Medetective gives payers, providers, and regulators a single, adaptive lens on claims activity—pinpointing anomalous patterns, flagging suspect encounters in real time, and recommending cost-optimized benefit designs.

By combining OLAP-grade slice-and-dice with machine-learning detection models, it helps the healthcare ecosystem protect funds, improve plan value, and strengthen public trust.

Integrates structured and unstructured claims data from clearinghouses, EMRs, and payers into a single analysis-ready warehouse.

Learns typical claim behavior by provider, specialty, and region to flag outliers in frequency, amount, or coding pattern.

Augments ML findings with configurable business rules for known fraud patterns like upcoding, phantom billing, and unbundling.

Triggers alerts as suspicious claims enter adjudication, enabling pre-payment investigation and faster recovery.

Investigators can explore claim clusters, provider networks, and historical patterns through intuitive, drill-down dashboards.

Analyzes reimbursement variance, service utilization, and population health trends to recommend value-based benefit designs.

FHIR/HL7-compliant APIs, role-based access, and full audit logging ensure HIPAA, GDPR, and SOC2 compliance.