Context Layer

An enterprise knowledge graph is a connected, contextualized view of an organization’s data that highlights the relationships among key business entities. It is part of the context layer, which also incorporates additional relevant data, often in real time, such as user permissions, definitions, and key metrics, and puts it all in a machine-readable format optimized for AI consumption.

The context layer transforms institutional knowledge into the structured, machine-readable format AI agents need to make decisions and take actions. However, without a foundation grounded in trustworthy golden records, the context layer will be incomplete—leaving AI agents vulnerable to errors, hallucinations, and unreliable decisions. MDM solutions unify, cleanse, and enrich data about an organization’s key business entities—such as customers, products, or suppliers—to form golden records, providing the master data the context layer needs to be effective.

AI models and AI agents need context such as semantic meaning, real-time entity information, data lineage and provenance, and data governance to produce trustworthy results. The context layer translates complex enterprise schemas into language an agent can understand, providing a continuous flow of information that helps agents move past generic pattern matching toward relevant enterprise reasoning.