Continuous adaptive authorization for human and AI agent access to applications and APIs

Standing entitlements are the thing Reva.AI argues against. Roles are granted, inherited, and nested until nobody can state why a given identity can reach a given resource, and the review cycle that is supposed to catch this runs quarterly at best. Reva's position is that authorization should be a decision made at the moment of the request, informed by what the identity is doing and what has changed since it last authenticated. That framing matters more with AI agents in the path, since an agent's access requirements shift between one task and the next and cannot be described adequately by a static role.

The platform is built from four parts. A Policy Control Tower is where policies are authored and governed. The Reva Trust Gateway enforces them inline across applications and APIs. Policy Intelligence produces explainable decisions and behavior analytics, together with an access graph that traces the actual grant path behind a permission. A data fabric orchestrates policy across the environments involved. Risk signals arrive through the Shared Signals Framework and CAEP, so a session can be re-evaluated or cut when a device or identity risk event lands rather than at the next login. The stated outcomes are zero standing privileges, a lighter access certification burden, and one policy layer covering hybrid cloud, SaaS, and agentic workloads.