How to Price an AI Agent Marketplace
Per-agent, per-task, and revenue-share models for marketplaces where autonomous agents do the work.
Agent marketplaces flip the SaaS model on its head. Instead of seats, you bill for outcomes — tasks completed, actions taken, or value created by third-party agents running on your platform.
The cleanest models are per-task (flat or metered by complexity), per-agent (a subscription per deployed agent), and revenue-share (you take a cut of the agent builder’s earnings). Most mature marketplaces blend all three.
The hard part is attribution: which agent caused which charge, and who gets paid. Orvlin attributes every token and action to a stable agent id, so you can split revenue with builders and cap spend per agent automatically.
Done well, this turns your marketplace into a metering layer everyone trusts — builders ship agents, you bill accurately, and customers only pay for work that actually happened.
Frequently asked questions
What’s the best pricing model for an agent marketplace?
A blend of per-task metering, per-agent subscriptions, and revenue share. Orvlin attributes usage per agent so you can mix all three.
How do I pay agent builders?
Use revenue share on metered usage; Orvlin’s per-agent attribution makes payouts auditable.