AI-powered employee wellness platform that predicts burnout before it becomes attrition, delivers personalized health programs, and gives managers the intelligence to act — without surveilling employees.
Sovereign AI identifies burnout risk patterns from work signals — communication cadence, focus time distribution, after-hours activity — without surveillance or keylogging. Risk scores update daily; managers see trends, not raw data.
Adaptive recommendations delivered to each employee based on their health signals and stated preferences. Mental health check-ins, physical activity nudges, and recovery practices are sequenced to fit their actual schedule.
Aggregate team health scoring gives managers a weekly view of department-level risk. Identify which teams are approaching capacity limits before the top performer submits a resignation letter.
WorkShrinker surfaces actionable recommendations for managers: which 1:1s to prioritize, what workload signals to address, and when to proactively offer flexibility — before an employee has to ask.
Enterprise plans connect directly to Workday, BambooHR, and ADP. Onboarding, role changes, and offboarding automatically update wellness context so the AI model stays current without manual data entry.
Employee health data is sovereign — processed locally, never sold, never shared with insurers or third-party brokers. Employees opt into programs voluntarily. Trust is the foundation, not a policy footnote.
WorkShrinker connects to your calendar, communication, and project management tools — with employee consent. No screenshots, no keylogging. Only aggregate work pattern signals.
The AI establishes individual and team-level health baselines over two weeks. Burnout risk is personal — the model learns what normal looks like for each employee before flagging deviations.
Personalized wellness recommendations arrive in each employee's inbox or Slack — micro-interventions timed to their actual work patterns. 5-minute practices with measurable engagement tracking.
Weekly team health reports surface rising risk scores and recommended actions. Managers get context, not surveillance data — the difference between coaching and monitoring.
Replace annual engagement surveys with continuous, real-time health signals. Intervene early on flight risks and present the board with retention data that's predictive, not retrospective.
Maintain throughput without burning out the team generating it. WorkShrinker tells you when departments are approaching capacity limits before delivery timelines slip.
Connect wellness program utilization to actual health outcomes. Demonstrate ROI to leadership with engagement metrics and turnover reduction data tied directly to program deployment.
No. WorkShrinker uses aggregate work pattern signals — meeting density, communication timing, focus block availability — not surveillance. Employees are never shown individual spying data because none is collected. The system flags patterns, not behavior.
Yes. Employees control their participation in wellness programs. Opting out removes their individual data from manager dashboards while keeping aggregate team health scores intact. Trust is built by design, not compelled by policy.
WorkShrinker connects to Google Workspace, Microsoft 365, Slack, Asana, Jira, and major HRIS platforms (Workday, BambooHR, ADP, Rippling). Custom API integrations are available on Enterprise plans.
Individual health signals are processed with sovereign local computation — aggregate scores reach manager dashboards but raw behavioral data never leaves the processing layer. No employee health data is sold to insurers, advertisers, or third-party brokers.
The baseline learning period is two weeks. After that, the burnout risk model operates with team-specific calibration. Most customers see their first actionable high-risk flags within 30 days of deployment.
Per-employee health intelligence. Sovereign data. No vendor surveillance.