Sort metrics into input, quality, and outcome

Sort each metric into the layer it actually monitors for an AI data product. Input health Data quality Model performance Business outcome Source table updated before the 7 a.m. scoring job All required upstream feeds arrived with no schema drift Critical customer segment field is less than 3 percent missing Duplicate account records stay below the agreed threshold High-risk recommendations are correct often enough for the workflow Predicted confidence matches observed outcomes by risk band Frontline users act on the recommendation within the target window Average triage cycle time drops after the AI workflow launches

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