Basic RAG forces simple and complex questions through semantic search, often returning results in the wrong data shape as semantic chunks. If you have multiple data sources but focus on tuning just one retriever, the system may not always fetch the most useful document.

Join our technical session to learn how to give your agent specialized retrievers, so you can ask the right tool the right question and get the best response. Discover how a hybrid RAG pipeline answers questions about the structure of your data while reducing hallucinations.

Learn how to:

• Build a production-ready agentic system with multiple retrievers from a sample dataset
• Route semantic, computational, and relationship-based queries to the retriever built to answer them
• Implement an answer critic function to check whether your original question is answered correctly