Behavioral Trend & Retention Engine
Dynamic daily retention risk scores, cohort-level risk clustering, and early-warning alerts — HRIS-integrated and updated continuously.
Retention Risk Heatmap
Input signals
- Behavioral metadata streams
- Chemistry score shifts
- Sentiment trend data
- Manager interaction frequency
- Tenure and compensation context from HRIS
What RUDY surfaces
- Daily retention risk score per employee
- Cohort risk clustering map
- Early-warning threshold alerts
- Flight risk trend by team/function
- Regrettable attrition probability
Sample AI output
Alex M. (Senior Engineer) shows a 73% retention risk signal — 3 consecutive low-engagement weeks, reduced 1:1 participation, and 2 missed recognition events. Early warning: 6 weeks before a resignation would surface in exit interview data.
How it works
BTRE aggregates signals daily
Behavioral metadata, chemistry score shifts, sentiment trends, manager interaction frequency, and HRIS tenure/compensation data are aggregated into daily retention risk calculations.
Cohort clustering identifies systemic risks
BTRE clusters employees by risk profile to identify systemic patterns — a department under management strain, a cohort with unmet career expectations — before individual attrition occurs.
HR receives threshold alerts before retention events
When cohort risk or individual risk crosses a configurable threshold, HR receives a structural intervention recommendation 4–8 weeks before a resignation would otherwise surface.
A day with RUDY
“HR sees a retention risk heatmap across 5 departments. Sales has 3 employees at 70%+ risk. Engineering shows a cohort risk pattern suggesting workload strain — not individual performance. BTRE's early alerts fire 6 weeks before a resignation would otherwise appear in exit interview data.”
Research foundation
Organizational turnover research, predictive attrition modeling, and HR systems integration.
Frequently asked questions
See RUDY AI in action.
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No surveillance. No black-box scoring. Human review where it matters.