In 1970, Edgar Codd introduced the relational database model, transforming how we store and query data. Before that, programmers had to know exactly where data was stored and how to navigate complex file structures. Codd's innovation was making data access declarative - you describe what you want, not how to get it.

Today, RAG systems and Agentic AI have made great strides in natural language querying. But there's still room to make data access even more intuitive and conversational, and responses even more fast and contextual.

This session will cover building intelligent AI agents that can understand natural language queries with intent and context. We'll explore vector search and semantic caching with Redis, and show how these agents can deliver results at sub milli-second speeds.