This Week in Neo4j: GraphRAG, GraphAcademy, Knowledge Graphs, Symfony and more

Alexander Erdl

Senior Developer Marketing Manager

Welcome to This Week in Neo4j, your fix for news from the world of graph databases!

This edition is a very GraphRAG one: it showcases how Lettria achieved 20% accuracy gains with GraphRAG, introduces the new GraphRAG learning path on GraphAcademy, explains GraphRAG fundamentals with Knowledge Graphs and offers Symfony developers tools for deeper Neo4j integration.


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Happy Graphing,

Alexander Erdl

 

COMING UP!

Seema’s expertise includes AI-driven solutions for EDA and educational applications, with a proven ability to lead distributed teams and drive cross-functional collaboration.

Connect with her on LinkedIn.

Seema is a Featured NODES 2025 Speaker. Her session is titled “Building Smarter Knowledge Graph Pipeline for Secure and Robust Semiconductor Chips”. In this talk, she will present a scalable, graph-driven system that transforms chip design metadata into a dynamic, queryable knowledge graph. This enables proactive detection and traceable analysis of potential security risks.


Seema Naswa

 

GRAPHRAG: GraphRAG: How Lettria Unlocked 20% Accuracy Gains with Qdrant and Neo4j


Daniel Azoulai shows a hybrid approach of combining Qdrant’s vector search capabilities with Neo4j’s knowledge graphs, which addresses the limitations of traditional vector-only RAG systems, particularly in handling complex, regulated documents in industries like pharma and aerospace. The result was an improvement of over 20% in accuracy and enhanced explainability and auditability in AI outputs.

 

GRAPH ACADEMY: Neo4j & GenerativeAI Learning Path


On GraphAcademy, we have curated a GRAPHRAG Learning Path for you. Start with the just updated Neo4j & GenerativeAI Fundamentals and follow the path or just pick the lessons you are interested in, e.g. how to build Knowledge Graphs or using frameworks like LangChain or Agents with MCP.

 

KNOWLEDGE GRAPH: GraphRAG Explained: AI Retrieval with Knowledge Graphs & Cypher


In this video, Meredith Syed walks you through building a GraphRAG system that extracts structured knowledge from unstructured text using LLMs and stores it in a Neo4j knowledge graph. You’ll learn how to transform text into nodes and relationships, construct Cypher queries from natural language and generate contextual answers by combining LangChain, Neo4j and IBM watsonx.ai.

 

SYMFONY: Integrating Neo4j With Symfony: Profiling Queries and Centralized Logging


This guide by Ghlen Nagels demonstrates how to integrate Neo4j with Symfony’s Profiler and Logger tools to monitor Cypher query performance and centralise logging. Symfony’s debugging capabilities allow developers to gain insights into query execution times, identify bottlenecks and efficiently debug issues. The tutorial provides step-by-step instructions for setting up the Profiler and Logger, enabling a streamlined development workflow when working with Neo4j in Symfony applications.

  • GraphAcademy: Another addition to our GraphRAG Learning Path: “Using Neo4j with LangChain
  • Get to Know Graph: Level up your graph skills with webinars packed with practical insights to help you build powerful apps
  • Learn on Your Schedule: Go deeper into graph technology on Neo4j’s On-Demand webinar library
  • New Webinar: Neo4j Graph Analytics on Snowflake: Uncover Deeper Insights – AMER, EMEA, Asia Pacific

POST OF THE WEEK: deepset



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