A simple RAG (Retrieval-Augmented Generation) prototype is easy to build, but often fails in production due to complex documents, latency issues, or imprecise user queries. To make RAG systems truly "enterprise-ready", we must move beyond the standard approach. In this session, we dive deep into advanced RAG architectures within Microsoft Foundry that ensure performance, reliability, and scalability.

Key Takeaways
• Introduction to Multi-Query Generation, Re-Ranking, and HyDE to significantly improve search results
• Leveraging Graph RAG for enhanced semantic context and multi-hop reasoning
• The leap to Agentic RAG: Autonomous AI agents that dynamically decide when and how to retrieve information

Target audience:
Data Engineers, AI Engineers and Architects

Session duration:
45 minutes

Products:
Microsoft Foundry, Azure AI Search