Reporting That Says Something Specific About Your Team
Every entry categorized automatically, then aggregated into utilization, capacity, burnout signals and a workspace health score — with AI writing the narration, never the numbers.
Hours are only worth collecting if somebody can act on them. Stintt classifies each entry — meeting, focus, admin, break, time off — aggregates the period on the server, and uses AI to explain what moved. The figures are computed from real entries; the model narrates them, and says so explicitly when a week is too thin to draw a conclusion from.
Insights & reporting, in the concrete.
- Every entry classified automatically, and corrections are learned
- A workspace health score out of 100 with its inputs shown
- Capacity and burnout signals across the team
- 1:1 prep briefs summarizing a person's period before the meeting
- A meeting kill-list: the recurring meetings costing the most hours
- Scheduled email reports, so the numbers arrive without a login
Your team’s last 12 weeks, mapped.
+3 more teammates in the workspace
AI insight ·Mia’s meeting load is up for the third straight week — the recurring-meeting audit flags two candidates.
Illustrative sample2 features, one page each
Each has its own page: what it does, how it works, and which plan it sits on.
The things people ask before signing up
No. Every figure is aggregated server-side from actual entries. AI writes the sentences around those numbers, and refuses to characterize a period with too little data rather than inventing a trend.
Personal insight panels come with Pro. Team-wide surfaces — health score, capacity, 1:1 briefs and the meeting kill-list — are Workspace features.
There is no raw activity to see. Stintt has no screenshots, no app-and-URL log and no keystroke data. Managers see logged and approved time for the people their role covers.
