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Ontology Agent

Generate and maintain the primitives that model your domain.

The Ontology Agent is in beta.

The Ontology Agent generates and maintains the instances of ontology primitives that model your domain. Generation and ongoing reconciliation are handled by a single agent through a single review surface; there is no separate tool for the initial build versus later updates.

Inputs

The agent accepts uploaded documents and connects to external data sources such as fileshares and databases. Together with a prompt and the surrounding context, these inputs define the material the agent draws on when proposing primitives.

Generation

From its inputs, the agent instantiates three kinds of primitive:

PrimitiveModelsExample (OEM hardware manufacturer)
Thing Type DefinitionsThe entities in your domainProduct models, assemblies, and parts
Metric DefinitionsMeasured or derived quantitiesTolerances, mean time between failures, test thresholds
TemplatesReusable structures for instantiating these consistentlyA mapping from a supplier's data sheet to a part type

Every proposed primitive is shown in a preview before it enters the ontology. You can inspect what the agent generated, edit it, and publish it. Nothing is written to the ontology without review.

Drift detection

Once primitives are published and their sources remain connected, the agent monitors those sources for change. When a source diverges from what the ontology currently records — a specification is updated, a field is added, a part is superseded — the agent detects the drift and proposes updates to the specific affected primitive instances.

These proposals appear in the same preview, edit, and publish surface used for initial generation, so reviewing an update is identical to reviewing a new primitive.

Because generation and drift detection share one agent and one review surface, the ontology is treated as a living model that the agent continuously proposes changes to, rather than a one-time output that falls out of date.

  • Agentic overview explains how the agent fits the build–maintain–surface lifecycle.
  • Knowledge Base renders the published ontology as a portable wiki.
  • Data model defines the primitives the agent generates.