This Week in Neo4j: Developer Survey, Supply Chain, Knowledge Graph, Agentic RAG and more


Welcome to This Week in Neo4j, your fix for news from the world of graph databases!
At NODES, we launched our 2024 Neo4j Developer Survey – we hope you take part. Additionally, in this episode, we analyse the global supply chain in pharma with GraphRAG, learn from developing a custom knowledge management system, and examine the concept of Agentic RAG.

I hope you enjoy this issue,
Alexander Erdl

 
COMING UP NEXT WEEK!

Astrid is a tech entrepreneur, software developer, AI/Machine Learning enthusiast, and Neo4j Ninja. An Indonesian living in Berlin, she loves travelling to explore different running scenes, cuisines (preferably spicy), cultures, and ways of life.
Connect with her on LinkedIn.

In her session at NODES 2024 “Next-Gen Travel Agents: Merging AI Agentic and Neo4j for Personalized Experiences”, she creates personalised travel agents using multiple LLMs and Neo4j, using AI Agentic design patterns for intelligent routing and hallucination checks.

Astrid Paramita Mochtarram
 
SURVEY: Neo4j Developer Survey
Your voice matters! By filling out the Neo4j Developer Survey 2024, you’re helping us create better tools for everyone in the community. The first 500 unique responses also get a $15 Amazon voucher. So be quick!
 
SUPPLY CHAIN: SupplyChainInsights: applying the Power of GraphRAG and Fine-Tuned LLMs in Global Health Supply Chain Analytics
Abhishek Shankar introduces SupplyChainInsights, which uses Neo4j and advanced AI techniques to enhance global health supply chain analytics. By integrating Retrieval-Augmented Generation (RAG) and fine-tuned models, this project offers detailed insights and efficient data retrieval, empowering organisations with improved data transparency and decision-making capabilities.
 
KNOWLEDGE GRAPH: Building Our Own Knowledge System: Why We Took This Pathe
Stefan Wendin discusses the development of a custom knowledge system to enhance organisational learning and decision-making. He outlines the challenges of managing information across various platforms and emphasises the benefits of a unified system that integrates data, fosters collaboration, and supports continuous improvement.
 
GRAPHRAG: Harnessing Agentic RAG and Graph-Based Metadata Filtering for Enhanced Information Retrieval
Shubham Nagar looks at the concept of Agentic RAG, which allows the creation of powerful systems capable of handling complex queries and delivering highly relevant results. This article explores these concepts and demonstrates how to implement them in a practical use case.


POST OF THE WEEK: Lewis N Watson

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