You sell fixed, seat-based, or tiered plans
Customer revenue is relatively stable while AI usage can vary dramatically.
See which customers cost you more in AI than they pay you.
paiment connects AI costs with customer revenue, plans, and workflows so you can spot margin erosion, find what is driving it, and see where profitability is heading before month-end.
Built for post-revenue AI SaaS teams with fixed, seat-based, or tiered pricing and variable AI usage.
Customer economics at a glance
See revenue, AI cost, margin, and trend direction per account — not just your provider bill.
| Customer | Revenue | AI Cost | Margin | Trend |
|---|---|---|---|---|
| Maria Alves | €2,000 | €640 | 68% | Stable |
| James Kessler | €1,500 | €1,190 | 21% | ↓ 8% |
| Priya Nair | €800 | €940 | -17% | Critical |
Trend reflects margin direction from recent usage — illustrative example.
Built for AI SaaS where customers pay predictably — but cost unpredictably.
paiment is designed for post-revenue teams whose AI product has real customer usage, variable cost-to-serve, and no dedicated FinOps or internal allocation system.
AI is part of the product people actually pay for
Not a side chatbot. A core workflow, agent, document process, generation flow, or service.
Some customers use far more AI than others
One account, team, or usage pattern can cost multiples more than another on the same plan.
You are big enough for the problem to hurt — but too small to build around it
Real customers. Real COGS. No dedicated FinOps team or custom cost-allocation engine.
Especially relevant for document-heavy LegalTech, RegTech and professional AI, AI support platforms, B2B creative generation, product imagery, dubbing/localization, and selected agent products.
The total AI bill does not tell you which customer is breaking the economics.
01
Averages hide loss-making customers
Ten low-usage accounts can make the customer base look healthy while one heavy account quietly consumes the margin created by the rest.
10 customers€3–€18 AI cost each
1 customer€612 AI cost
Average looks acceptable. One account is not.
02
Growth can make a customer less profitable
In traditional SaaS, more usage is usually good news. In AI SaaS, a customer paying €500 can create €600 in model cost simply by using the product more intensely.
Customer revenue€500
AI cost last month€180
AI cost this month€437
TrendHeading toward €612
03
Month-end tells you after the margin is gone
A new feature, model change, or usage spike can damage customer economics for weeks before the provider invoice makes the problem obvious.
Day 3Usage shifts
Day 8Cost accelerates
Day 18Customer margin turns negative
Month-endTeam finally reconciles the bill
From AI spend to a decision you can act on.
paiment turns variable AI usage into customer-level economics, then shows what is changing and where to investigate.
01
Connect
Connect every AI cost to the customer, account, plan, product, or workflow that generated it.
- Know real margin per customer — see customer revenue and AI cost-to-serve together, continuously.
- Compare economics across the business — understand profitability by customer, plan, product, model, segment, or workflow.
02
Diagnose
See what is eroding margin, why it is happening, and where profitability is heading.
- Find what is driving the loss — drill into model, provider, workflow, feature, usage pattern, or account behavior.
- See where margin is heading — track cost and profitability trends before the invoice arrives.
- Catch abnormal consumption early — detect unusual usage before one account burns through expected margin.
03
Act
Turn profitability signals into concrete product, pricing, and account decisions.
- Protect margin before the damage compounds — reprice an account, change model mix, introduce usage limits, investigate abnormal behavior, or intervene before month-end.
- See whether the change actually worked — compare cost and margin before and after a pricing, model, routing, or product change.
Cost tracking tells you what AI cost. paiment shows what that cost is doing to the customer economics.
AI provider dashboard
How much did we spend?
LLM observability platform
Which requests, users, or models created the cost?
paiment
Which customer or plan is losing economic value, why is it happening, and where is it heading?
paiment does not ask you to replace your gateway, billing system, or cloud stack. It connects the data needed to understand customer-level AI economics.
Connect the systems that already know your costs and revenue.
Keep your existing AI provider, billing system, and product stack. paiment brings the relevant signals together at customer and account level.
AI cost
- •OpenAI
- •Anthropic
- •More providers — talk to us
Revenue and plans
- •REST API subscription sync
- •TypeScript & Python SDK
- •Stripe and other billing — via your webhook → paiment API
Customer context
- •TypeScript SDK
- •Python SDK
- •REST API
- •Outbound alert webhooks
Your application identifies the customer, account, plan, or workflow behind the usage. paiment connects that context with cost and revenue signals.
Proof from real customer economics.
AI-powered portfolio and proposal platform for real estate agents.
Pilot case studyFinding the workflow that was quietly eroding margin
Before
The team could see provider spend and approximate cost, but not reliably connect the economics to individual users, plans, and core product behavior.
paiment revealed
One user and one core workflow were creating a disproportionately large cost event.
What changed
The team investigated model choice, payload size, and the information being sent to the model, while also revisiting pricing assumptions.
Result
Pilot findings in review — quantified results to be published with customer approval.
Full quantified results pending customer approval — see Resources for updates.
View case studies →Start with one month of real customer economics.
Connect a focused slice of your AI business and use 30 days of real usage to see where customer economics are drifting.
Connect
One AI provider, relevant customer/account context, and the revenue or plan data needed for analysis.
Observe
Track customer and plan economics as real usage changes.
Investigate
Identify expensive accounts, workflows, anomalies, and margin drift.
Review
End with a structured economics review of what changed, what is driving it, and what the team may want to test next.
Best for post-revenue AI SaaS teams with active customer usage.
FAQ
paiment is best suited to post-revenue AI SaaS teams where AI is part of a core paid workflow, usage varies materially across customers or accounts, and revenue is fixed, seat-based, tiered, or only loosely tied to actual AI consumption.
Find the customer that looks healthy until AI cost is included.
Connect usage, revenue, and customer context to see where economics are already drifting — and where they are heading next.