Learn how a visualization-first approach to AI can transform how we look at documents and quickly gain actionable insights from large and unstructured content. Whether you’re implementing AI applications or just exploring what’s possible, this talk is a practical look at how visualization enhances graph analysis through an AI-mediated user experience. See how we extract explainable knowledge maps from PDFs, looking in depth at the Enron scandal through email chains, as an example.
We emphasise the significance of engaging visually with the output of large language models (LLMs). AI-powered graph solutions streamline data enrichment, entity extraction, and contextualization, further empowering analysts to uncover hidden patterns and make informed decisions. Visualization enables a human user to explain results, render complex situations understandable, and encourage LLMs to express answers with greater depth and flexibility.
Demo Visualization View: https://graphxr.kineviz.com/share/65de29d02ae7517560a2c12f/Murder%20Mystery/65de29f92ae7517560a2c18e/24-02-27-13-29
Knowledge Mapping Insurance Fraud with SightXR: https://youtu.be/ISrsM9TBUcE?si=EXoLauWl70sFtgyE
A Visualization-First Approach to GenAI & Knowledge Graphs: https://www.youtube.com/watch?v=NXHIj1lI5rE
Blog: https://medium.com/kineviz
Website: https://kineviz.com/sightxr
Guests: Ben Goosman & Dienert Vieira, Kineviz
#neo4j #graphdatabase #visualization #llm #ai #knowledgegraph