From 0 to 100: how protected is your catalogue from AI? The PartSentinel Score is a composite weighted across three pillars — Reality Gap, Inference Risk, Competitive Visibility — calibrated by vertical, computed deterministically, and reported alongside its industry benchmark. Exact pillar weights and per-vertical calibration are disclosed inside the signed audit dossier under NDA.
A score of 27 places you in the Vulnerable band. Industry median for automotive aftermarket is 42.
The PartSentinel Score aggregates three pillars. Each pillar is derived from one or more of the six metrics — AI Visibility, Reality Gap, Inference Risk, Competitive Share of Answer, Substitution Risk, Category Authority. Exact weights are disclosed under NDA.
Reality Gap measures every divergence between AI output and your ground-truth catalogue: invented equivalences, approximate compatibilities, obsolete information, technical hallucinations. Memory errors weigh more than web-grounded errors — they are permanent.
Inference Risk is our key differentiator. Memory-track exclusive. The worst case: low Reality Gap + high Inference Risk — AI makes few errors but correctly reconstructs your secrets. No competitor measures this.
Competitive Visibility combines Share of Answer and Category Authority. Available with zero client data. Reveals where you win, where competitors capture demand, where you're invisible.
A score on its own is opaque. The five bands give you a one-glance read of where your catalogue sits — and what action it warrants.
The score is deterministic given the same audit inputs. No retroactive re-weighting, ever.
SentinelScore = Σ ( w_i × verdict_points_i ) where i ∈ { identification, cross_ref, application, spec, procedural }
verdict_points = { ok: 95, warn: 55, bad: 20, leak: 5 }
audit.score = mean( score_per_ref_per_model ) over the audit panel
weights w_i (per vertical, immutable per rubric_version):
Exact values are withheld — see "Anti-gaming" pillar below.
Cross-reference carries the highest single weight (commercial-IP signal).
Customers receive their full weights table inside the signed audit
dossier, under NDA.
per-section verdict logic:
identification = SKU + EAN + reference id + brand match
cross_ref = public crossrefs valid AND no internal codes leaked
application = vehicle / engine / year-range fit
spec = numeric values within ±2% tolerance
procedural = install / torque / safety notes complete
vertical calibration:
each rubric_version is cryptographically signed and immutable
rubric_id is stamped on every report so customers can replay any audit
methodology table available under NDA at /docs/methodology