Show HN: Billing for AI Agents: Valmi (Open Alternative to Paid.ai, Legacy Zuora
https://github.com/valmi-io/value
Hi HN,I am Raj, founder of Valmi.
We were building AI agents and quickly hit a pricing problem.
Tokens, API calls, and seats made no sense for agents. One agent run might be cheap and useless; another might be expensive and replace hours of human work. Billing on usage felt disconnected from real value.
What customers actually asked was: “Did it finish the task?” “Did it resolve the ticket?”
That pushed us toward outcome-based billing - charge only when the agent delivers something meaningful.
But existing billing systems don’t handle this well:
outcomes aren’t first-class concepts costs vary per run (LLMs, tools, retries) it’s hard to see margins per agent or customer
So we built Valmi:
1. outcomes as billable units 2. cost + margin tracked per agent run 3. outcome, usage, or hybrid pricing 4. open-source SDKs, self-hostable stack
Outcome billing also builds trust: customers pay for results, not experiments.
Available on GitHub (https://github.com/valmi-io/value).
I also wrote my hypothesis here: https://www.valmi.io/blog/an-imperative-for-ai-agents-outcom...
Would love your feedback! Also hosted at https://value.valmi.io
-Raj
What do you think are the challenges with AI Agents pricing? How you are currently pricing your AI Agents work?
Would be great to know what HN community thinks.
As costs vary, I think it becomes even more important to track costs for each task.
Also, if costs also vary a lot without usefulness, it becomes difficult to pass these costs onto the customer.
Hence pricing needs to take care of volatility in cost as well. However, pricing is mostly dependent on the value AI Agents create. That I think, AI builders need to generate somehow, instead of just activity.
There could be some workflows where outcomes may not be immediately delivered. Take for instance, a recruiting AI agent solving a successful hire. I would be very glad to understand those scenarios in the field.