Summary

Keywords

neo4j graph databases graphs LLM retrieval augmented generation RAG vector database vector search GenAI AI Artificial intelligence nodes25

Full Transcript

The intersection of agentic artificial intelligence (AI) and enterprise knowledge graphs presents a very exciting opportunity for Enterprises to transform complex business processes into intelligence guided by a standard business Ontology. Graph database like Neo4j largely helps organize and manage complex, interconnected data, giving a single source of truth. Agentic AI helps look at manual processes and move beyond Automation into the realm of Transformation. Outcomes not possible via techniques like RPA and integration, can now be easily enabled by large language and multi-modal models. Newer techniques like Model Context Protocol (MCP) can be leveraged to create an orchestrated, intelligent system for provisioning, managing, and querying the knowledge graph at enterprise scale, with particular focus on maintaining robust security through Role-Based Access Control (RBAC). By combining specialized AI agents with standardized protocols, organizations can create flexible, dynamic systems that significantly reduce management overhead while ensuring compliance with strict enterprise security requirements. We now have an Ontology guided approach to organize and consume enterprise data to enable digital transformation. Speakers: Dattaraj Rao & Sadashiv Borkar 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