AI Impact
Measure AI's impact on your engineering team.
Track adoption, productivity gains, and code quality from AI coding tools like GitHub Copilot, Cursor, and Claude Code.
Adoption Tracking
See who's using AI tools and how
Track AI coding tool adoption across your team. Understand usage patterns, adoption curves, and power users.
- Per-developer AI tool adoption rates
- Usage frequency and patterns
- Tool-by-tool comparison
Adoption Tracking
Productivity Impact
Quantify AI's productivity boost
Measure the actual impact of AI tools on cycle time, throughput, and developer velocity.
- Before/after AI adoption metrics
- AI-assisted vs. manual PR comparison
- Time savings estimation
Productivity Impact
Team Alpha1.8d
Team Beta3.2d
Team Gamma2.4d
Team Delta4.1d
Quality & Safety
Ensure AI code meets your standards
Monitor whether AI-generated code maintains your quality bar through review patterns and bug rates.
- AI-generated code review patterns
- Bug rate in AI-assisted PRs
- Security scan results for AI code
Quality & Safety
Improved
On track
Needs attention
38%
PRs with AI assistance
2x
Faster coding with AI tools
< 1%
Difference in bug rate