The Scoring Model

Onboarding Score

A single 0–100% insurance-grade readiness number, computed from 5 weighted report types with causal explanations for every point gained or lost.

Onboarding Score Formula
25%
× Operational Readiness
+
20%
× Risk Causation (inverted)— inverted — lower risk = higher score
+
20%
× Warranty Protection
+
20%
× Evidence & Compliance
+
15%
× Asset Intelligence
= 100%
Interactive Band Demo — drag to explore
42%
Operational Control

Core systems are tracked and permits are on file. Evidence gaps remain — maintenance records, SOPs, and inspection reports need to be linked.

→Upload service records for critical systems
→Generate jurisdiction profiles
→Attach first inspection records
0%
Basic Awareness
26%
Operational Control
51%
Verified Operations
76%
Insurance-Grade Readiness
100%

The 4 Readiness Bands

Basic Awareness0–25%

Minimal data on hand. Asset inventory is incomplete or entirely AI-inferred. Insufficient for defensible underwriting position.

→Sync facility locations from GraphQL
→Run AI enrichment on permits
→Complete asset make/model/serial capture
Operational Control26–50%

Core systems are tracked and permits are on file. Evidence gaps remain — maintenance records, SOPs, and inspection reports need to be linked.

→Upload service records for critical systems
→Generate jurisdiction profiles
→Attach first inspection records
Verified Operations51–75%

Good evidence coverage across most assets. Approaching a defensible position. Some warranty gaps and SOP logs may still be missing.

→Complete SOP execution log documentation
→Resolve remaining warranty interval compliance
→Add media evidence (photos / IR scans)
Insurance-Grade Readiness76–100%

Full causal traceability, warranty proof, and compliance documentation across all critical assets. Ready for broker submission or policy renewal.

→Maintain evidence freshness (max_age_days compliance)
→Set automated obligation trigger reminders
→Export report snapshot for broker submission

Confidence Model

Every AI-generated record carries a confidence score (0–1). The threshold rules determine whether records auto-approve or enter the review queue.

confidence < 0.7
→ needs_review (human triage)
confidence ≥ 0.7
→ auto-approved (contributes to score)
human_verified = true
→ full weight in scoring
review_status = rejected
→ excluded from scoring
Get Your Onboarding Score →