CodeHealth™ analysis shows in minutes where AI coding can safely be applied today. Measure and track impact. Prove ROI.
Enable CodeHealth MCP in any AI workflow to automatically safeguard AI-generated code and prevent technical debt.
Fix unhealthy code first and make it AI-ready. Use the MCP server to guide improvements, and validate progress with the CodeHealth™ metric.
Unhealthy code undermines AI-assisted development. AI error rates increase by 2–5x in problematic code, eroding the benefits of automation. Organizations that want safe and effective AI-assisted development must invest in Code Health as a foundational capability.
Code Health™ scores predicting AI performance. At least 60% defect risk when AI works on unhealthy code.
The CodeHealth metric is a validated, research-based metric and the industry’s only code-level metric with proven business impact, linking low code quality to higher defect rates and slower development speed.
AI performance depends on code quality. Healthy code:
Code Health™ scores predicting AI performance. At least 60% defect risk when AI works on unhealthy code.
Keep AI-generated code healthy, automatically. The CodeHealth™ MCP Server runs real-time checks and guides agents as you code. Model-agnostic, secure, and built for your workflow.
Scale AI coding without accumulating technical debt. The AI Performance Framework shows where AI will fail, safeguards AI-ready areas, makes legacy code AI-ready, and tracks impact across your projects.
CodeScene identifies and prioritizes high-impact technical debt to accelerate delivery and reduce defects. The CodeHealth™ metric makes progress visible as a shared KPI.
Enforce change with automated CodeHealth™ Reviews. They act as both quality gate and coach, preventing new technical debt without slowing teams down.
Shift left with real-time CodeHealth™ feedback in the IDE. Identify risks early and prevent technical debt from entering your codebase.
“At Carterra we reduced unplanned work by 82% over a twelve-month period thanks to CodeScene.”