Data Science & AI #30 – Knowledge Graphs

This meetup will focus on knowledge graphs and their role in modern AI systems — from structuring complex information to making unstructured content more usable for search, reasoning, and intelligent applications.
Together with Neo4j and Capgemini, we will look at how knowledge graphs can help bridge the gap between raw data and useful, context-aware AI. The evening will combine practical perspectives, real-world use cases, and space for discussion with other data and AI professionals from the Nuremberg area.
A special thank you to ZOLLHOF for hosting us in Nuremberg.
You can expect an evening of technical insights, conversation, and informal networking over food and drinks.

🗓️ Agenda
17:30 – Arrival and welcome
18:00 – Talks
19:00 – Networking with food and drinks
Location: ZOLLHOF, Nuremberg

Build an Aura Agent in 20 Minutes – From Unstructured Content to Knowledge Graphs
By Zaid Zaim, Developer Advocate, Neo4j
Databases, documents, APIs, notes — data is usually scattered across many systems, while AI agents can only work with a limited part of it. Structured data is often easier to query, but unstructured content and the relationships within it remain much harder to use effectively.
In this session, Zaid Zaim will show how to build an Aura Agent in under 20 minutes. Starting with natural-language interaction over structured data, the session then moves on to using LLMs to extract entities and relationships from unstructured content, generate a graph schema, and build a knowledge graph. Finally, the graph is connected back to the agent, enabling richer and more context-aware responses based on both structured and unstructured information.

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Join us for an evening of practical insights, technical discussion, and exchange with others working in data science, AI, and knowledge-driven systems.