Detect Burnout Risks


Agentic tasks
Calibrated personal baseline & thresholds
Completed
Completed
Completed
In progress
Solved problems

Fewer Absences
Avg.

-2.9
days
-22%

Earlier Detection
Avg.

3.2
weeks
+78%

Lower Attrition
Avg.

−3.1
pts
−18%
How it works:
Multisignal model: Blends workload patterns, quiet-hour breaches, micro-recovery gaps, and sentiment trends; learns personal + cohort norms.
Explainable & actionable: Surfaces top drivers (e.g., back-to-back meetings, weekend pings) with safe levers and one-click fixes.
Agentic control loop: Sense → explain → act (reschedule, nudge, resources) → review outcomes; auto-tunes alerting to cut noise.
Policy & privacy first: Consent-based scope, HR policy engine, minimal content processing, aggregation/differential privacy, clear audit.
Native to Teams: Uses chat nudges, calendar rebalancing, Viva/HRIS/EAP hooks — no new tools; manager prompts stay compliant and consistent.