Clocknext - Pricing and Billing Infrastructure for AI Agents
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Clocknext is a billing and monetization platform for AI-native apps and agents. It’s tailored for AI founders, revenue, and engineering teams, to track AI usage from your product in real time, turn it into billable metrics with flexible pricing plans, and monitor costs, margins, and profitability at every level.
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Hey Product Hunt 👋
I’m Vijay, founder of @Clocknext. I’ve spent 16 years in software, and for most of that time, “how do you charge?” had a short answer: one-time payments, per seat, per month.
AI products changed that. The cost of serving a customer moves with every request, and the unit of value can be credits, outcomes, something you invent, or a mix of all of it.
Most teams try out leading billing tools like Stripe, Chargebee, Zuora, etc., and try to make it work for their pricing models, find them lacking, and end up their own billing system: a signals table in Postgres, a cron job that totals the month, and a spreadsheet that matches provider invoices against customer invoices.
It holds well at the start. But the problems start when:
Pricing needs to change but is waiting on engineering bandwidth
You build new features that require new pricing models that need to be built
Revenue teams lose sight of P&L per customer until it’s too late
We built Clocknext so you can price an AI product without maintaining that system yourself. With it, you can:
Mix credits, outcomes, units, and wallets in one plan
Bill prepaid and postpaid entitlements side by side
See provider cost next to price, per customer, per agent, and per model
🎁 Launch offer: 60% off the annual plan for Product Hunt signups.
How are you pricing your agent today? I’ll be in the comments all day.
@Clocknext @vijayanandkailash Congrats on the launch flexible pricing and clear cost tracking really important for AI products usage grows
@Clocknext @shivam_kushwaha16 Thanks for the support!
Congrats on the launch Clocknext Team!
What is the target company? Does it work for small teams?
@mukesh_swamy All companies that build AI workflows can set their billing stack on Clocknext. We provide both billing infra and invoicing. So it is suitable to all the sizes.
@mukesh_swamy Thank you Mukesh! Means a lot.
Clocknext is for any company that sells LLM-based offerings to their customers.
It's a great fit for anyone looking to price their product based on credits, usage, outcomes, or even a combination of all of it!
The platform scales really well for small and big teams alike; it's intuitive and easy to pick up for solopreneurs selling MicroSaaS products, and also has the strong fundamentals in place for bigger teams to build complex billing frameworks on top of it :)
Hello Product Hunt 👋
This is Manish, one of the makers from the @Clocknext team.
We've been at it for months, and I'm super excited to be able to launch Clocknext to the PH community.
It felt like the right time to launch Clocknext because of how quickly we watched the AI ecosystem evolve in the months we spent building it.
Every day, I’d see new agentic products launch, especially here on Product Hunt. It kept us wondering whether these tools had the right infrastructure underneath to monetize their products well. Validation kept coming with every conversation we had with AI founders who were either retrofitting legacy subscription tools or building their own frameworks to manage billing.
We saw how much of a distraction this was, pulling focus away from delivering an exceptional product. So we decided to build a platform that is tailored to handle all of it.
So when you try Clocknext, you'll see a platform that helps you meter AI usage in real time, monetize it with the right pricing models for your agents, and give you clarity and control over the profits you make with each agent run.
There's a lot more to the platform and I hope you'll ask us all about it; leave your comments, questions, and feedback below - let's chat!
I've experienced how tricky it can get to manage pricing and billing, especially when usage keeps changing. Glad to see someone building a solution that addresses this. Wishing you and the team all the best! 🚀
@madhu_mita4 Thank you for the kind words, Madhu. Means a lot!
Seeing provider cost beside the customer price is useful when usage changes from run to run. I'd want to trace an unexpected cost back to the particular agent run that caused it.
@oleksii_sekundant We ensure you protect margin 100% irrespective of heavy-usage and light-usage customers. If underneath model is modified or provider cost is changed, you will get the real-time usage report where you are loosing the profit. With one-click adjustment on the margin, your profitability will be ensured.
@oleksii_sekundant Precisely! The biggest issue with a pricing model for AI is that customer usage can be so arbitrary, making it so hard to attach a fixed price on it.
We enable margin control on every agent run that takes place, so that you make margins on every run, regardless of fluctuating customer usage.
The biggest source of unexpected costs that founders usually bear comes with charging per outcome and owning the provider cost for failed attempts.
We capture signals for every sub-agent operating to achieve an outcome, so you can quickly identify what's burning tokens for you without generating revenue and take care of it.
If you'd like to chat more about this, just let me know! I'll set some time aside.
We are using clocknext internally here in superb. It’s never been easier than this to calculate and charge credits per workspace/customer. Congrats on the launch Clocknext team.
@iamsaravanaa Glad that we are able to manage all your pricing plans on Clocknext, which is based on "AI Credits". More to come on the customization of credit calculation and dynamically changing it at customer level.
Thanks for being one of our early adopters.
Congrats on the launch, @vijayanandkailash . How quickly can a team integrate Clocknext with an existing stack and how do you handle tracking usage for asynchronous or multi-step sub-agent workflows?
@vijayanandkailash @kevin Thanks a lot, Kevin! We couldn't have done this without you.
The integration process is very simple, and takes minimal engineering help to integrate with their tool stack.
We have two ways to handle multi-step sub-agent workflows:
Monetizing outcomes: Building an outcome entitlement that helps you bring a host of sub-agents that work together to deliver that outcome are defined and the price is baked in for the outcome as a whole. The outcome is tracked and is marked as delivered only when all of these sub-agents are successful.
Creating composites: This is something we built as a unique offering for people who still want to monetize multi-step agents without tying it to outcomes. You can bundle together sub-agents that are priced individually to build an action-focused agent, and customers are billed for how entitlements are consumed for each sub-agent.
looks cool!
@louislecat Thank you, Louis! Means a lot. 😄
Good luck with the launch!
@yenceesanjeev Thanks a bunch, Sanjeev! 🙏🏼
Congratulations on the launch 🎉
@bhavyasree Thank you for your support, Bhavya! Much appreciated.