Architecture and engineering teams
Use a living, machine-native system model to keep intent, assumptions, boundaries, behaviours, invariants, and the consequences of change explicit as AI and people work on the system.
Agencies and consultancies
Take on systems where being wrong is expensive. Use one traceable model to connect each recommendation to its reasoning and each constraint to an origin that can be demonstrated during review and sign-off.
Security and system assurance teams
Build assurance from the living, machine-native system model instead of reconstructing it after implementation. Connect obligations, controls, boundaries, decisions, and evidence.
Product leaders and system owners
See what the system assumes before an incident exposes it. Understand where uncertainty persists and how proposed interventions affect integrity, risk, and compliance posture.