AI-Driven Fraud, Waste, and Abuse (FWA) Detection System Development

The contract seeks development and deployment of an AI-driven analytics platform designed to identify fraudulent, wasteful, and abusive billing patterns within Medicaid programs operating under both fee-for-service and managed care models. The system must integrate seamlessly with the Georgia Department of Community Health’s existing data infrastructure to analyze claims data in real time, detect anomalies, and flag suspicious activity with high accuracy. The platform is expected to leverage machine learning algorithms trained on historical Medicaid datasets to uncover complex fraud schemes that traditional rule-based systems may miss, improving detection speed and reducing false positives. The subcontract is open for response until May 25, 2026, and falls under NAICS code 541512, indicating it is for computer systems design and related services. Performance of the work is expected to occur within Georgia, aligning with the agency’s operational scope. The project underscores a strategic effort by the Department of Community Health to modernize its oversight capabilities through advanced technology, aiming to protect public funds and ensure program integrity. Contractors must demonstrate technical expertise in AI model development, healthcare data integration, and compliance with state-specific data governance protocols.