THE BUSINESS-AUTHORITY LAYER FOR CONSEQUENTIAL AI ACTIONS

Connect business authority
to consequential AI actions.

PayReality connects approved business rules and current enterprise facts to action authorization, integrated enforcement, and execution evidence. Evaluate what an agent may do, require review where needed, and retain a connected record of the decision and reported outcome.

RULES · FACTS · AUTHORIZATION · ENFORCEMENT · EVIDENCE

Explore the Authority Flow

Follow an AI agent attempting a real enterprise action, in a live, simulated environment.

Agent
Attempted Action
Authority
Decision
Evidence
scroll

One connected workflow, from rule to record

PayReality connects approved business rules and current enterprise facts to action authorization, integrated enforcement, and execution evidence, as one accountable workflow rather than five unrelated tools.

Rules in

Relevant organizational rules and their authoritative sources are identified, and a structured interpretation is proposed with traceable references back to them.

Interpretation approved

An authorized human reviews and approves the exact interpretation of the rule, before it can govern anything. This is a different event from approving an individual action.

Action evaluated

The exact requested action is established, current enterprise facts the policy needs are obtained, and the action is evaluated against approved policy, authority, and those facts.

Action approved where required

Where the policy requires it, an authorized human approves this specific action. Conditions are re-checked before the authorization to act is issued.

Enforced & evidenced

A compatible, integrated enforcement point applies the authorization. Where a destination reports back, PayReality reconciles it and preserves the linked decision and evidence history.

This is the target workflow the platform is built toward. Which steps are live, reference-tested, or still in development for a given integration is covered page by page, not implied by this summary.

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 what happens to authority once a human hands a task to a system.

Assistant
AI answers questions at human request. Humans decide and act.
Recommendation
AI proposes an action. A human still approves before anything happens.
Execution
AI initiates and executes business actions directly against enterprise systems.
Workforce
AI operates as a standing participant in the business, delegating and receiving work across other agents and tools, not on request.

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 authority the organization actually granted, and that it hasn't quietly grown along the way.

Delegation of Authority
Approval Matrices
Procurement Policy
Risk Frameworks
Internal Controls
Audit Processes

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.

WHAT AI DOES
Reasons
Analyzes
Recommends
Negotiates
Plans
WHAT ONLY THE ORGANIZATION DECIDES
Whether this specific action, right now, is within the authority that's actually been delegated to this agent.

An approved task becomes explicit boundaries.

A human approves a task in the terms people already use: what it covers, what it's worth, where it can go, and how long it's good for. PayReality expresses that approval as machine-verifiable authority boundaries, not a vague instruction an agent has to interpret for itself.

This is approval of the rule's interpretation, a policy or governance decision. It's a different event from approving an individual action later, which is covered in Current Execution below.

Permitted action
Resource
Value limit
Destination
Time window
Required evidence
Approval requirement

Not every task uses every field. A required-evidence condition is declared on a policy; whether it's independently checked at the moment of the action depends on what that specific policy actually evaluates.

Authority may narrow. It must never expand.

As authority moves from a person to an agent, or between agents and tools, each downstream grant can only remain within, or become narrower than, the authority it received. This is the one rule every delegation in PayReality has to obey.

THE RULE
"Authority may narrow during delegation, but must never expand."
WHAT'S TESTED TODAY, AND WHAT WE'RE BUILDING TOWARD

A single delegation, a person to one agent, or one agent to one connected system, is checked and revocation-aware today: PayReality verifies the grant is still live at the moment it matters, and denies the action the instant it's revoked or expired. Chains that span multiple agents and tools are the harder case this rule is built for, and the direction our architecture is designed toward; verifying every hop of a multi-agent chain end to end is on our roadmap, not something we're claiming as shipped and proven today.

Narrowing bounds what any one delegation can do; it doesn't, by itself, prevent several narrowly-scoped child agents from adding up to more spend or activity in aggregate than intended. That's a separate policy question, evaluated at the level the organization defines it.

Checked again, right before it happens.

Before a consequential action reaches a supported, integrated enforcement point, PayReality evaluates the current authority, the applicable policy, and whether anything has since been revoked, then allows, blocks, or escalates the action to a human.

GOVERNANCE & IAM
"Who is this, and what's it technically permitted to touch?"
Authenticates identity and enforces technical access and entitlements well. It doesn't evaluate a specific autonomous action against the authority it was actually delegated, in the moment it happens.
ALREADY IN PLACE
WHAT CONNECTS THEM
Policy → Decision
A written policy still needs something to evaluate a specific AI action against it, at the moment the action is attempted
PAYREALITY, AT THE MOMENT OF ACTION
"Is this action authorized, right now?"
Evaluates the specific action against current authority and policy, then allows, blocks, or escalates it, before it executes.
Agent
Attempted Action
Authority
Decision
Evidence
PAYREALITY DECIDES. YOUR ENFORCEMENT POINT MAKES IT EFFECTIVE.

PayReality makes the authority decision and issues the constrained authorization. A compatible, integrated enforcement point makes that decision effective at the execution boundary; an Allow decision is not, on its own, an execution, and where no enforcement point is integrated, PayReality cannot prevent the action from happening some other way.

An AI agent tries to change a supplier's bank details.

This is the same scenario the interactive demo walks through, step by step.

AgentAP-Invoice-Agent
Trusted Adapter reportsChangeSupplierBankDetails
Approved Action MappingUpdate supplier bank details
PayRealityEvaluates the agent's delegated authority
DecisionNeeds human approval
Changing where a payment goes is exactly the kind of action this organization's policy sends to a human every time: not a failure, a deliberate control the organization chose for a historically high-risk action type. PayReality determines whether the exact action is supported by valid delegated authority; it doesn't score the action for fraud itself. Whichever way it resolves, the decision already produced signed Evidence.

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.

Review resolutionApproved
Capability authorizationIssued
CapabilityVerified and consumed by the enforcement point
An external, customer-operated enforcement point verifies and consumes this authorization before the downstream operation proceeds. PayReality issues the authorization; it doesn't carry out the operation itself, and can't prevent it from happening through a path that never calls PayReality at all.
Single use
Once consumed, the same authorization cannot be replayed.
One per decision
A second authorization cannot be minted from the same decision.
Scope bound
The wrong action, resource, or environment is rejected.

What remains after a decision.

PayReality preserves the authority lineage, the relevant policy, and the decision record, alongside the reported execution outcome when one comes back. A record shows what was authorized, evaluated, and reported. It does not, on its own, independently prove every source fact behind it was true.

EACH SYSTEM STAYS AUTHORITATIVE FOR ITS OWN FACTS

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.

Authorization Receipt
AgentAP-Invoice-AgentActionUpdate supplier bank detailsAuthority basisDelegated Treasury authorityDecisionNeeds human approvalEvidence Signature verifiedExecution reconciliationAwaiting receipt
PayReality records what it authorized. When a separately authenticated destination or trusted execution adapter later supplies an execution receipt, PayReality verifies its linkage and reconciles the reported execution against the authorized action (matched, mismatched, failed, partial, missing, or indeterminate). A cryptographically authenticated receipt proves what the trusted source reported; it does not independently prove that the underlying business system or real-world event was truthful. Historical authority evidence stays valid even after current permission to execute has since been revoked.

A single agent, or a chain of them.

PayReality works whether a person delegates directly to one autonomous agent, or through a workflow that hands work between multiple agents and tools. Multi-agent handoffs are the hardest case for the narrowing rule to hold, not the only case it applies to.

ONE AGENT

A person delegates a task directly to a single autonomous agent, or a single connected system. This is the case our current implementation is tested and revocation-aware against today.

MANY AGENTS AND TOOLS

Work moves from a person, through several agents and tools, to a final action. The same narrowing rule applies at every hop; verifying it end to end across a full multi-agent chain is the architecture we're building toward, not a capability we're claiming is fully proven in production today.

Your authority
already exists.
We make it continuous.

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, its interpretation reviewed and approved by an authorized human, current cross-system facts resolved, the exact action evaluated, a separate action-level 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 together
Delegation of Authority
Approval Matrices
Procurement Policy
Risk Frameworks
↓ PayReality compiles these into machine-evaluable rules

PayReality is a layer, not a replacement.

It's designed to sit alongside the systems you already run, not compete with them for the same job.

Identity systems
Establish who or what is acting, and what it may technically access.
ERP and business systems
Remain the source of business facts, and execute the action itself.
Policy and orchestration
Existing policy engines and workflow orchestration can stay exactly where they are.
PayReality
Preserves and evaluates authority across the delegated action, and the evidence behind it.

No specific vendor is named here because no vendor partnership is currently documented. PayReality is built around a vendor-neutral authority and evidence contract, so an enforcement point you already operate can submit actions, enforce authorizations, and report execution back.

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.

A pilot evaluates one consequential workflow against your existing controls: one action, the systems holding its authority, and a measurable comparison with what you already have in place.

See Example Applications
ONE EXAMPLE WE'RE EXPLORING: PROCUREMENT AI

PayReality is seeking procurement AI vendors to test a narrower question: when an enterprise customer changes the commercial boundaries an AI agent operates within, can the vendor clearly show what changes, test the impact, and obtain an approved release record before the new rules govern agent behavior? This is an early discovery programme we're seeking participants for, not a claim that signed design partners or a deployed product already exist.

Learn more, or help us test the model

See how PayReality
evaluates a real decision.

Your existing systems already establish identity and enforce local access. PayReality evaluates whether a specific autonomous action is within the authority your organization has delegated, and that it hasn't expanded along the way, before it happens, and preserves the evidence.

See PayReality in Action
Or watch the 7-minute walkthrough