The execution layer
Where a decision about AI becomes a governed system.
The simulation is where a team discovers the decision: where a given use of AI should automate, augment, assist, or escalate. This is a view of the layer that comes next. It describes an operating model for governing AI systems across an enterprise, not a single tool, and it is meant as an architecture and a point of view rather than a product tour.
The lifecycle
- 01
Tier 1
Intake
Structured conversational intake that translates business requests into explicit system specifications, context parameters, and constraints.
- 02
Tier 2
Vetting
Policy-driven evaluations with automated hard-stop rules across safety, bias thresholds, and compliance.
- 03
Tier 3
Prioritization
A scoring engine that weighs technical feasibility and cost against business and clinical impact.
- 04
Tier 4
Proof Window
Tracking real-world outcomes, drift auditing, and ROI, while maintaining a verifiable decision history.
How it connects
Two layers, not one checklist.
The simulation and this operating model answer different questions. The simulation is about judgment: where a given use of AI should automate, augment, assist, or escalate. The execution layer is about process: how AI systems are taken in, vetted, prioritized, and proven once those decisions are made. The four authority levels and the four lifecycle tiers are separate ideas, and they do not line up one to one.