Most modern enterprise systems already have a rich backbone of structured relational data — but the explosion of AI and LLMs brings a new challenge: how to make these two worlds work together. This session explores practical architectural patterns for combining SQL Server (or any RDBMS) with AI/ML workloads to build smarter, data-aware applications.
We’ll cover how to bring AI capabilities close to your data, how to keep systems consistent when mixing vector search, embeddings, and traditional queries, and how to architect for performance, cost efficiency, and governance. From hybrid query flows to enrichment pipelines and caching strategies, this session is designed for developers, data engineers, and architects who want to infuse AI without ripping out their existing data foundations.
By the end, attendees will understand key integration approaches, gotchas, and patterns to future-proof their data architecture in an AI-first world.