Monitoring spend does not save money on its own, but it enables everything else: without measuring cost per task, per user and per endpoint, you do not know where you are overpaying and you optimize blind. What you do not measure, you cannot optimize.
The three metrics that matter
| Metric | What it reveals | What it is for |
|---|---|---|
| Cost per task | What one real unit of work costs | Comparing models and deciding routing |
| Cost per user | Who consumes and how much | Spotting abuse and setting prices |
| Cost per endpoint | Which part of the product eats the spend | Knowing where to apply the levers |
Cost per task
This is the root metric: what it costs to solve one unit of work that means something to the business —classifying a ticket, generating a listing, answering a query—. In money per task, not in tokens. It is the only thing that lets you compare models honestly and justify a change. We develop it in cost per task.
Cost per user
Split the spend across the accounts generating it. It serves two purposes: spotting the handful of users who concentrate a disproportionate share of consumption, and setting prices that do not leave you at a loss on the top plans.
Cost per endpoint
Split the spend across your product’s features. There is almost always one that takes the largest share, and it is usually not the most used one: it is the one dragging the most context or calling the large model. That is where to apply the 7 saving levers first.
How to start without building anything
You do not need a platform. Tag every request with three fields —task, user, endpoint—, store the input and output tokens the API returns, and aggregate it in a table. That already gives you the three metrics. If you want an estimate before instrumenting, the token cost calculator gives you the order of magnitude in a minute.
Frequently asked questions
Which metrics should I track to control AI cost? Three: cost per task, per user and per endpoint. The first lets you compare models, the second spot anomalous consumption and set prices, the third know where to optimize first.
Is looking at the provider’s bill enough? No. The bill gives you the total, not the breakdown. Without knowing which task, which user and which endpoint generate it, you cannot act on it.
How often should it be reviewed? Weekly during the first months and after every model or prompt change. AI spend drifts fast when usage changes.
At e-ficient we measure the cost per task of companies that already run AI in production and tell you how much you would save with each lever at your real volume. The first audit is free if you start a plan with a three-month commitment and returns a diagnosis within 72 hours.