Training Series – Mastering Neo4j Deployment for High-Performance RAG Applications

21 Mar, 2024

This session offers valuable insights from our experience transforming a RAG (Retrieval Augmented Generation) Proof of Concept, which utilizes a Neo4j knowledge graph, into a fully-fledged cloud application. This session is designed to provide practical guidance on enhancing your development practices and optimizing Neo4j-based applications for the cloud environment. During the workshop, the team will delve into several key areas, including: – Prioritizing Development: Discover strategies for efficiently prioritizing development tasks to ensure your project advances smoothly from concept to production. – Moving Code out of Jupyter Notebooks: Learn the best practices for transitioning code from Jupyter Notebooks to a more structured and scalable environment suitable for cloud application development. – Creating Ingestion Pipelines: Gain insights into designing and implementing effective ingestion pipelines that streamline the flow of data into your Neo4j knowledge graph, enhancing data reliability and availability. – Refactoring the Graph Data Model: Explore techniques for refining and optimizing your graph data model to better support the scalability and performance requirements of cloud applications. Slides: Needle Design Kit: GenAI Ecosystem: Graph Data Science with Generative AI Workshop: Tomaz Bratanic Blog: Going Meta Series: LangSmith: Neo4j Developer Blog: NeoDash: Trainers: Daniel Bukowski, Alex Gilmore & Alexander Fournier #neo4j #graphdatabase #genai #llm #knowledgegraph #deployment #cloud

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