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.
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Enzai provides enterprise-grade infrastructure to manage AI risk and compliance. It creates a centralized system of record where AI systems, models, datasets, and governance decisions are documented, assessed, and auditable.
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