Uzera

Uzera is an AI agent control platform designed to provide governance, visibility, and standardization for engineering teams using multiple coding agents. It addresses challenges such as unclear AI spend, inconsistent code quality, lack of context for agents, and the risk of vendor lock-in by serving as a governance layer across various agents, including Claude Code, Cursor, Copilot, Windsurf, and any agent compatible with the MCP standard.

The platform enables teams to set and enforce rules and policies that agents must follow, with quality gates and security standards checked before code is committed. Uzera indexes codebases locally, ensuring that only structured metadata is sent off-machine, and agents receive precise context rather than entire repositories, reducing token usage and associated costs. It provides dashboards that attribute token spend, track agent activity, and present compliance data, allowing leaders to connect AI investment to measurable outcomes. Audit logs are maintained for governance and compliance, mapping every agent action to controls and enabling exportable evidence.

Uzera supports any programming language, framework, or repository, and is designed to work with the agents teams already use, without requiring source code to leave the developer's machine. Its features include codebase indexing and retrieval, pre-commit and pre-push hooks, cost attribution by agent, repository, and task, and unified dashboards for monitoring code quality, agent actions, and ROI. The platform is aimed at roles such as CTOs, engineering managers, staff engineers, developer experience and platform teams, application security, and financial operations, each benefitting from its unified governance, compliance automation, and cost transparency.

Setup involves scanning repositories to build a structured codebase map, retrieving context for agent requests, running governance rules at the agent level before commits, and shipping compliant, context-aware code. Uzera is positioned as a control plane for AI-assisted coding, ensuring that standards and knowledge persist across agent vendors and that teams can maintain consistency, security, and cost control as they scale AI development.