Identify the agent
Bind the request to a verifiable agent identity, delegated role, owner, and workflow purpose.
Lupsee enables controlled workflows in which an AI agent can propose or initiate a payment while deterministic controls, human approvals, execution boundaries, reconciliation, and evidence remain institutionally governed.
An agent may have enough context to identify a payable obligation, but the right to reason about a payment should not automatically grant unrestricted access to move funds.
Lupsee separates the agent’s proposed intent from policy evaluation, approval authority, credentials, and execution.
Coordinate the workflow across existing systems while preserving institution-defined authority and controls.
Bind the request to a verifiable agent identity, delegated role, owner, and workflow purpose.
Check source data, payee, asset, amount, timing, duplicate risk, and required supporting context.
Apply deterministic limits and obtain human approval when policy requires it.
Use a constrained adapter, monitor the outcome, and match it to the originating obligation.
Every agent-initiated instruction passes through the same policy, risk, approval, execution, reconciliation, and evidence stages as other institutional work.
The outcome depends on the institution’s systems and operating model, but coordinated workflows can improve control and operational clarity.
Know which agent initiated the action, under whose authority, and for what purpose.
Keep financial controls outside probabilistic model behavior.
Connect source context, agent rationale, policy decisions, approvals, and settlement outcome.
Follow the control, architecture, and workflow concepts related to this page.
Define the agent’s purpose, authority, source context, approval thresholds, execution adapter, and evidence requirements.