Graph Databases + LLMs: Why Connected Data Makes AI Smarter
Details
Most enterprise data holds answers that never get surfaced — not because the data isn't there, but because the connections between it are invisible to traditional search and SQL.
Contextus is an AI-powered discovery agent built on Arango Contextual Data Platform that changes this. It combines graph traversal — the ability to follow relationships across entities in your data — with large language model reasoning to find high-value connections that flat queries simply can't reach.
In this session, we'll walk through how Contextus works under the hood: how Arango's multimodel architecture stores and traverses connected data, how Arango AutoGraph automatically builds the knowledge graph from raw enterprise data, and how an LLM reasons across that graph to surface insights a human analyst would take days to find.
If you've ever wondered what graph databases actually enable that relational databases don't — or how LLMs become meaningfully smarter when grounded in structured knowledge — this is a hands-on look at both.
Speaker: Daniel Morris, Lead Solutions Engineer — Applied AI, EMEA, Arango
Date: Thursday, July 9th at 8:00amPT /1 1:00am ET /5:00pm CET
Format: Virtual presentation (zoom) + open discussion