Wikidata has built the semantic web backbone supporting knowledge cards in popular engines. Now, it's extending this foundation using a vector database to enhance its existing knowledge graph and ...

Without structured context, GenAI applications are noisy and error prone. After all, real intelligence requires context, precision and understanding. This is why ...

Traditional RAG typically retrieves relevant text from a vector database and supplies it to an LLM as context. Automation ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

FlureeDB acts as a secure context layer fit for autonomous systems: pull from many data sources wherever they live, answer structured queries ...

When Aquant Inc. was looking to build its platform — an artificial intelligence service that supports field technicians and agents teams with an AI-powered copilot to provide personalized ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the generation of plausible-sounding but factually incorrect information. KAIST ...

Knowledge graphs are hyped. We can officially say this now, since Gartner included knowledge graphs in the 2018 hype cycle for emerging technologies. Though we did not have to wait for Gartner -- ...

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