This hands-on lab guides attendees through building a Retrieval-Augmented Generation (RAG) scenario using SAP HANA Vector Engine to ground generative AI responses in trusted enterprise data. Participants will work through a guided, end-to-end exercise that demonstrates how semantic search and vector-based retrieval improve accuracy, relevance, and explainability for AI-driven applications.

By attending, you will learn how to:

• Prepare and store vector embeddings in SAP HANA Vector Engine.

• Perform semantic search to retrieve contextually relevant enterprise data.

• Connect retrieved results to a generative AI workflow using RAG patterns.

• Evaluate how grounding improves response quality, trust, and usability in business scenarios.

This lab emphasizes practical implementation and leaves participants with a working RAG prototype they can adapt to real-world use cases across analytics, operations, and application development.