We'll show you exactly how AI is impacting your speed and code quality.




Developer satisfaction surveys run twice a year and tell you sentiment, not outcomes. Whether your platform actually moved cycle time and deployment frequency stays unmeasured.
A new internal tool launches. Three teams pilot. Six months later, nobody can tell you who's on the golden path and who's still on legacy.
Infrastructure cost is a line item. Whether that investment translated into faster delivery, fewer incidents, or better developer experience is a question Finance keeps asking and platform can't answer.




Tag teams or repos with custom labels (golden path, legacy, hybrid) using Hivel's team configuration. Compare delivery metrics across labeled cohorts to see where adoption correlates with cycle time, deployment frequency, and rework improvements.
Both. Every dashboard supports team-level scoping, so the platform team gets the same delivery health view as product teams. Useful for measuring the platform team's own throughput, review coverage, and sprint accuracy.
Yes. The AI Impact view supports per-tool breakdowns. See adoption depth, AI code percentage, and delivery metrics for each tool side by side. Useful when running AI tool pilots across different teams or evaluating renewal decisions.


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See exactly how AI-assisted code is impacting your delivery speed and code quality, before you commit to anything.
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