Ontology
A living model of your business
Unify your data, systems, people, and processes into a living model that AI can understand, reason over, and act on.
What the model supports
- Entities
- Typed objects with attributes, relationships, and identifiers.
- Mapping
- Field-level mapping from every connected source.
- Resolution
- Deterministic and probabilistic matching rules, per entity.
- Versioning
- Schema versions, validated against existing records before they take effect.
- Access
- Read through the API, the SDKs, and agent tool calls.
- Relationships
- Typed links between entities, traversable from queries and tool calls.
One model your teams and agents share
You define entities once. People query them in the interface, agents resolve them through tool calls, and both get the same answer.
What a shared model prevents
The failures that disappear once everything agrees on the same definitions.
A shared vocabulary
Define the entities, attributes, and relationships your teams and your agents both use.
Mapped to source systems
Each entity points back at the records and fields it was built from.
Evolves safely
Schema changes are versioned and validated against the data you already hold.
Queryable by agents
Agents resolve references through the ontology instead of guessing at table names.
Permissions travel with it
Access rules live on the entity, so every tool that reads it enforces the same boundary.
Defined once, used everywhere
The same definitions serve the interface, the API, your workflows, and your agents.
Before you model
What teams ask before committing to a shared definition layer.
Model your first entity
Start with the one you act on most. Extend it as you learn.