The Decision Layer™ · AI Assurance
Know How Much Authority Your AI Agent Really Has
Know where autonomy is defensible, where human approval is still required, and whether harmful actions can be stopped, reversed or reconstructed.
The transformation
Before
An AI agent has access to tools and systems, but its real authority is scattered across permissions, workflow logic and assumptions nobody has assembled in one place.
After
Management can see the boundary between intended autonomy and actual capability, including where a human must still decide.
What changes for you
AuthorityKnow what the agent may decide without human approval.
AccessSee which identities, APIs, systems and data it can reach.
ActionKnow what it can send, buy, change, delete, approve or execute.
ConstraintMake prohibited actions and approval gates explicit.
ObservationReconstruct what the agent actually did and why.
RecoveryProve that material actions can be stopped or reversed.
What you receive
Agent authority map
Delegated decisions, permissions, tools and human approval points.
Agent action trace
End-to-end reconstruction of selected agent behaviours.
Autonomy boundary assessment
Where autonomy can be accepted, constrained or rejected.
Reversibility plan
Stop, rollback and escalation requirements for material actions.
How The Decision Layer moves the issue
AuthorityDefine delegated decision rights.
AccessTest identity and permission reach.
ActionTest what the agent can execute.
ConstraintTest limits and gates.
ObserveTest logs and traces.
RecoverTest kill switch and rollback.
DecideSet the defensible autonomy boundary.
Connected service: this module sits inside AI System & Lifecycle Assurance™. Use the parent page to compare all four assurance modules.
Best used when
The decision is material, the evidence is incomplete, or the current assurance is harder to defend than it looks.
Bring the live use case and the decision it supports. The engagement starts there.