BerriAI / litellm
github.com·3d ago
Developer Tools
Databricks Blog·Sep 1·5 min read
How the FDA is building a secure, AI-ready data foundation on Databricks for Government
TL;DR
The FDA is modernizing its data platform using Databricks to create a secure, AI-ready environment that meets stringent regulatory requirements. This initiative aims to enhance public health decision-making while ensuring compliance and speed to value.
✦ Why It Matters
Evaluate your current data infrastructure to ensure it meets compliance and security standards for AI deployment.
Key Takeaways
- Implement a secure, governed data foundation for AI workloads.
- Focus on stakeholder engagement throughout the modernization process.
- Adopt flexible configurations to support evolving needs.
- Utilize cloud environments designed for regulated workloads.
Full Summary
The FDA's modernization effort addresses the challenges of siloed data and operational inefficiencies that hinder its regulatory mission. By implementing HALO (Harmonized AI and Lifecycle Operations for Data) on Databricks, the agency has established a secure, governed data foundation that supports AI workloads.
Key milestones included achieving FedRAMP High authorization, migrating to AWS GovCloud, and adopting Unity Catalog for data governance. This transition allowed the FDA to onboard over 6,000 users and consolidate more than 40 data sources, resulting in a 30% improvement in query response times and a 20% reduction in compute costs.
The FDA's approach emphasizes responsible AI use, integrating AI tools to enhance, not replace, human expertise in regulatory processes. Overall, the modernization has streamlined operations and improved collaboration across the agency.