Ian McCloy, Senior Product Manager, Neo4j Sep 23 6mins read
Neo4j transforms graph database management with Cypher API versioning and calendar-based releases, offering seamless upgrades, flexibility, and features. Read more →
Elena Kohlwey, Data Scientist & Graph Database Specialist Sep 16 11mins read
Explore advanced GraphRAG retrieval patterns and how graph structures enhance RAG systems. Learn actionable strategies to implement and optimize GraphRAG. Read more →
Recommend movies to users based on their reading histories and ratings. Learn the setup of Neo4j, mapping data into Java with Neo4j Object Graph Mapper (Neo4j-OGM), and crafting Cypher queries for recommendations. Read more →
Explore the pros and cons of fine-tuning versus retrieval-augmented generation (RAG) for overcoming large language model (LLM) limitations. Read more →
Learn how combing vectors and graphs boosts AI’s ability to reason, helping uncover deeper insights and create smarter queries for complex data. Read more →
Alex Thomas, Senior Software Engineer, AI Sep 05 7mins read
Learn how to enhance GraphRAG applications with hybrid retrieval using the Neo4j GraphRAG Package for Python, combining vector and full-text search. Read more →
Explore running a Neo4j client on a Commodore 64, blending retro computing with modern database technology for a unique learning experience. Read more →
Matthew Wood, Product Manager, Neo4j Aug 20 8mins read
Boost write performance in Neo4j with parallel execution of Cypher subqueries, enabling faster data processing and more efficient graph updates. Read more →
Suman Gautam, Data Scientist, Slalom Aug 16 12mins read
Create a Neo4j GraphRAG workflow using LangChain and LangGraph, combining graph queries, vector search, and dynamic prompting for advanced RAG. Read more →
Alex Thomas, Senior Software Engineer, AI Aug 16 5mins read
Learn Neo4j GraphRAG Python package's capabilities and how to further customize and improve your applications by using the other included retrievers. Read more →
Learn how to simultaneously ingest data into Milvus and Neo4j for a powerful RAG agent with LangChain, optimizing vector and graph database capabilities. Read more →
Tomaž Bratanič, Graph ML and GenAI Research, Neo4j Aug 13 16mins read
Integrate Microsoft's GraphRAG with Neo4j, using LangChain and LlamaIndex for advanced retrieval in just a few steps. Explore detailed code examples. Read more →
Tomaž Bratanič, Graph ML and GenAI Research, Neo4j Aug 12 6mins read
Constructing knowledge graphs from text has been a fascinating area of research for quite some time. With the advent of large language models (LLMs), this field has gained more mainstream attention. However, LLMs can be quite costly. An alternative approach… Read more →
Tomaž Bratanič, Graph ML and GenAI Research, Neo4j Aug 08 5mins read
Learn to use Llama 3.1 native function-calling capabilities to retrieve structured data from a knowledge graph to power your RAG applications. Read more →
Nathan Smith, Senior Data Scientist at Neo4j Aug 06 7mins read
Explore how Neo4j enhances entity resolution with embeddings for string edit distances, improving accuracy and efficiency in data processing. Read more →