Enterprise data, however, is rarely ready for an LLM. Most organizations use relational databases, which can have fatal flaws when used directly with an LLM. Knowledge graphs—machine-readable ...

To keep an SLM relevant and accurate, you still need to feed it fresh, contextual data. That’s where graph technology comes ...

Knowledge graphs: The link between data and meaning While Google popularized the term “knowledge graph” in 2012, the concept of representing knowledge as interconnected information has roots ...

As industrial data grows in complexity and scale, traditional methods of managing information, focused on storage and basic ...

An essential component for building more trustworthy AI lies in creating a more solid data foundation on top of graph databases, knowledge graphs, and vector databases. Each element plays a ...

One of the best-known graph databases is Neo4j, which recently announced support for the enterprise version of its cloud-hosted service, Aura, on Azure. Available in the Azure Marketplace, it’s ...

To start building your knowledge graph, set up a Neo4j database. It will be the backbone of your project. You’ll use the Cypher query language to add, change, and find complex network data.

To stay visible in AI search, your content must be machine-readable. Schema markup and knowledge graphs help you define what ...

On February 26, 2025, Valkyrie's revolutionary knowledge graph technology will embark on its journey to the Moon aboard Intuitive Machine's IM-2 Mission as a part of the Athena Mission Launch from ...