Ontology Inference

A taxonomy says what something is; an ontology says how things relate. Inference exploits the relationships — if a policy governs a department, and a role belongs to that department, the policy is relevant to the role without anyone stating it. For retrieval this converts a flat corpus into a navigable structure, letting a system surface material that a keyword or embedding match would miss because the connection is organizational rather than textual. The cost is modelling effort, and the risk is inferring relationships the organization does not actually assert.

Because taxonomy, audiences, roles and record relationships are all first-class in Centralpoint, the relationships available to inference are the ones the organization already maintains for governance rather than a separate semantic layer built for AI. Relationships used to broaden retrieval are the same ones used to control access, so inference cannot reach across a boundary that governance established.