Graph Database - France

Register: luma.com/ai-builders-paris-sept

Building the AI Stack: Models, Infrastructure, Inference, Agents & Graphs
​Official side event of AI Engineer Paris, 2026
​AI engineering is moving beyond individual models toward full-stack systems that bring together models, inference, data, and infrastructure. Join Mistral, Neo4j, Daytona, and SGLang for an evening of practical conversations about what it takes to build and run modern AI applications.
​We’ll explore the technologies powering the AI stack—from open models and high-performance inference to to secure sandbox infrastructure for AI agents and graph-powered context. Speakers will share real-world approaches, lessons learned, and emerging patterns for building AI applications that are faster, more capable, and easier to develop.
​Come hear from the teams building the infrastructure and developer tools behind the next generation of AI—and stick around to connect with other AI engineers, developers, and builders.

Guest: Jose Latorre ( https://www.linkedin.com/in/joslat/ )

Blog: https://neo4j.com/blog/developer/agentmemory-for-net-a-native-sibling-to-neo4j-agent-memory/

#neo4j #graphdatabase #agenticai #knowledgelayer #knowledgegraph #graphrag #AIAgents #dotnet #agentframework

Register: https://neo4j.registration.goldcast.io/series/94f27929-1670-4f2b-bfdd-ab4e48eb8c22

# Road to NODES 26 Workshops

Get hands-on with graphs and AI before NODES 2026, Neo4j's free 24-hour global conference on November 12. Road to NODES is a series of free, two-hour, live workshops that walk you through building real graph-powered systems step by step.
Sessions include:

• Oct 1 — Build knowledge graphs from unstructured documents and structured data, then power similarity search with embeddings and Neo4j vector indexes.
• Oct 8 — Tackle hallucinations at the structural level with GraphRAG retrieval, semantic tool selection, multi-agent swarms, and agent steering.
• Oct 15 — Build a lightweight knowledge layer over your documents and SQL data using tables of contents, themes, and a semantic connections layer.
• Oct 22 — Query Snowflake, Databricks, or Google BigQuery directly with Cypher using Neo4j Virtual Graph, no data movement required.
• Oct 29 — Build a full graph-based agent memory stack with hierarchical context graphs and dynamic playbooks.
• Nov 5 — Build a memory layer with the Neo4j Agent Memory Service, combining short-term conversation history, long-term entities, and reasoning traces in one graph.

Each session runs live at multiple times to fit different time zones, so pick the slot and topics that work for you.

NODES, the biggest community gathering dedicated to engineering better intelligence returns on November 12, 2026, for its eighth year.
Join thousands of developers and data and AI practitioners for this free, 24-hour conference to learn about the latest advancements in intelligent systems and gain insights from speakers who showcase their implementations, tools, and models.

AI Engineering: Generative AI, RAG, and Agents
Build software with AI. From architecting multi-agent systems to exploring new coding workflows, AI tools and techniques are evolving rapidly—and graphs play a central role. Learn from the latest research and real-world applications. Topics include knowledge graph construction from structured and unstructured data, context graphs and memory for more reliable AI systems, GraphRAG retrieval patterns, full-stack agentic strategies, and the libraries, tools, and services used to bring these systems into production.

Modern Applications: Libraries, Frameworks, and Platforms
Discover how developers build modern applications and AI-powered systems using graph databases alongside popular libraries, frameworks, and platforms. Learn how teams solve real-world problems across software stacks, deployments, integrations, and programming languages. Explore tools and practices tailored to different use cases that streamline development, improve the developer workflow, and accelerate the delivery of intelligent applications.

Data Intelligence: Knowledge Graphs, LLMs, and Fully Fledged Context
Explore how developers, data scientists, and AI builders unlock deeper intelligence from data. Learn how knowledge graphs and modern data workflows combine data engineering and domain expertise to build scalable pipelines, models, and knowledge structures that continuously improve outcomes. Sessions highlight practical techniques and real-world applications including GraphRAG, centrality, entity recognition, graph visualization, and scalable data integration.

To see the talks from last year, check out the NODES 2025 Playlist.