I’m happy to share that I’ll be speaking again at the Azure User Group Munich as part of our recurring meetup series. 🎤
This time, the session continues the GraphRAG topic from Part 1 and moves one step further: from understanding the concept to actually building with it.
The session is called:
GraphRAG in Practice, Part 2: Building with Microsoft GraphRAG
In the first session, we looked at why classic vector search and traditional RAG approaches are not always enough, especially when information is highly connected and relationships between entities matter.
In this follow-up session, we’ll take a more practical look at Microsoft GraphRAG, Microsoft’s open-source framework for creating graph-based retrieval workflows.🔗
The goal is to understand how GraphRAG can be applied in practice: how unstructured data can be transformed into a knowledge graph, how indexing and querying work, and how graph-based structures can support more contextual, traceable, and explainable retrieval. 🧠
This session is designed for anyone interested in practical GenAI architectures, retrieval patterns, knowledge graphs, and real-world AI engineering. No prior GraphRAG knowledge is required — I’ll start with a short recap before moving into the practical part.
🎯 We’ll look at:
- a short recap of GraphRAG and why it matters
- what Microsoft GraphRAG is and which problem it solves
- how indexing, graph creation, and querying work in practice
- how domains and communities can help structure connected knowledge
- a hands-on look at the Microsoft GraphRAG SDK
- where GraphRAG adds value compared to classic RAG
- practical considerations for real-world AI architectures
As always, I’m looking forward not only to presenting, but also to the discussion afterwards. 🤝 These community sessions are a great opportunity to exchange ideas, hear different perspectives, and learn from each other.
📅 Event Details
Date: Thursday, 28 May 2026
Time: 18:00–19:00
Format: 💻 Online via Microsoft Teams – join here
Language: 🌍 English, with questions also welcome in German 🇩🇪 or Turkish 🇹🇷
If you’re interested in GraphRAG, retrieval, knowledge graphs, AI architecture, or practical GenAI engineering, I’d be happy if you joined us. 🚀
