The law
Fabric Platform
A portable runtime for ontology-based, agent-native business applications.
Your auditors get an answer that holds. Every state change carries the actor, the policy that allowed it, and the event that explains it, so an audit becomes a query instead of a reconstruction. Teams adopting it stop building a bespoke approval and audit layer for every application.
3 common questions, answered below ↓- Role in the family
- The law
- Databricks surfaces
- Lakebase / PostgresUnity CatalogDatabricks Apps
- Status
- Published on npm as @fabricorg/platform. Every other accelerator on this page consumes it.
- Documentation
- platform.fabric.pro
The problem
In most enterprise systems, a row changes and nothing explains why. Audit means reading application logs and guessing. When an AI agent is one of the actors, that gap stops being an inconvenience and becomes a governance failure.
How it works
Every domain change passes through one mutation pipeline: Actor, Action, Policy, State Machine, Handler, Adapter, Event, Projection. No exceptions and no bypasses. Read models are derived from the event log rather than being authoritative, so state is replayable.
What it does
One auditable entry point
Every state change goes through invokeAction. There is no second path into the domain.
Policies at every checkpoint
Code, data, or hybrid policies evaluated before a transition is allowed, not inside a prompt.
Declarative state machines
Illegal transitions are structurally impossible rather than defended against in handler code.
Agent-equivalent governance
An AI actor passes exactly the same gates as a human one. Same pipeline, same policies, same audit trail.
Your auditors get an answer that holds. Every state change carries the actor, the policy that allowed it, and the event that explains it, so an audit becomes a query instead of a reconstruction. Teams adopting it stop building a bespoke approval and audit layer for every application.
FAQ
Fabric Platform, answered
Do we have to adopt the whole platform to use it?
No. It is a library you register inside your own application, not a system you migrate onto. You start by routing one domain's mutations through it and expand from there.
How is this different from an audit log?
An audit log records that something changed. This makes the change impossible unless a policy allowed it, and the event that explains why is emitted as part of the same transaction. Audit becomes a query rather than a reconstruction.
Does it work for AI agents as well as people?
That is the reason it exists. An agent actor passes exactly the same policy and state-machine gates as a human one, with the same audit trail. There is no separate, weaker path for automation.