Overview
How the platform builds, maintains, and surfaces your organization's knowledge.
The platform maintains a single structured model of your organization's knowledge — your ontology — and keeps it current as the systems and documents it describes change over time. Two components share this model:
- The Ontology Agent builds and maintains the ontology.
- The Knowledge Base renders it as readable, portable documentation.
Both read from and write to the same source of truth, so your structured definitions and your human-readable knowledge never drift apart.
How it works
The system operates in three stages — build, maintain, and surface — which also describe the lifecycle of any piece of knowledge it holds.
The Ontology Agent reads your documents and connected data sources and instantiates the primitives that compose your ontology: Thing Type Definitions, Metric Definitions, and Templates. You review each proposed primitive, edit it as needed, and publish it.
As the underlying sources change — a revised specification, a new data field, a hardware revision — the same agent detects the drift and proposes targeted updates to the affected primitives. The model stays aligned with reality instead of decaying after each change. Users can also edit and maintain ontology resources and links via API, Agent, or Console.
On a fixed cadence, the Knowledge Base compiles the published ontology into a continuously maintained wiki in the Open Knowledge Format (OKF). The result is one body of knowledge in two renderings: structured primitives that your teams and applications build on, and open, human- and agent-readable documentation that anyone can consume.
The design goal is to provide the rigor of a typed ontology and the portability of an open format at the same time, rather than trading one for the other.
Where to start
Don't try to model everything at once. Start from the work that matters most:
- Pick the workflow with the most leverage. The highest-volume task, the biggest time-sink, or the single decision with the most leverage over revenue.
- Define a great outcome. Decide what success looks like for that workflow — faster, cheaper, or more accurate — so you can tell when you've reached it.
- Pull in only what that outcome requires. Connect just the data sources and integrations the workflow needs, not everything you have.
- Get the highest-value capability live as soon as possible. Ship that one workflow, prove the outcome, then expand from there.