Neo4j Live: From Language to Logic - Why Graph AI Succeeds Where LLMs Fail

Описание: In this Neo4j Live session, we explore why Graph AI succeeds where LLMs fail. You’ll learn how knowledge graph–powered systems deliver significantly higher accuracy by explicitly modeling relationships, enabling traceable reasoning, and grounding AI in structured intelligence. This is the difference between fluent language and reliable logic - critical for use cases like regulatory compliance, financial analysis, and operational decision-making.

If you’re thinking beyond text generation and toward AI that can reason, connect, and scale with confidence, this session will show you the path forward.

Guest: Matthias Buchhorn-Roth

LinkedIn:   / mbuchhorn  
Github: https://github.com/ma3u

Overcoming LLM Deficits with Multi-Layered Ontologies:   / overcoming-llm-deficits-multi-layered-onto...  
Building Graph-Aware Agents with Neo4j and Microsoft Agent Framework https://neo4j.com/labs/genai-ecosyste...
NeoDash: https://neo4j.com/docs/neodash-commer...
NeoDash on Aura: https://neo4j.com/docs/aura/dashboards/

0:00 – Welcome & intro
3:00 – Live quiz: Where vector search falls short
10:25 – The legal challenge: Why LLMs struggle with law & hierarchy
16:30 – Vector search trap: Similarity ≠ authority
21:00 – Introducing symbolic Graph AI for legal reasoning
25:50 – Temporal dimension & state machines in legal workflows
32:10 – Architecture overview: Hybrid Graph + LLM approach
41:00 – From document management to knowledge management
49:50 – Legal AI in practice: Lessons learned & tooling
57:00 – Q&A: Hierarchies, compliance & implementation
1:06:30 – Wrap-up & upcoming Neo4j events

#neo4j #graphdatabase #KnowledgeGraph #genai #llm