A twelve-word post from Peter Steinberger on July 18 triggered millions of views and a live technical war over AI agent architecture. Andrew Ng's new knowledge graph course added fuel: should ...

According to the latest analysis by Future Market Insights, the AI-Ready Enterprise Knowledge Graph Market is poised for exceptional growth as organizations ...

FlureeDB acts as a secure context layer fit for autonomous systems: pull from many data sources wherever they live, answer structured queries fast and efficiently, carry citations and lineage on every ...

"The no-kill-switch kind of thing? It's increasingly becoming a requirement," says Neo4j CEO Emil Eifrem. This is one of the reasons behind the company's decision to buy GraphAware, an intelligence ...

Neo4j has agreed to acquire GraphAware to expand AI-based intelligence analysis offerings The acquisition supports Neo4j’s $100 million AI investment road map The 2026 Intel Summit on Sept. 24 will ...

Neo4j Ⓡ, the world’s leading graph intelligence platform, today announced an agreement to acquire GraphAware, an intelligence analysis software company for government agencies. The acquisition will ...

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Graph intelligence leaders will join forces to deliver a customer-proven, open-standards intelligence analysis platform that ensures data sovereignty Neo4jⓇ, the world’s leading graph intelligence ...

Neo4j, a leading graph intelligence platform, announced an agreement to acquire GraphAware, an intelligence analysis software company for government agencies—enabling Neo4j to launch a new generation ...

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 ...

Building retrieval-augmented generation (RAG) systems for AI agents often involves using multiple layers and technologies for structured data, vectors and graph information. In recent months it has ...

ABSTRACT: In today’s data-driven business environment, small and medium-sized enterprises (SMEs) struggle to implement effective knowledge management (KM) due to limited financial, technical, and ...