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FOR ENGINEERING MANAGERS

Know which teams thrive with AI — before they tell you.

Some teams ship 2x more with AI. Others burn licenses. Scout shows you which is which — and what high-performing teams do differently.

Talk to an Expert

FOR ENGINEERING MANAGERS

Know which teams thrive with AI — before they tell you.

Some teams ship 2x more with AI. Others burn licenses. Scout shows you which is which — and what high-performing teams do differently.

For CTOs - Export-3

Talk to an Expert

What You Can See

Deep visibility into how AI is working across your teams
— without micromanaging.

Team-level Drill-downs

Compare adoption, velocity, quality, and cost per team with 2-level deep breakdowns. See which teams are thriving and which need support.

Bottleneck Detection

See where delays shifted post-AI.
Coding time may be down, but has the bottleneck moved to review or testing? Scout surfaces the shift.

Sprint Intelligence

AI-attributed ticket data shows which work types benefit most from AI assistance.
Focus AI investment on high-impact areas.

From Signals to Action

Ask a question, get an investigation. Scout walks you through the data to find answers, not just charts.

Comparing Team Adoption Patterns

Platform team: 82% active AI users, avg 4.2 sessions/day. Mobile team: 34% active users, avg 0.8 sessions/day.

 Gap: 2.4x adoption difference 

Analyzing Productivity Correlation

Platform: cycle time down 28%, PR throughput up 45%. Mobile: cycle time down 4%, PR throughput flat. Strong adoption-velocity correlation.

High adopters: 5.8x more velocity gains

Checking Root Cause Signals

Mobile team survey: "AI tools don't support Swift well" (72%), "No time for setup" (58%). Platform team had structured onboarding.

Barrier: Tooling fit + onboarding gap

Recommendation
Targeted Enablement for Mobile

Mobile team has low adoption due to language support gaps and missing onboarding.
Recommend: add Claude Code (strong Swift support), replicate Platform’s onboarding playbook.
Projected impact: +35% CAT gain within 60 days.

Recommendation
Targeted Enablement for Mobile

Mobile team has low adoption due to language support gaps and missing onboarding.
Recommend: add Claude Code (strong Swift support), replicate Platform’s onboarding playbook.
Projected impact: +35% CAT gain within 60 days.

Lead with data, not intuition.

See which teams are getting real value from AI — and help the rest catch up.