Your AI can access the system.
Is it authorized to take this action?
PayReality converts organizational authority into verified, machine-enforceable controls, resolves that authority using trusted context across systems, and preserves evidence from the proposed action through reported execution.
Follow an AI agent attempting a real enterprise action, in a live, simulated environment.
AI is moving from assistance,
to execution, to workforce
Organizations are increasingly comfortable with AI executing real-world actions on its own. The next step is AI operating as a standing part of the workforce, not a tool invoked occasionally. What hasn't kept pace is who decides whether any of that activity is allowed.
Enterprise authority is
already distributed.
Enterprise authority already lives across identity systems, ERP controls, approval structures, business rules, and accountable people: some of it already encoded in the systems you run, some of it still written for a person to read and follow. Autonomous AI can act across all of those boundaries at once. The challenge is determining whether a specific action is within the full mandate the organization intended.
Access is not authority.
Existing identity and application systems already determine who an agent is and what it may access or execute locally, and they do that well. PayReality evaluates a different question: whether this specific action, given the broader business context, is within the authority your organization actually delegated to it, right now.
Every PayReality decision answers three questions.
PayReality only ever answers the third one. It never assumes an agent is trustworthy just because a Trusted Adapter exists. When a trusted destination or execution adapter later reports what happened, PayReality reconciles that report against what it authorized, but a reported receipt proves what the trusted source reported, not independently what occurred in the physical or business world.
The Agent: a certificate-holding identity, acting for a specific principal, signing every request it makes.
A customer-controlled Trusted Adapter can independently report the real enterprise operation, translated through a deterministic, human-approved Action Mapping.
PayReality's Runtime Authority: has this organization actually delegated this agent the authority to do this, under these conditions, right now?
The Adapter never gives the agent authority. It answers what's being attempted; PayReality alone answers whether it's authorized, and separately reconciles what a trusted destination reports back against that authorization.
What makes an authority decision trustworthy
AI proposes structured authority from your governance documents. It cannot grant authority or activate policy. Citations and critical values are deterministically checked, identities and relationships are resolved by human reviewers, and authorized humans approve the exact version before it can ever be enforced. This extraction pipeline has been validated in controlled synthetic testing; accuracy against real enterprise documents using a live model is a separate evaluation we are still completing before we describe it as production-ready.
A decision often depends on current facts held by other enterprise systems, such as who currently holds a role or whether an approval is still active. PayReality authenticates the source, provenance, and validity window of each fact it consumes; it does not independently guarantee that the underlying fact itself is true. When a required fact is missing, stale, or conflicting, the decision fails closed or routes to human review rather than guessing. Packaged, named-vendor connectors into specific enterprise systems are not yet generally available; today's cross-system facts are wired per design partner.
PayReality decides. Your enforcement point makes it effective.
PayReality makes the business-authority decision and issues the constrained authorization. A compatible policy enforcement point makes that decision effective at the execution boundary, an Allow decision is not, on its own, an execution.
PayReality is designed around a vendor-neutral authority and evidence contract. Agent runtimes, gateways, and customer-controlled enforcement points can submit canonical actions, enforce PayReality authorizations, and return authenticated execution receipts. Named adapters are built according to customer workflow requirements.
The PayReality reference PEP remains a working reference implementation, a certification mechanism for other enforcement points, and a fallback deployment option. It defines what correct authorization verification looks like; it is never positioned as the only place PayReality can be enforced. PayReality does not depend exclusively on any single runtime or gateway vendor, and does not replace the identity, sandboxing, technical policy, or monitoring capabilities those environments already provide.
An AI agent tries to change a supplier's bank details.
This is the same scenario the interactive demo walks through, step by step.
From decision to controlled execution
A human reviewer approves the request above. The original decision still reads "Needs human approval" forever; the approval is a separate, linked record. For actions that need stronger execution control, that approval lets PayReality issue a short-lived, single-use authorization tied to this exact request.
What remains after a decision.
Every decision produces a signed, hash-chained record across three layers: intent evidence (what was proposed or observed), authority evidence (why it was allowed, denied, or escalated), and execution evidence (what a trusted destination reported, and whether it matched). The Authorization Receipt packages that record into one shareable, human-readable view.
Your authority
already exists.
We make it machine-evaluable.
Every enterprise already operates approval matrices, spending limits, delegation of authority policies, procurement policies, and risk frameworks, some already encoded in the enterprise systems you run, some still written for a person to read. Runtime Authority, the Authority Graph, Runtime Policies, the Evidence Portal, and Authorization Receipts aren't five separate purchases, they're one connected capability set spanning a single lifecycle: authority proposed from your governance sources, verified and approved, current cross-system facts resolved, the exact action evaluated, human approval obtained where required, a constrained authorization issued, a compatible enforcement point applies it, execution evidence returned, authorized and reported execution reconciled, and the whole authority lifecycle remains auditable end to end.
See how the five capabilities fit togetherFour ways into the same runtime
Platform
Learn the Runtime Authority architecture: how the Authority Graph, Runtime Policies, and Evidence Portal fit together.
Products
Explore the components: Runtime Authority, the Authority Graph, Runtime Policies, the Evidence Portal, and Authorization Receipts.
Developers
Integrate Runtime Authority: register an agent, submit a signed intent, and get a decision and evidence back.
Solutions
See how Runtime Authority applies to your industry's own delegated authority and approval workflows.
Broad category. Narrow, honest proof.
Financial approvals, procurement, claims and refunds, privileged system changes, contract actions, and regulated operational decisions are candidate action categories, example applications we're designing for and validating with early design partners, not production deployments already running across every industry listed on this site. We are selecting initial cross-system workflows with design partners. A controlled pilot focuses on one consequential action, the systems holding its authority, and a measurable comparison against your existing controls.
See how Runtime Authority
evaluates a real decision.
Your existing systems already establish identity and enforce local access. PayReality evaluates whether a specific autonomous action is within the broader authority your organization has delegated, before it happens, and preserves the evidence. Ready to go further: identify one fragmented authority decision, test it in controlled or shadow mode, and define success before any production enforcement.
Or watch the 7-minute walkthrough