The GraphRAG Manifesto: Unlock Better GenAI Results With Knowledge Graphs | Read Now
Dev Conference by Neo4j
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Session Track: AI
Session Time:
Session description
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.
Senior Software Data Architect, The Boeing Company
Satej works as Senior Software Data Architect at Boeing with over 14 years of experience in the industry. He has worked with renowned organizations such as adidas, Honeywell specializing in architecture, big data and machine learning use cases. With a strong track record of architecting scalable and efficient systems, Satej has successfully delivered data-driven and ML applied solutions.