In this session, Satej will explore how integrating graph data and relationships can enhance Retrieval-Augmented Generation (RAG) models by improving data validation from multiple sources. The session will cover different implementation patterns for RAG and introduce a framework that employs multi-agent integration to gather and validate data through their relationships. Key Takeaways: – Understand the basics of RAG and its applications – Learn about the challenges of data validation in RAG models – Explore the role of graph data and relationships in enhancing RAG – Demonstrate a framework for multi-agent integration in RAG – Best practices and lessons learned from real-world implementations – Gain practical insights into leveraging graph technologies to improve data accuracy and validation in their AI and ML projects.

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