One Model, Not Many
Nothing to reconcile, nothing to re-integrate.
Most platforms stitch together separate data models for billing, metering, and revenue recognition. BillingPlatform runs on one.
- Self-describing by design. Every object defines itself: fields, relationships, rules, workflows, permissions.
- Read at runtime, not trained in. The AI reads the definitions live, never from your setup or a stale copy.
- Nothing to reconcile or re-integrate. Change the model, and you’re done, nothing downstream to rewire.
This self-describing layer has a name, a revenue ontology: the platform’s declarative definition of everything it knows about itself. When it grows, the AI grows with it.
One Reasoning Layer Across the Whole Platform
Native orchestration, not a patchwork of agents.
Bolt-on AI gives each function its own agent, each blind to the rest. BillingPlatform runs one orchestration layer that sees the whole model and dispatches work across it.
- One orchestrator, full domain awareness. It plans and executes across every function, not within one.
- Deterministic execution. The AI acts on one source of truth, not a guess at how systems reconcile.
- Available the moment it’s configured. Capabilities live in the model, so anything you configure, the orchestrator can already use. No development project, no vendor roadmap.
Use Our AI or Bring Your Own
One gateway, your choice of model.
Reach the same orchestration layer two ways: BillingPlatform’s native assistant, or your own AI tools. One gateway, governed by your permissions.
- In the platform. The native assistant already knows everything the model does. Nothing to set up.
- Through MCP. One server connects any compatible AI tool to the live model. No connectors, no exports.
- Open to your ecosystem. It speaks MCP, ACP, and A2A, so agents from your CRM, ERP, tax, and payment systems can dispatch to it too.