Is Your AI Brain-Dead? Knowledge Graphs Provide the Nervous System
According to MIT, “Despite $30–40 billion in enterprise investment into [AI], 95% of organizations are getting zero return.” Most AI projects never move beyond pilots because enterprise data remains context-stripped.
An LLM without connected knowledge can generate answers, but it can’t reliably understand how your data, systems, and decisions fit together. This leads to inconsistent results that sacrifice trust and stall AI initiatives.
Join us on February 26 to learn why context engineering is the missing link for successful enterprise AI projects. Discover how knowledge graphs power GraphRAG to improve explainability and production-readiness, and boost accuracy by up to 3x.
See how Prospa, Australia’s leading online business lender, used knowledge graphs to cut loan approval times from 48 hours to just 2.
SPEAKER
John Stegeman
Senior Graph Database Product Specialist, Neo4j
John “Steggy” Stegeman is a Senior Graph Database Product Specialist with Neo4j. Prior to joining Neo4j, he held solution architect and consulting roles at Oracle, DXC, Waterline Data, and Hitachi Vantara. John is a self-avowed technology nerd who loves using technology to solve real-world enterprise challenges
