AI agent payments: control before execution

The payment rail answers how money moves. The control layer answers whether the agent should be allowed to initiate that economic action.

The practical model

• Agent identifies itself and its workspace.
• A proposed spend is checked against policy.
• Exceptions route to a human.
• The chosen rail executes or records settlement.
• Outcome telemetry closes the loop.

How Alem approaches it

Alem keeps authorization separate from execution so the same policy model can sit above multiple rails.

What is live today

Alem's self-serve sandbox includes company workspaces, agent registry, budgets, spend policies, human approvals, economic ledger, ROI, HTTP/OpenAPI and MCP. Live payment execution remains private beta / integration-stage.