Frequently Asked Questions
Find answers to common questions about SmartScore MQI, how our AI-assisted monitoring works, and what to expect when you start a pilot.
SmartScore MQI™ is an AI-assisted monitoring framework that translates complex KPI environments into a deterministic quality index and explainable diagnostics. It helps organizations monitor performance, detect drift, and identify outliers—while keeping humans in control of final decisions.
No. SmartScore MQI adds a translation and monitoring layer on top of your existing dashboards. It normalizes KPIs into a consistent scoring language so AI can monitor performance across cohorts and time windows.
AI identifies deviations, cohort drift, or anomalies and drafts recommendations. A human reviewer approves alert escalations, ticket creation, or recalibration updates. This ensures governance, accountability, and operational oversight.
Traditional dashboards show metrics. SmartScore MQI translates heterogeneous KPIs into a structured performance index and AI-readable diagnostics, enabling explainable monitoring rather than static reporting.
A cohort pilot is a limited-scope engagement where a defined dataset (e.g., locations, teams, customer segments, or time windows) is evaluated using SmartScore MQI. The pilot demonstrates scoring calibration, drift detection, and explainable insights before broader rollout.
Pilot timelines vary depending on data readiness and KPI complexity. Most engagements begin with a discovery session, followed by calibration and reporting within a defined evaluation period.
SmartScore MQI supports:
Service performance benchmarking
Operational health monitoring
Experience and quality scoring
Release validation and rollout assessment
Executive performance reporting
Data is handled securely and, where required, under a non-disclosure agreement (NDA). Access controls, governance processes, and evidence trails support responsible monitoring.