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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