AISynq
AI unit economics

How much does AI data extraction cost per record?

Pulling structured fields out of invoices, forms, emails or free text.

The short answer

Per call$0.0040
Per user, per month$1.60
Of a $99.00 price1.6%

On Claude Haiku 4.5, at 3,000 input and 200 output tokens per call. Small input, tiny output, very high volume. Four hundred calls per user per month assumes a back-office process running continuously rather than a person clicking a button.

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$0.0040
Per user, per month$1.60
That is this much of what they pay you1.6%
You can afford to spend$24.75

Using 6% 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. The cost per call is trivial and the monthly figure is not, which is the opposite of most features here and the reason extraction is where per-call optimisation actually pays.

Where the estimate goes wrong

Re-processing the same records. Extraction pipelines re-run on retries, on schema changes, and on backfills, and each re-run costs full price. Caching by content hash is the single largest saving available in this use case and it is almost always skipped.

What this does not price

Extraction is the use case most likely to be a deterministic problem wearing an AI costume. Where the documents are machine-generated and consistently formatted, a parser is cheaper, faster and does not hallucinate. Model the deterministic version before accepting any verdict here.

Other features people cost

Next step

If structured data extraction 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

A 30-minute call. No deck.