent duplicate review.
Governance and codebase quality can be monitored and risk-assessed with the Qodo Software Map, which automatically maps an organization's repositories, calculates the blast radius of a proposed change, and surfaces quality issues as a heat map across the architecture.
Qodo 3.0 supports enterprise engineering teams wherever they run, including Gerrit, newly added alongside GitHub, GitLab, Bitbucket, and Azure DevOps, a full on-premises or air-gapped deployment with the Context Engine and Agentic Toolbox inside the perimeter, and open-source model support, including Nemotron, so review can run on models hosted inside a customer's own infrastructure.
Qodo 3.0 becomes the quality control layer engineering teams need to trust the agentic SDLC, from the code an agent generates to the pull request it opens.
For more information about this news, visit www.qodo.ai.