Join us at the upcoming Databricks DMV User Group meeting to explore modernizing government fraud prevention and inter-agency collaboration. Public sector benefit programs face growing challenges in detecting complex fraud schemes across fragmented systems while maintaining tight data security, privacy, and regulatory compliance. In this session, we will examine how a unified data and AI lakehouse architecture can serve as a foundation for real-time risk assessment, cross-agency data sharing, and AI-driven investigative workflows.

We'll walk through the architecture, emerging field patterns, and a practical demonstration showcasing how organizations can move from reactive, manual review processes to automated anomaly detection. Learn how technologies like Delta Sharing and Databricks Clean Rooms enable secure, zero-copy data collaboration across agency boundaries, and see how AI-assisted agent interfaces can help analysts, investigators, and legal teams synthesize complex evidence, preserve data lineage, and accelerate time-to-insight. Whether you are focused on improving audit readiness, streamlining eligibility verification, or advancing your agency's data strategy, this talk offers practical architectural blueprints and takeaways for public sector data and AI practitioners.