AI architects know the pain: organizations’ data sprawls across warehouses, lakes, SaaS tools, and APIs—and your in-house AI can’t use it without heavy engineering. In this session, we’ll show how MindsDB Open Source, a federated data engine for AI, lets you run AI where the data lives—without moving or duplicating it—so teams can deliver real-time, production-grade capabilities faster.

You’ll learn how to:

• Plug LLMs and agents directly into live, distributed data via MindsDB’s federated query engine, avoiding brittle ETL and batch delays.

• Access hundreds of enterprise data sources using natural language, with handlers that translate questions into real-time queries.

• Deploy anywhere (local, containers, cloud) and integrate with existing stacks using open source.

• Enable real-time answers and natural-language queries inside your current applications and workflows.

Why attend?
If you’re building enterprise AI but stuck behind messy pipelines, stale data, and latency bottlenecks, this session gives you a practical, open-source path to real-time AI over federated data—so you can ship semantic search, copilots, and decisioning features in days, not months.