When an AI agent runs, it often needs to buy something to finish a task: a model inference, an API response, access web content, or a call to another agent. These purchases are small and frequent, sometimes a fraction of a cent each, and they happen inside the agent’s loop with no person available to approve them.

Amazon Bedrock AgentCore payments removes that burden. It gives agents a managed way to pay for services on demand, with spending limits enforced by the infrastructure rather than by the model. In this post, we look at how Incarna used AgentCore payments to let its agents pay BlockRun for model inference one request at a time. BlockRun is a pay-as-you-go inference router serving more than 90 models from more than 15 providers over x402, each call quoted and settled independently. AgentCore payments works with x402-compatible endpoints, including Amazon Bedrock inference endpoints. With the service, the Incarna team cut the work of adding x402 payment support from months to days, and put an end-to-end pay-per-inference flow into production.

The challenge: Paying for inference by the request

Paying per inference is a high-frequency, low-value pattern. An agent might make hundreds of small purchases in a single session, each worth a fraction of a cent. Card networks weren’t built for sub-cent payments. Building your own rails means solving several hard problems at once. You must decide where the money is held and how each payment is signed, support emerging payment protocols such as x402, and keep an autonomous agent from overspending.