Graph-based contextual retrieval, which uses GraphRAG to traverse a context graph rather than relying on vector similarity alone, improves AI agent accuracy by following explicit relationships between…
Neo4j principal consultant Jesús Barrasa's knowledge-layer series published a second chapter on modeling enterprise processes as a graph rather than a BPMN diagram, using AcmeBank's SMB loan approval …
Neo4j Labs' meta-knowledge-graph repository adds a consolidation layer that converts accumulated agent session learnings into reusable skills and user profiles, addressing the problem where twelve ses…
Microsoft Fabric and Neo4j Graph Intelligence combine OneLake Delta tables with connected property graphs to give AI Copilots multi-hop relationship intelligence for real-time retail recommendations, …
Neo4j published a comparison of vector RAG and GraphRAG, stating that GraphRAG has been shown to more than double factual accuracy while offering better token efficiency and a traceable path back to e…
Neo4j detailed a GraphRAG-based generative AI framework it built internally to ground LLM answers in a Neo4j Aura knowledge graph, combining vector search with an entity layer of types such as Documen…
Neo4j Head of Product Innovation & Developer Strategy Michael Hunger built neo4jev, an open-source experiment that uses TypeSafe.AI's Jev classification model to navigate a Neo4j knowledge graph one r…
Neo4j published the NODES 2026 agenda for its free 24-hour virtual conference on November 12, featuring 100+ speakers across AI Engineering, Data Intelligence and Modern Applications tracks, alongside…
Neo4j announced new enterprise AI capabilities, including Neo4j GraphAware Financial Crime Intelligence (FCI) for graph-powered financial crime detection and Neo4j Virtual Graph, currently in Preview …
Neo4j announced that Virtual Graph, its zero-copy knowledge graph capability over Snowflake, Databricks, and Google BigQuery data, is in public preview for every Aura customer and will reach General A…
Security Operations Centers are adopting Agentic AI faster than heavily regulated sectors like healthcare, but the tools fail when they lack tribal knowledge and environmental context, according to a …
Neo4j published a guide distinguishing three graph technologies — graphs, knowledge graphs, and context graphs — describing them as a progression from data to knowledge to intelligent action. Neo4j st…
A Neo4j solutions engineer argues that enriched knowledge graphs with pre-computed graph metrics let AI agents detect financial crime faster and more precisely than agents given raw graph data, citing…
Neo4j, a graph database company, explains that decision traces stored in a context graph provide a structured, queryable record of how AI agents reach decisions, capturing the reasons, tools, and poli…
Neo4j Labs released @neo4j-labs/nams-ai-provider, a community provider for the Vercel AI SDK that gives any model persistent, cross-session memory backed by the hosted Neo4j Agent Memory Service (NAMS…
Neo4j detailed a multi-agent integration that grounds Salesforce Agentforce responses in a Neo4j knowledge graph using Aura Agent over the Model Context Protocol (MCP), moving graph-specific computati…
A Neo4j semantic layer built with Neocarta cut Text2SQL token costs by up to 81% on a 278-table BigQuery Census ACS catalog and up to 54% on a 264-table Databricks catalog, according to a Neo4j soluti…
Neo4j's Director of Engineering demonstrates using the company's new Document Intelligence tool to convert unstructured PDFs, such as a history assignment on the Swedish-Danish war of 1657–1658, into …
Neo4j AI Research Engineer Michael Hunger argues that Andrej Karpathy's LLM-maintained wiki recipe, which gained viral attention and inspired Google Cloud's Open Knowledge Format (OKF) in June 2026, c…
Neo4j principal consultant Jesús Barrasa published the first chapter of a series building an enterprise knowledge layer, modeling AcmeBank's operating structure as a graph to answer accountability que…