Neo4j: Augmented AI: Building Contextual Intelligence with Knowledge Graphs

This video explores how knowledge graphs, specifically using Neo4j, enhance AI by providing contextual intelligence and regulatory-grade explainability, addressing common AI pilot failures due to fragmented data and hallucinations.

What it covers

AI Pilot Failures
AI projects often stall due to fragmented data and context-free models that generate hallucinated rather than reasoned outputs.
GraphRAG Introduction
GraphRAG uses verified, traceable graph relationships to ground AI answers in factual, contextual data.
Knowledge Graphs in AI
Knowledge graphs enable AI systems to reason with structured, interconnected data instead of relying on unverified patterns.
Regulatory Compliance
GraphRAG supports compliance with GxP, EMA, and FDA standards by providing explainable, traceable AI decisions.
Pharma Use Case
In pharmaceuticals, knowledge graphs help ensure AI models meet rigorous regulatory requirements for data integrity and transparency.