Ontology
The business object model — types, instances, and relationships — agents reason over.
category ▸ Data & Provenance
Ontology, in plain language.
An ontology is a structured model of the things a business cares about and how they relate: object types (Customer, Case, Claim), the specific instances of those types, and the typed relationships between them. It gives agents, workflows, and policies a shared, explicit vocabulary instead of leaving them to guess at unstructured data.
An ontology also becomes a governance surface. Once data is modeled as typed objects with named properties, you can attach permissions at the property level and constrain which actions are allowed on which object types — turning the data model into a control plane.
How Cortex implements it.
This term isn't abstract here — it maps to a real capability in the runtime. Here is exactly how Cortex enforces or relates to it.
Cortex's ontology service models object types, objects, and typed relationships, with an Object Explorer that walks the neighborhood around any object. Each object type declares allowed actions and property-level permissions.
Those permissions are enforced: an action proposed against an object is checked against the type's allowed-actions list (403 ACTION_NOT_PERMITTED_FOR_OBJECT if it is not allowed), and restricted property reads fail closed — so the ontology enforces minimum-necessary access, not just structure.
Keep building the vocabulary.
These terms sit next to this one in the governed-AI model — follow the thread to see how the controls connect.
Provenance
The recorded origin of a fact or output — what source it came from, and where.
Action Fabric
A lifecycle that makes every agent action a governed object: dry-run, propose, approve, execute, compensate.
DLP
Data loss prevention — screening data in and out of tool calls to catch leakage and injection.
Tenant isolation
Strict separation so one customer's data and agents can never reach another's.
See Ontology enforced, not just defined.
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