Capri Ai Agentpay

Capri Ai Agentpay is a governed payment layer purpose-built for AI agents that need to execute transactions, call paid APIs, and settle payments autonomously. As AI agents evolve from simple prompt responders to active participants in digital economies, the fundamental security challenge becomes acute: giving an agent direct access to a private key is a catastrophic risk. A single prompt injection or misaligned instruction could drain an entire wallet. Capri Agentpay solves this by inserting a runtime policy gate between the agent and the signing mechanism, ensuring that no payment is ever made without passing through a fixed, auditable set of checks. The product is designed for engineering teams shipping agent systems in production, particularly those at companies like Northwind, Vela Labs, Orbit, and Greymatter who need real controls around machine-initiated spending. At its core, Agentpay intercepts HTTP 402 Payment Required challenges, evaluates each request against a strict policy order that includes merchant allowlists, per-transaction caps, daily budgets, and an auto-approve threshold that can pause for human review. Only when every check passes does the system settle the payment, retry the original request with cryptographic proof attached, and store a signed receipt that operators can verify offline. Agents never hold keys, never bypass policy, and every payment leaves a verifiable trail. This transforms the dangerous proposition of autonomous agent spending into a manageable, auditable, and secure workflow that satisfies both engineering and security teams.

HTTP 402 Payment Challenge Handling

Capri Agentpay natively handles the HTTP 402 Payment Required status code, which is emerging as the standard for paid API endpoints. When an agent makes a request and receives a 402 challenge, Agentpay intercepts it automatically, evaluates the payment against configured policies, and either approves, denies, or pauses the transaction. This eliminates the need for developers to write custom payment logic for every paid API integration, providing a consistent, secure, and automated payment flow that works across any service that uses the 402 standard.

Per-Agent Budgets and Spending Caps

Every agent operating under Capri Agentpay is assigned its own budget and spending limits, completely independent of other agents in the system. Operators can define per-transaction caps that prevent any single payment from exceeding a set amount, as well as daily budget limits that ensure an agent cannot overspend over time. These granular controls allow teams to allocate resources precisely, restrict high-cost agents, and maintain financial oversight without blocking legitimate autonomous operations.

Merchant Allowlists and Policy Gates

Capri Agentpay enforces a merchant allowlist that restricts which recipients an agent can pay. Every payment request is checked against this allowlist as the first step in the policy evaluation order, ensuring that agents can only send funds to pre-approved merchants, APIs, or services. This prevents agents from being tricked into sending payments to malicious or unauthorized addresses, adding a critical layer of security that protects against prompt injection attacks and misconfigured agent instructions.

Human-in-the-Loop Approvals and Verifiable Receipts

When a payment request exceeds the auto-approve threshold, Capri Agentpay pauses the transaction and surfaces it for human review. Operators see the exact amount, asset, chain, and recipient before deciding to approve or deny. Once a payment is settled, the system generates a signed receipt containing hashes, timestamps, and verification fields that can be independently verified offline. This creates a complete audit trail for every machine payment, satisfying compliance requirements and giving security teams full visibility into agent spending.

Autonomous Research Agent Paying for Premium Data APIs

A research agent tasked with aggregating market intelligence from multiple paid data sources can use Capri Agentpay to autonomously call premium APIs. The agent requests data, receives a 402 challenge, and Agentpay evaluates the payment against a research-specific policy with a moderate daily budget and approved merchant list. Below the auto-approve threshold, payments settle instantly, and the agent continues its analysis. Above the threshold, the human operator reviews and approves the transaction, maintaining control while enabling efficient data gathering.

AI Agent Managing Cloud Infrastructure Costs

An infrastructure management agent that spins up and down cloud resources needs to pay for compute, storage, and network usage. Capri Agentpay provides per-agent budgets and spending caps that prevent the agent from exceeding allocated cloud credits. The merchant allowlist restricts payments to approved cloud providers, and every payment generates a verifiable receipt for cost accounting. The human-in-the-loop approval catches any unusual spending spikes, preventing runaway costs while allowing the agent to operate autonomously.

Customer Support Agent Settling Refunds and Credits

A customer support agent authorized to issue refunds or credits can use Capri Agentpay to settle these payments directly. The agent initiates a refund, Agentpay checks the merchant allowlist against the refund recipient, applies per-transaction caps to prevent excessive refunds, and pauses for human review if the amount exceeds the threshold. The signed receipt provides a permanent record of the refund for accounting and dispute resolution, reducing manual effort while maintaining strict financial controls.

Multi-Agent System with Shared Budget Pool

A team of specialized agents working together on a complex workflow can share a budget pool managed by Capri Agentpay. Each agent has its own per-transaction cap and daily limit, but the total spending across all agents is governed by the pool. The policy gate ensures that no single agent can drain the pool, and the human operator can review aggregate spending patterns. This use case is ideal for agent platforms that deploy multiple agents for tasks like content generation, data enrichment, and API orchestration.

Does Capri Agentpay require my agent to hold a private key?

No. Capri Agentpay is designed specifically to eliminate the need for agents to hold private keys. The agent only interacts with a typed surface and MCP tools. The actual signing and settlement happen inside the Capri runtime after policy checks are passed. This means even if an agent is compromised or given a malicious prompt, it cannot directly access or drain your wallet because the keys are never exposed to the agent.

What happens if a payment request fails the policy checks?

If a payment request fails any of the fixed policy checks, such as the merchant allowlist, per-transaction cap, or daily budget, Capri Agentpay denies the transaction and does not create a signature. The agent receives a denial response, and the operator can review the failed request in the Capri interface. This ensures that no unauthorized payment ever reaches the signing stage, providing a hard security boundary around agent spending.

Can I integrate Capri Agentpay with my existing agent framework?

Yes. Capri Agentpay provides six MCP tools that integrate directly into agent frameworks supporting the Model Context Protocol. Additionally, the product offers a VS Code extension for local development and testing, a quickstart guide, API references, and deployment notes. The Base Sepolia sandbox allows teams to test payment flows in a safe testnet environment before deploying to mainnet, making integration straightforward for most modern agent development stacks.

How does human review work in practice?

When a payment request exceeds the configured auto-approve threshold, Capri Agentpay pauses the transaction and surfaces it in the operator interface. The operator sees the exact amount, asset, chain, and recipient, along with the policy branch that triggered the review. The operator can approve, deny, or modify the request with a single click. Once approved, the payment settles and a signed receipt is stored. This workflow takes seconds and provides a clear audit trail without becoming manual busywork.