Enterprise Authority over AI
Consequential AI action should remain grounded in the mandate of the people and organizations responsible for it.
COMPANY
AI capability is accelerating. Enterprise authority has to keep up.
Authrizd exists to make sure increasingly capable AI remains inside explicit human and enterprise authority.
WHY AUTHRIZD EXISTS
The authority problem AI created.
AI is moving from generating answers to taking consequential actions across software, data, cloud systems, workflows, and enterprise applications.
That creates a new control problem. Identity can prove who or what is acting. Permissions can show what a system is technically allowed to access. But neither answers the more important question:
Authrizd was created to close that gap. We connect consequential AI actions to explicit human and enterprise mandate, delegation, constraints, and evidence—before the action is allowed to proceed.
Authrizd keeps consequential AI action inside explicit enterprise authority.
COMPANY PRINCIPLES
What guides the work.
Proof before execution
Resolve the authority basis before a consequential action occurs, then preserve the decision and its evidence.
Permission is not authority
Technical access establishes capability. It does not prove that a particular action was intended or legitimately empowered.
Vendor-neutral authority
Enterprise authority should follow the action across models, agents, tools, platforms, and infrastructure.
Evidence that survives the action
Authority, delegation, constraints, decisions, and outcomes should remain reconstructable after execution.
Authority stays with the enterprise
The enterprise—not an AI vendor or orchestration layer—must define and retain its own authority model.
EXPLORE AUTHRIZD
Evaluate the authority model before starting a pilot.
View the synthetic Authrizd for GitHub demo to see how mandate, scope, delegation, and evidence shape an action-specific authority decision.