Concerned about data privacy or compliance? Don’t want your sensitive information sent to external AI systems? This session is for you!

We’ll explore retrieval-augmented generation (RAG), a method to enhance large language models (LLMs) with your specific, ever-changing data, without it ever leaving your systems.

You’ll learn:

What is a vector database?
How can you vectorize your own data?
How to integrate your existing data sources, like SQL databases, to enrich AI interactions.
We’ll implement RAG step-by-step, running AI models locally (on the “edge”) while maintaining full control over your data. By the end of the session, you’ll know how to build an AI assistant that uses your private and volatile data, all without relying on external cloud services.

Stay compliant, stay secure, and build AI solutions that fit seamlessly into your systems—on your terms.