A proprietary composite for factual grounding and semantic relevance in multi-modal LLM outputs—built for release gates, not vanity dashboards.
Pilot coverage
91%
Categories instrumented
Hallucination delta
-34%
Sampled agent evals
Monthly checks
12k+
Fidelity samples
Correlation
0.87
Internal gate model
Merchandising-grade quality scores do not predict whether an autonomous agent can safely cite a SKU. Teams need a defensible index that decomposes into explainable drivers auditors and merchants can act on.
CFI blends corroboration-aligned fidelity, semantic relevance to intent classes, coverage and freshness, and explicit conflict detection across supplier feeds, golden records, and policy text. Thresholds vary by agent use-case severity.
Operational as a gating signal for agent-eligible surfaces; regressions route to owners with driver-level explainability. Correlates with reduced hallucination incidents in pilot evaluations.
Signals
Scoring
Ops
Safety