Epic’s predictive models aim to enhance clinical decision-making beyond traditional scores like SIRS and MEWS. To foster clinician trust, ECU Health is deploying continuous AI monitoring through Microsoft Fabric’s comprehensive analytics. This involves integrating diverse data sources from Epic’s databases into a semantic model, which feeds into Fabric notebooks, culminating in a user-friendly AI monitoring dashboard. This solution enables robust analytics with daily dataflows, adaptable definitions per clinical; operational; and quality needs, and ongoing performance comparisons with traditional clinical scores. Power BI, enhanced with Python visuals, offers performance comparison plots and extensive filtering by different populations, facilitating user-friendly, no-code analysis and updated threshold selection overtime. The AI monitoring dashboard supports model validation, encourages AI adoption, and ensures continuous monitoring post-deployment.