By the time HR hears "I just got an offer", the conversation is already over. Bynarize PMS ships five purpose-built early-warning models — Performance Drift, Burnout Risk, Promotion Readiness, Hidden Talent and Recognition Gap — each consent-gated, each evidence-grounded, each writing into a unified AIInsight inbox with severity, top contributing factors and a recommended next action. And each is wireable into the Automation Engine: notify the manager, schedule a 1:1, raise a task, kick off a saga — without a human ever opening a queue.
Most people-analytics tools are dashboards looking for a question. Bynarize ships five purpose-built early-warning models with consent gates, severity scoring, contributing factors, recommended actions and direct wiring into the Automation Engine — so insights become actions, not slide decks.
Quarterly engagement survey + a vanity dashboard
Drift, burnout and flight risk discovered at the exit interview
Five daily/weekly models — Drift, Burnout, Promotion-Ready, Hidden Talent, Recognition Gap — with severity, contributing factors and recommended action
A "burnout score" computed from a survey
Survey is filled by people who aren't burnt out yet; the rest don't reply
BurnoutRiskAssessment from after-hours work + weekend signals + PTO-not-taken + meeting load + sentiment trend — consent-gated, evidence-grounded
Promotions decided in a closed-door committee
Bias creeps in; ready employees get missed; resentment compounds
PromotionReadinessAssessment scores competency coverage + behavioural indicators + bench depth — every cycle, every role, defensibly
Recognition flows to the loudest, never the quietest
Hidden talent leaves; org loses domain experts who never got noticed
HiddenTalentSignal uses collaboration graph centrality + cross-team mentions + skill embeddings — surfaces the quiet brilliant ones
Insights live in 5 dashboards nobody opens
Even when something is detected, nobody acts on it
Unified AIInsight inbox with severity sort, snooze, recommended action AND Automation Rule wiring — insight → action without a human opening a queue
"AI watching us" feels creepy — and DPDP/GDPR teams block rollout
Six months of legal review, then features get gutted to ship
Every model gated by per-employee ConsentRecord; revocation cascades to feature hide + data masking; full AIInteractionAudit per call
"Top performer" resigns on Monday — turns out the score has been drifting for 3 months.
PerformanceDrift compares snapshot windows daily, classifies sudden vs sustained vs recovering drift, and writes a severity-scored AIInsight with the contributing pillars and recommended action.
Burnout discovered at the exit interview, not at week 6.
BurnoutRiskAssessment runs daily on consenting employees; pulls after-hours work, weekend signals, PTO-not-taken, meeting load and sentiment trend; produces a 0–100 risk score with contributing factors.
"Why didn't we promote them?" — because nobody noticed they were ready.
PromotionReadinessAssessment scores competency coverage + behavioural indicators + bench depth + tenure + recent impact; surfaces a ranked list of ready-now employees per role and per cycle.
Quiet brilliant people leave because the loud ones get the recognition.
HiddenTalentSignal uses collaboration-graph centrality + recognition history + skill embeddings + cross-team mentions to surface employees with high impact and low visibility.
Same employee not recognised in 6 months — manager never noticed the drought.
RecognitionGapAlert reads EmployeeRecognitionAnalytics and flags systematically under-recognised employees by severity with a recommended action and one-click "send kudos" prompt.
Insights pile up across 5 dashboards and nobody acts on any of them.
All five models write into ONE unified AIInsight inbox with Acknowledge / Dismiss / Snooze actions. Each insight can trigger an Automation Rule — notify manager, schedule 1:1, create task, raise saga.
AI watching employees feels creepy — and DPDP/GDPR teams block rollout.
Every model is gated by ConsentRecord (BurnoutMonitoring, SentimentAnalysis, AIProcessing). If consent is missing, the feature is hidden — not just disabled. Employees control their Privacy Center end-to-end.
"Where did this prediction come from?" — silence.
Every prediction ships with top contributing features (from FeatureLineage), confidence band, and links to underlying signals. AIPrediction + AIInteractionAudit make every model decision auditable per employee.
Drift, burnout and disengagement signals are detected weeks before the LinkedIn update — turning regretted attrition into a manager conversation, not a goodbye email.
Every model checks ConsentRecord before running. No consent = feature hidden. Employees control their Privacy Center end-to-end. DPDP and GDPR teams sign off on day one.
Every insight has Critical / High / Medium / Low + recommended next action + a one-click path to act. No more "interesting chart, what now?".
All five models write to the unified AIInsight inbox. Managers see everything in one place — drift, burnout, promotion-ready, hidden talent, recognition gap.
Tenant-defined "if X then Y": "BurnoutRiskScore > 0.8 → notify manager + create 1:1 + raise HR task". From signal to action without a human opening a queue.
AIPrediction.Factors + FeatureLineage + AIInteractionAudit make every model decision explainable to the employee, the manager, HR, legal and the auditor.
Five focused early-warning models. One actionable inbox. Consent-gated, severity-scored, audit-ready — and wired straight into the Automation Engine so insight becomes action.