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Incarna uses Amazon Bedrock AgentCore for pay-per-inference with BlockRun

This setup allows AI agents to autonomously purchase model inference services on a per-request basis, settling transactions in USDC on the Base network. The integration addresses the challenge of high-frequency, low-value payments that traditional card networks are not designed to handle.

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Key points

  • Incarna integrated Amazon Bedrock AgentCore payments in three days using roughly 200 lines of code.
  • Agents processed over 1,000 payments ranging from $0.001 to $0.05 per call during the beta.
  • BlockRun serves more than 90 models from over 15 providers via the x402 payment protocol.

BlockRun acts as a pay-as-you-go inference router, serving over 90 models from more than 15 providers via the x402 protocol. Incarna, which provides persistent identities for AI agents, used AgentCore payments to manage wallets and enforce spending limits at the infrastructure layer. This ensures agents cannot exceed budget caps even if their prompts are manipulated. The system uses Coinbase CDP connectors for wallet management and supports both exact and dynamic pricing schemes.

The Incarna team reported that integrating this payment flow took three days and roughly 200 lines of code, compared to an initial estimate of two to three months. During the beta phase, agents processed over 1,000 payments, with individual calls ranging from $0.001 to $0.05. Vicky Fu, founder of BlockRun, noted that this approach allows developers to balance performance with sustainable economics, while Justin Zhou, founder of Incarna, highlighted that the platform handled all payment signing and governance without custom code.

The story so far

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  1. Incarna uses Amazon Bedrock AgentCore for pay-per-inference with BlockRunthis story
Full story from AWS Machine Learning Blog · by Peter Jiang primary sourceOpen source ↗

Pay-per-inference for AI agents: How BlockRun and Incarna use Amazon Bedrock AgentCore payments

AWS Machine Learning Blog · 8 October 2026

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This text was published by AWS Machine Learning Blog and written by Peter Jiang. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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IncarnaBlockRunCoinbaseSpreadXVicky FuJustin Zhou

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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