Natural language queries across your entire engineering dataset.
"Why did cycle time spike last sprint?"
"Which teams have the highest revert rates?"
"How does AI-assisted output compare across teams?"
Context-aware answers
Score code review quality on depth, thoroughness, and practicality. Keep your review bar high over time instead of letting it silently degrade.
Source-cited answers
Break down review volume by team member and week. Balance workload and keep reviews from piling up on your most senior engineers.
Uncover what dashboards miss
Track how many rounds of review each PR goes through. Identify bottlenecks and reduce the cycles that slow delivery.
Stop digging through dashboards
Ask the question, get the answer, and move on.