For VP Engineering & CTOs

Prove AI ROI to your board — with data, not anecdotes.

Your company spends $50K+/month on AI coding tools. Scout quantifies the return — velocity gains, quality impact, and dollar ROI — so you can make data-driven investment decisions.

Is Our AI Investment Paying Off?

ROI quantification across tools and teams. See exactly which tools deliver value, which teams benefit most, and where spend can be optimized.

Are We Accumulating Tech Debt Faster?

Code turnover monitoring with red-flag thresholds. Track whether AI-generated code sticks or gets rewritten within days, weeks, or sprints.

How Do We Compare to Industry?

Benchmarks from 500+ engineering teams. Know whether your AI adoption, velocity gains, and quality metrics are above or below industry norms.

Analyzing AI Adoption Trends

Copilot acceptance rate up 18% over 90 days. Claude Code sessions up 3.2x since rollout.

Adoption Strong

Correlating with Velocity Metrics

Cycle time down 22%. PR throughput up 31%. Coding time reduced but review time increased 15%.

Velocity: Net positive, constraint shifted

Checking Quality Indicators

Code turnover rate stable at 8.2%. Bug-fix ratio unchanged. No regression in code quality metrics.

Quality: No degradation

For VP Engineering & CTOs

Prove AI ROI to your board — with data, not anecdotes.