Neo4j's director of partner marketing argues that enterprise AI success depends on an ecosystem of cloud, data, and AI partners, with graph technology providing the connected context layer to ground A…
A developer has built a production-grade AI trading bot for Polymarket that operates autonomously with persistent memory, server-side event loops, and native tool integration. The system uses a multi-…
Neo4j acquires GraphAware, a provider of intelligence analysis software for government agencies, to build an open-standard alternative to proprietary tools like Palantir Gotham. The deal addresses gro…
Databricks and Neo4j have partnered to create a next-generation digital twin that combines operational data with graph-based asset topology, enabling real-time fault propagation analysis and fleet-wid…
Databricks and Neo4j have partnered to build a retail AI assistant that combines a governed lakehouse foundation with a connected knowledge graph to improve consumer trust. The assistant uses a two-ag…
INTERPOL's 2026 Global Financial Fraud Threat Assessment reports global fraud losses reached $442 billion in 2025, with financial fraud now among the top five global crime threats. A new graph-enriche…
Neo4j announced Document Intelligence, a new feature in preview inside Neo4j Aura that converts documents into a queryable knowledge graph without requiring graph modeling expertise or extraction code…
Neo4j announced Neo4j Virtual Graph, a zero-copy architecture that lets enterprises run Cypher queries and graph algorithms directly on data in Snowflake, Databricks, and other databases without movin…
SynapCores has launched an AI-native database that unifies graph traversal, vector similarity, and LLM inference into a single execution engine, eliminating the need for multiple systems and round-tri…
Researchers introduced Reflection-Augmented Scaling (RAS), a method that uses execution error messages from databases to improve Cypher query generation through in-context learning. Testing across thr…
Basic vector search is inadequate for enterprise AI pipelines and promotes GraphRAG, a hybrid retrieval approach combining vector search with graph databases. It describes a Spring AI and Neo4j implem…
At HumanX, Neo4j CTO Philip Rathle discussed with Ryan how knowledge context enhances AI agents, arguing that a model-only approach is unsuitable for enterprises due to issues like stale training data…
This summary is based on the provided article. The second edition of *Unlocking Data with Generative AI and RAG* by Keith Bourne expands its coverage to include agentic RAG, graph retrieval, semantic …
The article provides instructions for deploying a multi-instance causal cluster of Neo4j 3.1 RC1, referencing resources such as a docker-compose.yml file from the docker-neo4j repository and a beta ma…