Knowledge Graph
A structured representation of entities and their relationships used to improve AI explainability, auditability and alignment with domain ontologies.
A graph database where nodes represent real-world entities (people, products, events) and edges capture their relationships (owns, authored, located-in). Knowledge graphs provide semantic context, enable transparent query-based reasoning, and support provenance tracking. Governance includes schema management, ontology versioning, and access controls to ensure that the graph remains accurate, consistent with business definitions, and compliant with data-privacy constraints.
A pharmaceutical company builds a knowledge graph linking genes, compounds, clinical trials, and side-effect reports. When its drug-discovery AI suggests a new molecule, researchers trace through the graph: “This molecule binds to Gene X, which in trial Y showed adverse event Z.” This explainability fosters trust and accelerates regulatory submissions.
“What used to take weeks of manual reviews and policy work is now structured and auditable in Enzai within minutes. It’s the first time AI governance has felt operational, not theoretical.”
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