Build Smarter AI: GraphRAG & Generative AI Workshop

Large language models are powerful — but without structure, they lose context fast.

As part of the mAI ist für AI series at 42 Berlin, this workshop explores how can improve GenAI applications and reduce common challenges such as hallucinations.

In this instructor-led workshop, participants will explore how graph databases can improve GenAI applications and reduce common challenges such as hallucinations. You’ll learn key concepts including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), GraphRAG, vector search, knowledge graphs, and AI agents.

The workshop follows a mixed format, combining short theoretical inputs with practical exercises. Participants will work through tasks while instructors are available to support and answer questions.

During the session, you will learn how to:

• Use Neo4j to enhance GenAI applications
• Build knowledge graphs from unstructured data
• Use vector embeddings for similarity search
• Create GraphRAG retrievers using Python
• Build a conversational AI agent using Neo4j and LangChain

16:00 – Registration & Networking
16:30 – Welcome & Kickoff: 42 Berlin & Neo4j
16:45 – Workshop Part I
18:30 – Break
18:45 – Workshop Part II
19:30 – Networking

Basic knowledge of Neo4j, Cypher, and Python

Your own laptop

is a Microsoft MVP, technology innovator, and active figure in the Berlin AI and tech community. His work spans emerging technologies, data architecture, and applied AI. He is known for making complex topics approachable and for helping developers connect technical theory with real implementation.

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Host or Publisher 42 Berlin