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Note: This is an affiliate event that requires registration on luma

Join Neo4j and Microsoft for an hands-on workshop where you’ll learn how to build AI agents powered by knowledge graphs. Limited to 50 qualified builders.

​In this session, we will build a functional GraphRAG pipeline within a live Azure environment. Moving beyond high-level theory, you will deploy Neo4j Aura and integrate it with Microsoft Foundry to implement a complete, end-to-end architecture for reasoning over connected data.

​What You Will Learn:
We’ll use SEC EDGAR filings—specifically the quarterly holdings of asset managers with $100M+ in assets under management (AUM)—as our primary dataset. This data is ideal for demonstrating how to map complex ownership structures and many-to-many relationships.
✅ Build AI agents that leverage knowledge graphs
✅ Automate Ingestion: Use AI to parse and load data from Azure Blob Storage into Neo4j.
✅ Model Relationships: Use Cypher and the Neo4j Browser to map connections between thousands of portfolios and their institutional holdings.
✅ Orchestrate Agents: Layer a Microsoft Foundry AI agent over the graph to enable natural language reasoning across the connected financial data.

​Who should attend:
Developers, Builders, Data engineers, Data scientists, and Tech leaders.
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Speakers:

![img](https://images.lumacdn.com/cdn-cgi/image/format=auto,fit=cover,dpr=2,quality=75,width=800,height=800/uploads/zp/325d123a-db95-4667-9fb1-ac6739ea8a10.jpeg)


​Ben Lumley, Neo4j

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​Agenda

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  • ​12:30PM Arrival, Check-In, Lunch & Networking
  • ​1:30PMI ntro & Overview
  • ​2:00PM AI Hands-On Workshop
  • ​3:00PM Break
  • ​3:30PM Labs: Moving Data
  • ​4:30PM Labs: Neo4j and AI
  • ​5:00PM Networking & Refreshments

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​Requirements:
You'll need a laptop with a web browser.
​Sponsors:
Neo4j and Microsoft

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Thanks to our sponsors: Linux Australia and ANU!
Want to sponsor our costs for pizza and drinks, and meet our enthusiastic members? Get in touch!

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You can find our Code of Conduct here: https://github.com/canberra-python/README/tree/main/conduct
We care about new people and quiet people, so we want to have some bare minimum standards that we expect.

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