Transform structured review data into calibrated, bias-aware, leadership-ready decisions. Combine narrative intelligence, rating normalization, trajectory modeling, and defensible documentation in one unified system.
Generates complete review narratives from actual performance data - goals achieved, feedback received, check-in history, and OKR progress. Managers cut review writing from 8 hours to 30 minutes while improving quality and consistency.
Continuously scans written narratives and rating patterns for linguistic bias, recency distortion, halo/horn effects, and inflation tendencies - supporting equitable and defensible performance decisions.
System identifies rating distribution anomalies per manager, highlights inconsistencies between scores and goal data, and recommends data-backed calibration adjustments to support consistent, defensible decisions.
Data-driven trajectory modeling highlights early signals of performance risk or acceleration based on historical review and goal data. Identify declining trajectories early, surface the factors most correlated with improvement, and feed predictions into succession planning.
Every review automatically generates a personalized Individual Development Plan. AI maps skill gaps to specific learning resources, suggests stretch assignments, and tracks progress over review cycles. Shifts performance reviews from retrospective evaluation to forward-looking capability development.
Auto-generate personalized review letters with mail-merge style templates. Include performance data, increment details, development plans, and manager commentary. Structured communication workflows with digital acknowledgment tracking.