Launching today
Clocknext
Pricing and Billing Infrastructure for AI Agents
192 followers
Pricing and Billing Infrastructure for AI Agents
192 followers
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!
@Clocknext @vijayanandkailash oh no problem man
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.
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.
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 :)
@vijayanandkailash @arundesigns Thank you, Arun! That's a great question, because it's a dull pain that founders hardly recognise until it eats into their revenue.
Some strong trigger points we've seen with AI founders that push them towards a solution:
Current solutions in the market are still traditional, where they realise that they're trying to fit the product's pricing strategy to the tool, rather than the other way around, where the tool supports the ideal pricing strategy
In-house billing setups they have, become increasingly troublesome to maintain and scale as they onboard customers
Founders have no clue whether a customer they've signed is actually making them money until the end of the month, when they may have already lost revenue
Margins per customer is the metric most AI apps don't have until it's too late. How do you handle a single user action that fans out to several model calls with different providers, do you attribute the combined cost back to that one action or does it show up as separate line items?
@galdayan Exactly, Gal. A lack of visibility into margins per customer can hurt, especially when expensive models and high usage numbers are in play!
Clocknext solves this by handing complete control over how each user action is monetized.
Raw usage is captured in real time as signals.
You can create entitlements like credits, outcomes, and more, and define exactly how the customer's signal should be monetized, what models are being used, and what margins go along with each of them.
So regardless of what model or what provider a user runs, you make margins.
On top of that, cost attribution comes back to you as a single line item when you combine it as an outcome or composite. You can also bill them as separate line items by keeping them as individual entitlements.
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!