Retrospective AI
Retrospectives that write themselves from your team's actual data, recurring themes flagged, action items tracked.
Retrospective AI drafts your retro from what actually happened in the sprint (items, blockers and comments) so the meeting starts at insight instead of recollection.
Auto-extracted themes
Discussion topics are clustered from real sprint signals, with sample quotes to keep them honest.
Recurrence detection
Themes that come back sprint after sprint are flagged, so systemic problems stop hiding.
Action items that stick
Every retro action is tracked to done, and a 0–100 sprint health score shows whether things are actually improving.
The retro drafts itself from what actually happened.
Retrospective AI analyzes a sprint's real history (items, blockers, comments, metric signals) and drafts the retrospective before the meeting starts: clustered themes with evidence, a health score, and action items that are tracked to completion.
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