Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

Michael Down, Global Head of Financial Services at Neo4j, tells RBI Editor Douglas Blakey that the fraud challenge for banks ...

Sudhir Hasbe, Neo4j's President and Chief Product Officer, on the strategic shift behind the GraphAware deal, what "open ...

Model Context Protocol (MCP) has gained considerable momentum as a standard connector between LLM-powered tools and local systems, internal and external APIs, and data sources. From major clouds to ...

Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, embedding them into a ...

Neo4j, the graph database from the US-Swedish company of the same name, is used by 76% of the Fortune 100, and its Australian customers include organisations in the healthcare, policing and banking ...

Neo4j Aura Agent is an end-to-end platform for creating agents, connecting them to knowledge graphs, and deploying to production using low-code and autogeneration tools. Let’s dive in. You may be ...

What if you could transform overwhelming, disconnected datasets into a living, breathing map of relationships, one that not only organizes your data but also reveals insights you didn’t even know you ...

Neo4j has introduced "property sharding" which, according to one analyst, will help overcome its earlier struggles with scalability, while also allowing transactional workloads on the same system. The ...

This project is maintained again as of 2026-06. The current goal is to keep the original py2neo v3 / Neo4j 3.x example usable for learners, notebooks, and legacy projects while adding a current Neo4j ...

To gain competitive advantage from gen AI, enterprises need to be able to add their own expertise to off-the-shelf systems. Yet standard enterprise data stores aren't a good fit to train large ...