Summary
Keywords
Full Transcript
Executives aim to leverage GenAI, but distrust arises from its ""black box"" nature exhibiting hallucinatory behavior. Standard RAG is a preliminary step, but fetching documents differs from understanding business intricacies. How can AI both retrieve data and reason effectively? In this session, participants will learn to advance beyond basic RAG methodologies to create a true AI ""Corporate Brain"" using a knowledge graph. This session targets leaders wanting trustworthy, accurate, and context-aware AI systems. Dr. Anderson Prewitt will explain how modeling business aspects (customers, products, processes, and personnel) as a knowledge graph can reduce AI hallucinations and reveal valuable insights. Attendees will realize knowledge graphs are vital for an AI system that supports Harmony, Ethics, Veracity, Integrity, Discernment, and Safeguards (H.E.V.I.D.S.) as core operational elements. Participants will leave with a strategic framework for implementing trustworthy AI, combining advanced graph technology (Graph ML for RAG) with ethical design principles represented in the H.E.V.I.D.S. framework. Speaker: Anderson Prewitt View Presentation: https://drive.google.com/file/d/1suNE5wBZlwUgbBm-UfDf6XklkCoExMXF/view?usp=drive_link Resources: Get Started with Aura - https://bit.ly/3LOLrjh Deployment Center - https://bit.ly/4jOelM3 Ground AI Systems and Agents with Neo4j - https://bit.ly/4oVsnyb #nodes2025 #neo4j #graphdatabase #graphrag #knowledgegraph
