Responsible AI
AI assists. The rules decide what can run.
FlowMaster uses AI inside a Business-as-Code execution model controlled by approved process definitions, human authority and runtime governance. A model can only act inside the boundary set by the approved process.
Operating position
| #01 | People own judgement Approval, exception and escalation points are part of the process definition. Human authority is explicit, named and versioned. |
| #02 | Models do not carry policy The model can draft, read, classify, call tools or suggest the next step. Policy lives in rules evaluated by the runtime governance layer. |
| #03 | Control happens before commit Attempted actions are checked against actor, rule version, data state and process state before they update a system of record. |
| #04 | Model choice belongs to the customer Customers can bring a hosted or self-hosted model. FlowMaster binds execution through the process and runtime governance layer, not through a preferred model. |
Execution-time control
The runtime governance layer is separate from the provider.
What AI may do
- Read the current process context and source-system records it is allowed to see.
- Prepare drafts, summaries, classifications and next-step recommendations.
- Call approved tools when the current process state permits that action.
What binds the action
- The approved process version, not the model prompt.
- The actor and authority rules in force for that customer.
- The runtime governance check immediately before a write, notification or escalation commits.
Practical effect
A smarter model is useful. It is not the control system.