Knowledge Graphs & GraphRAG – Essential Ingredients for Enterprise GenAI

Knowledge graphs are emerging as useful and often necessary for bringing Enterprise GenAI projects from PoC into production. They make GenAI more dependable, transparent and secure across a wide variety of use cases. They are also helpful in GenAI application development: providing a human-navigable view of relevant knowledge that can be queried and visualised. This talk will share up-to-date learnings from the evolving field of knowledge graphs; why more & more organisations are using knowledge graphs to achieve GenAI successes; and practical definitions, tools, and tips for getting started.

Key Takeaways

• Knowledge graphs are essential for scaling Enterprise GenAI projects: They are crucial for moving beyond PoCs and achieving production-ready GenAI applications.
• Enhanced trust and security: Knowledge graphs make GenAI more reliable and transparent, ensuring better decision-making and reducing risks.
• Improved development and understanding: They provide a human-navigable view of relevant knowledge, aiding in application development and understanding GenAI’s reasoning.
• Growing adoption and benefits: Organisations are increasingly recognising the value of knowledge graphs in achieving GenAI success. It’s essential to stay updated on the latest developments and consider incorporating knowledge graphs into your own projects.

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Bio

Emil Pastor- Head of Solutions Architecture ANZ| Neo4j| Australia

Emil Pastor is Head of Solutions Architecture A/NZ at Neo4j, based in Sydney, Australia. He is a data and AI professional, who enables organisations in various industries through strategy, architecture, use case delivery, and capability building to support stakeholders and client data professionals in leveraging their data assets. Prior to working at Neo4j, he worked as an Architect and Consultant for organisations such as Microsoft, McKinsey & Company (QuantumBlack), EY, and Teradata.