Join Neo4j and Databricks experts for an in-person, hands-on workshop. It is built for data scientists, data engineers, AI/ML engineers, and AI developers who want to build production-style AI agents grounded in governed lakehouse data and connected graph context.

In this half-day Neo4j Graph Workshop, you will combine the Databricks Lakehouse, Databricks Genie Agents, and Neo4j graph intelligence to build a multi-agent system with memory. The system answers natural-language questions across structured analytics data and connected graph context.

Working with an Aircraft digital twin dataset, you will see how Databricks handles high-volume sensor telemetry and SQL analytics while Neo4j captures the relationships between aircraft, systems, components, flights, delays, maintenance events, airports, and documentation. You will then connect both platforms through a Supervisor Agent that routes each question to the right specialist: Genie for sensor trends and aggregations, Neo4j for graph traversal and relationship questions, or both when the answer spans data sources.

During this interactive workshop, you will:

• Deploy and explore your own Neo4j Aura instance, and learn Cypher basics over connected aircraft relationships.
• Load governed Databricks Lakehouse data into Neo4j using the Neo4j Spark Connector.
• Model aircraft, systems, components, sensors, flights, delays, airports, and maintenance events as a knowledge graph.
• Build semantic search and GraphRAG over maintenance documentation using Databricks Foundation Model APIs and Neo4j vector search.
• Configure a Databricks Genie Agent for natural-language SQL analytics over Unity Catalog tables.
• Build a LangGraph supervisor agent that routes questions across the Genie Agent, Cypher over your own Aura instance, and the GraphRAG retriever, then deploy it to Databricks Model Serving.
• Add memory to your supervisor agent with Neo4j Agent Memory, so it recalls prior conversations alongside the fleet graph it already queries.
• Learn when to combine lakehouse SQL, graph traversal, semantic search, agent memory, and multi-agent orchestration.

Requirements: 

• Bring a laptop with a modern web browser.
• Ability to access the workshop Databricks workspace.
• Ability to access Neo4j Aura (ports 7474 & 7687).
• Basic familiarity with SQL and Python is helpful but not required for every section.
• No local software installation required.
• If your work laptop has firewall restrictions you cannot control, we recommend bringing a personal laptop.

Join Neo4j and Databricks experts for an in-person, hands-on workshop. It is built for data scientists, data engineers, AI/ML engineers, and AI developers who want to build production-style AI agents grounded in governed lakehouse data and connected graph context.

In this half-day Neo4j Graph Workshop, you will combine the Databricks Lakehouse, Databricks Genie Agents, and Neo4j graph intelligence to build a multi-agent system with memory. The system answers natural-language questions across structured analytics data and connected graph context.

Working with an Aircraft digital twin dataset, you will see how Databricks handles high-volume sensor telemetry and SQL analytics while Neo4j captures the relationships between aircraft, systems, components, flights, delays, maintenance events, airports, and documentation. You will then connect both platforms through a Supervisor Agent that routes each question to the right specialist: Genie for sensor trends and aggregations, Neo4j for graph traversal and relationship questions, or both when the answer spans data sources.

During this interactive workshop, you will:

• Deploy and explore your own Neo4j Aura instance, and learn Cypher basics over connected aircraft relationships.
• Load governed Databricks Lakehouse data into Neo4j using the Neo4j Spark Connector.
• Model aircraft, systems, components, sensors, flights, delays, airports, and maintenance events as a knowledge graph.
• Build semantic search and GraphRAG over maintenance documentation using Databricks Foundation Model APIs and Neo4j vector search.
• Configure a Databricks Genie Agent for natural-language SQL analytics over Unity Catalog tables.
• Build a LangGraph supervisor agent that routes questions across the Genie Agent, Cypher over your own Aura instance, and the GraphRAG retriever, then deploy it to Databricks Model Serving.
• Add memory to your supervisor agent with Neo4j Agent Memory, so it recalls prior conversations alongside the fleet graph it already queries.
• Learn when to combine lakehouse SQL, graph traversal, semantic search, agent memory, and multi-agent orchestration.

Requirements: 

• Bring a laptop with a modern web browser.
• Ability to access the workshop Databricks workspace.
• Ability to access Neo4j Aura (ports 7474 & 7687).
• Basic familiarity with SQL and Python is helpful but not required for every section.
• No local software installation required.
• If your work laptop has firewall restrictions you cannot control, we recommend bringing a personal laptop.