AISynq
AI unit economics

How much does AI classification cost at volume?

Tagging, triaging or routing incoming items to the right queue or category.

The short answer

Per call$0.0014
Per user, per month$2.90
Of a $149.00 price1.9%

On Claude Haiku 4.5, at 1,200 input and 50 output tokens per call. A short item plus a label list in, one label out. The volume is what makes this interesting: two thousand calls a month is a queue rather than a person.

Your numbers

Now put your own in

The fields open with the profile above. Change them to match your feature and the read updates as you type.

Your numbers

Rough numbers are fine. You are checking whether you are near the line, not being exact.

Classification, extraction, routing. Anything where the job is narrow and the volume is high.

Everything you send it

What it sends back

How often one user uses it

$
%

List prices as at 19 August 2026

What it costs you

Each use costs$0.0014
Per user, per month$2.90
That is this much of what they pay you1.9%
You can afford to spend$29.80

Using 10% of what you can afford

The full answer

It pays for itself. See how much room you actually have.

  • The point at which this stops paying for itself
  • What it costs if people use it 2x, 5x or 10x more than you think
  • The same feature priced on every model, cheapest first
  • What to change, in the order worth changing it

We send you a copy, then roughly two emails a month. One click to stop.

What drives the cost

Volume alone. Per call this is the cheapest thing in the list, and at scale it is not free. It is also the use case where moving down a model tier changes the arithmetic most dramatically.

Where the estimate goes wrong

Using a frontier model because the first prototype used one. Classification is a narrow job and the cheapest model in the list usually does it at parity, at a twentieth of the cost. Where the verdict here is negative, the model choice is almost always the reason.

What this does not price

A rules engine handles the easy eighty per cent of classification for nothing. The honest comparison is not model against nothing, it is model against rules-plus-model-for-the-remainder, which is both cheaper and more predictable than either alone.

Next step

If classification and routing is on your roadmap and the number here made you pause, that is exactly the conversation worth having before an engineer starts.

Book the call

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