How Databricks AI Agents Reach Production

Most enterprises recognize the potential of AI agents - but getting them to production is where initiatives stall. Accuracy gaps, limited model flexibility, and the security risks of sending critical data to external systems are the most common blockers. Databricks takes a different approach: tailoring AI agents directly to enterprise data and use cases, with research-backed techniques to continuously measure and tune performance without rebuilding from scratch. See how customers are running these agents in production today: Banking: Multi-agent systems securely review investment theses and generate memos - saving 200,000 hours and delivering $250 million in value. Energy: Agents combine real-time grid, meter, and weather data to predict disruptions before they occur - enabling 25% faster power restoration and $18 million in annual outage cost savings. Healthcare & Life Sciences: AI agents predict how drug molecules impact gene expression, accelerating disease biology research and supporting the design of new treatments. The result: higher accuracy, continuous improvement, and AI agents that actually make it to production. Learn more at databricks.com/solutions/ai-agents