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 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 watch?
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.
Speakers
Bryan Reinero
Principal Product Manager, MindsDB
Bryan Reinero drives product strategy for MindsDB's Open Source Federated AI Data Engine, which helps developers, data scientists and AI engineers build in-house AI with own data..
