Submissions should be on graph-related topics that are technical in nature. They can include any stack, programming language, industry use case, technique, or methodology. Topics range from graph and AI projects to engineering and optimizations of the inner workings of applications and data intelligence. 

There is no limitation on the types of use cases you can discuss. We do ask that presentations concentrate on the "how" – for example, showing the code, graph data models, Cypher queries, best practices, lessons learned, and more.

We strongly encourage first-time speakers and presenters from minority groups to submit proposals. 

Choose from three session formats:

• 25-minute talks with Q&A
  
• 10-minute lightning talks
• 2-hour hands-on workshops

The conference's main themes are: 

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.

We'll highlight some talks and speakers before the CFP deadline. Submit your abstract by May 20, 2026, to be considered. 

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