The rise of AI agents is shifting how software services are consumed and so it is also changing how they need to be priced.
The traditional seat-based model relies on a simple idea: one human user equals one license.
Seat-based pricing doesn’t make sense in an economy with a growing population of agents that work 24/7 and outnumber the customers that run them against your APIs. More and more companies are following Mintlify’s lead – moving away from seats to usage-based pricing.
Usage-based pricing is a challenge to bolt on to an existing product. So we’re going to give you a quick overview of what you’ll be looking at, starting with – does usage-based pricing even make sense for your product?
Does Usage-Based Pricing Even Make Sense for Your Product?
The first step in deciding if you’re going to move to usage-based pricing (UBP to save typing) is to look at your industry and your competitors. Is it already common? Are others making the shift? If they are, adopting a similar structure can help you remain competitive. If they’re not, you might have a strategic window to capture some market share if your UBP can give potential customers the cost flexibility and lower adoption costs then you’re competitors can.
Next, you have to look at your product and ask yourself these three questions:
1. Can you actually break down usage into units?
What you’re going to be billing needs to relate directly with the value your customers are getting from your product. If you’re MailChimp you charge for sending emails and give templates away for free. Paying more money to send more emails makes sense to their customers.
Time can be a unit. If you’re AWS or Google you charge your customers based on the time they spend running their services on your hardware (plus many other things).
2. Can customers easily predict their usage requirements?
While customers want flexibility, they also hate unpredictable bills. This is why there is an interesting trend in enterprise software: multi-year contracts growing from 23% to 38% of agreements. They aren’t doing this for discounts, they’re locking in predictability, especially if AI-powered features are involved.
3. Are the usage and value of your products/services increasing?
If your customers are getting more value the more they use your tool, UBP allows your revenue to scale with their success.
Finally, consider your product. Do you need to develop entirely new features or services around your current offerings to make usage-based pricing make sense or are you ready to go?
How Do You Structure Usage-Based Pricing?
If you decide to move forward on UBP, you need to choose the right pricing structure. There are four primary variations to consider:
Variable Pricing: This model is based entirely on consumption. The most common example today is token-based pricing for AI models, but it could also apply to the number of reports generated, resolved customer support complaints (a model used by Intercom), or fraud predictions. This is typically managed via a credit-based system. Customers are given a default monthly credit allowance to help smooth out your revenue fluctuations, and they can buy more credits as their consumption increases. This is how platforms like Lovable handle their billing.
Tiered Pricing: Under this model, different unit costs apply as usage passes specific thresholds. Tiered pricing allows customers to maintain control over their budgets while ensuring your margins remain positive. It also lets you offer volume discounts to your largest accounts. The downside is that too many tiers confuse buyers, while too few make the price jump between tiers painful.
Dynamic Pricing: In this structure, prices shift in real time based on market conditions and demand. Uber’s surge pricing is the most familiar example of this model.
Per-Feature Pricing: Similar to variable pricing, this model charges customers only for the specific features they activate and use, often tracked via a credit-based system. This gives your customers complete autonomy over their costs, allowing them to balance the price-to-value equation themselves.
How Do You Deliver Usage-Based Pricing?
Building the technical infrastructure to support usage-based pricing is a significant engineering challenge. You will face three distinct hurdles: metering, storing, and implementation.
1. Metering
You must record consumption data exactly where it happens, whether that is API requests, token counts, or raw compute time. The recommended approach is “fire-and-forget”: your application code should emit a single billable event to your metering system the moment a transaction occurs.
For continuous workloads, like long-running background jobs or continuous compute, tracking start and end events is risky because data can be lost if a system crashes mid-job. Instead, use a “heartbeat” approach, where the active workload sends a heartbeat record to the metering system at regular intervals.
2. Storing and Processing
This is where you enter the world of data warehousing and complex stream processing. To provide real-time billing updates, you cannot simply dump records into a database and run batch jobs overnight; that leads to stale data. Most modern platforms rely on Kafka-based streaming architectures to process usage events in real time.
This data must be auditable. You cannot do this by halves, accuracy is paramount. If you are sharing revenue with partners or dealing with billing disputes, you need an audit trail that captures and tracks every single billable event.
Also, don’t treat usage data purely as an input for invoices. Your sales, product, customer success, and finance teams can all use access to this data. Real-time usage patterns can help sales spot upsell opportunities, help product teams track feature adoption, and help customer success flag accounts where dropping usage signals a risk of churn.
If you’re already tracking usage data for these purposes then lucky you, you’re already part way there.
3. Implementation
You do not have to build all of this billing infrastructure from scratch. There are lots of service providers out there already. You just need to instrument your code with those “fire-and-forget” messages to hit their databases and they give all the other tooling you need.
Here’s 3 examples:
Moesif: This platform specializes in metered API billing. It connects directly to API gateways like Kong or Tyk and integrates with payment processors to automate usage tracking and billing.
Stripe: In addition to standard subscription billing, Stripe supports complex usage catalogs (including models used by companies like Anthropic. They also offer an LLM proxy endpoint (in private preview), which automatically tracks token usage, applies your pricing markup, and handles invoicing in a single request.
Chargebee: offers usage-based billing features designed to separate your raw usage data from your pricing logic, making it easy to run experiments and iterate on your pricing tiers.
What to Watch Out For When Moving to Usage-Based Pricing
While the benefits of UBP are clear, the transition introduces real business risks that you need to manage.
The biggest challenge is revenue fluctuation. Unlike flat-rate subscriptions, your MRR will go up and down. To mitigate this, most companies use a hybrid pricing model. For example, you might charge a base subscription of $20 per month that includes 1,000 credits, and then charge a variable rate for extra credit purchases.
Another major risk occurs when you bill for consumption in arrears (charging after the usage has occurred, similar to AWS or Google Cloud). If an AI agent or a poorly written loop in a client’s code runs out of control, it can burn through thousands of dollars of spend. This leads to “bill shock,” which can ruin customer relationships or even bankrupt a small client.
Finally, remember that you are exposed to broader economic conditions. If your customers experience a business slowdown, their software usage—and your revenue—will drop alongside theirs. You may also face higher delinquency rates during market downturns.
Keep in Mind: Your Customers are Still Human
Even if AI agents are driving the usage, the person signing the contract and paying the bill is still a human. Humans require transparency, predictability, and clear communication. If you transition to usage-based billing, you must provide your customers with the tools, dashboards, and real-time alerts they need to monitor and manage their own consumption.
AI agents are changing how SaaS are run and valued. The traditional seat-based model is on its way out. While building the infrastructure to support usage-based billing is complex, we should be relieved we have a challenge that is straightforwardly solvable.
The alternative, in a world where people talk about using AI to build inhouse versions of the services they pay for, is not having a business at all.
