Agentspay

Use case

AI Agent API Billing - Pay Per Call Without Overruns

When an agent pays per API call, a loop is a bill. Cap the spend, throttle the velocity, and attribute every dollar to the provider it paid.

In short

AI agent API billing is how an agent pays for metered or pay-per-call services it consumes, such as model inference, data, or third-party APIs. Agentspay enforces per-transaction, daily, and total caps plus velocity rules, so a retry loop or runaway agent is declined before it racks up charges. Spend is attributed per provider in the audit trail for clean cost reconciliation.

The challenge

A metered agent stuck in a retry loop can burn through a usage budget in minutes, and you only find out when the invoice arrives.

How Agentspay handles it

Agentspay caps each metered wallet and applies velocity rules that limit how much can be spent in a window, so a loop is stopped instead of billed. Each provider gets a scoped card and its own attribution, so you see exactly which API consumed which budget. Cross a threshold and the spend waits for a human, while everything below it settles automatically and is logged.

Further reading: how agents pay per MCP tool call, setting spending limits on x402, and what agent payment infrastructure costs.

The control surfaces

The controls behind it

The surfaces this use case leans on, each enforced before any money moves.

See the whole flow in how it works, or check what it costs on the pricing page.

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Let this agent spend safely

Fund a capped wallet, write a policy, and issue a scoped virtual card today. Sandbox-first and rail-neutral.

Never moves money without policy