Grounding Is the Product: Where Enterprise AI Answers Fail
Most enterprise answer-system failures are grounding failures wearing a generation costume. Measuring grounding separately changes how you fix systems.
Blame the right layer
When an answer is wrong, ask first: was the right evidence supplied to the model? In our audits, the majority of failures are grounding failures — missing sources, wrong sources, or right sources ranked below the context budget. Optimizing the generator before fixing grounding is polishing the paint on a cracked wall.
Corpus engineering is real engineering
A corpus needs owners, freshness policy, coverage metrics and review. How knowledge is segmented and indexed is a modeling decision with measurable consequences. Treat the corpus like a product and answer quality stops being a mystery.
Measure in layers
Report evidence recall@k and citation precision separately from answer quality. Layered metrics tell you where to invest next week; a single 'answer score' tells you nothing actionable.
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