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 AI/ML projects to engineering and optimizations of the inner workings of applications.

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: 

Applications: Libraries, Frameworks and Platforms 

Discover how application developers use Neo4j to power inventive solutions to everyday problems across software stacks, deployments, integrations, and programming languages. With a wide range of tools and practices tailored to different use cases, discover how to improve the developer workflow.

AI Engineering: Generative AI, RAG, and Agents 

Build software with AI. Whether vibe coding or architecting multi-agent systems, AI tools and techniques continue to evolve rapidly, and graphs are everywhere. Learn everything from state-of-the-art research to practical, real-world applications. Topics will cover knowledge graph construction mixing structured and unstructured data, an array of GraphRAG retrieval patterns, full-stack agentic strategies, and neatly packaged libraries, tools, and services.

Data Intelligence: ML, Algorithms, and Models 

Explore how data scientists and ML practitioners drive AI innovation through better data, smarter algorithms, and graph-powered insights. Learn from a blend of hands-on techniques with practical applications—whether you're building better training sets, engineering features from graphs, or refining model behavior with fine-tuning and reasoning strategies. Topics include GraphRAG, centrality, named entity recognition, scalable data workflows and more.

Graphs: Knowledge Graphs, Visualization, and Tips & Tricks

See the power and insights of knowledge graphs in new and intuitive ways. Get introduced to the best tools and technologies to visualize large and dynamic graph data. Discover new ways of integrating with a broad range of data systems, including the best techniques for automated, scalable, and secure import processes. This path will accelerate your data discovery and analytics capabilities.

Architecture: Frameworks, Data Platforms, Clouds and Beyond

Graphs don’t exist in isolation—they connect seamlessly with modern data ecosystems. This theme dives into the technical landscape of integrating Neo4j with key frameworks, data platforms, and cloud environments. Learn how to leverage connectors, drivers, and APIs to integrate with streaming systems like Apache Kafka, AI/ML pipelines, and cloud-native services across AWS, Azure, and GCP. We’ll explore best practices for data ingestion, federated queries, and hybrid deployments, enabling you to build scalable, high-performance graph-powered solutions.

We'll highlight some talks and speakers before the CFP deadline. Submit your abstract by May 15, 2025 to be considered. 

To see the talks from last year, check out the NODES 2024 Playlist.