Applied AI demo · built for Snout

A scanned vet invoice in.
A line by line plan verdict out.

Wellness plans live or die on a boring back office question: what did this clinic actually bill, and what does the plan owe on it? Below, a photographed or photocopied invoice is read by a vision model, every line is matched against a schedule of benefits, and the money is computed in ordinary code that has to balance before anyone sees it.

Pick an invoice

Three fictional invoices, deliberately messy. Or upload one of your own.

How it is put together

Judgement and arithmetic are separated

The model reads the page and decides which benefit a line belongs to. It is never asked for a dollar figure. Allowances, annual limits and every subtotal are computed in code, in integer cents, and the run reconciles: plan share plus discounts plus client balance has to equal the invoice, or the result is flagged instead of shown.

The plan is data, not code

Snout builds each plan around a clinic's own pricing and codes, so the schedule of benefits is handed to the matcher as text and read fresh on every run. A new plan, a clinic with its own item codes, or a mid year change to an allowance is a data edit. Nothing in the pipeline is hard coded to a particular clinic's item names.

It checks the invoice, not just itself

Each line is re-multiplied from quantity and unit price, and the extracted lines are summed against the total printed on the page. On the third sample those two numbers disagree, because the receipt itself does not add up. The run says so rather than quietly picking one.

Built to be argued with

Every verdict carries the sentence of plan wording it leaned on and a confidence, so a reviewer can disagree with a specific line instead of distrusting the whole batch. That is what turns this from a party trick into something a claims team will actually run.