The account coding your customers asked for

Kaunt codes every invoice line — GL account, cost centre, VAT code, any dimension your customers use inside your platform, under your brand. You ship the feature. We run the AI.

API-first
Proprietary models
EU/US/Canada regions
Acme Facility Services INV-88214
Nov 2026 · EUR
Cleaning services12 400,00
Window cleaning8 900,00
Waste handling27 020,00
#LineGLCost c.ProjectTax
Coding accuracy

>98%

Across GL accounts, cost centres and any customer-defined dimension. It improves the longer it runs.

Time to value

<24hours

From the first historical data upload to live AI coding predictions.

Setup

0rules

Historical data is the only input. Nothing to template, nothing to map.

—Embedded AI

Your interface. Your brand.
Our intelligence

Ship AI account coding as part of your own product. Kaunt's coding interface drops into your screens under your own branding, so your customers never leave your platform. No second login, no other vendor's logo.

Your platform
Kaunt embedded UI
sits here
Kaunt · embedded
Coded by Kaunt
#LineGLCost c.ProjectTax
under Sample Ledger’s branding — same embedded UI, same call
  • One iframe tagNothing to bundle and no SDK to keep up to date. Improvements ship without you releasing any frontend code.
  • Keys never leave your serverAPI keys stay server-side. The browser only ever gets a short-lived, revocable token, scoped when it is issued and never widened.
  • Whole workflowsNot just widgets — validation, preview and the audit trail come with the embedded UI.
Or use no interface at all

The embedded UI is optional, not the product. The same call powers a fully headless integration behind your own screens — same proposals, same response, same model. Nothing about the coding changes because you chose to build the interface yourself.

With UI One iframe tagwe render the embedded UI
Headless One REST callyou render whatever you like
—Live in 24 hours

Send historical data. We do the rest

Upload your customers' historical invoices and postings, and training starts on its own. There is nothing to configure, because the history is the configuration.

Step 1 Send the history Your customers' existing invoices and postings. That is the whole input — nothing to template, nothing to map.
Step 2 Training starts on its own Kaunt automatically begins training a model for that customer. Nobody configures anything, because there is nothing to configure.
Step 3 Predictions go live Real-time GL accounts, VAT codes and any customer-defined dimension, over the same REST call you already integrated.
Step 4 And it keeps going Every posted invoice comes back and teaches that customer's own model — on its own, in the background.
No rules to write. And none to maintain.

Rule sets rot. Every new vendor, every reorganisation, every change to the chart of accounts is another rule somebody has to own — and somebody has to remember why it was written. There is nothing here to own. The history is the configuration, so it updates itself every time your customers post.

—Continuous learning

Every correction makes the next proposal better

When one of your users changes a code, that correction goes straight back into that customer's own model. The next invoice from the same vendor arrives already carrying the corrected code, at a higher confidence. No retraining request and no release on your side — the next invoice simply knows.

Their own model
coded proposals
posted results
Your customers

it follows how each customer actually works

.xml .pdf .png .jpg .tif .json
Kaunt AI Engine
—Any format

An .xml, a .pdf, a photo.
One proposal.

Structured XML, PDFs, scans, phone photos, your own JSON — however the invoice arrives, you get the same coded lines back. Leave the format to us.

—Confidence you can act on

We tell you how confident we are. You decide what happens

Every proposal comes back with a confidence on each dimension it predicted — HIGH, MEDIUM or LOW. The model knows the difference between a line it has seen a thousand times and one it is guessing at, and it says so. What each band should mean in your workflow is your decision, not ours.

High many close matches in that customer's posting history
Medium some matches, but fewer
Low few or no close matches

what happens next is entirely your call

Driver
Reconciles
—Advanced postings

The difficult postings,
proposed too

Most invoice lines post to a single account. The exceptions are where the time goes. Kaunt proposes the split as well as the code — freight across the goods it relates to, a shared service across cost centres, a subscription across twelve months.

—Posting text

Posting text written the way your customers write it

Kaunt composes the posting text from the invoice line itself — the vendor, the description, the date, the amount — in each customer's own house style: their length, their word order, their abbreviations.

One invoice line, exactly as it arrives
written in each house style
—A model per customer

Trained on their data. Only theirs.

Kaunt trains a separate model for each of your customers, on that customer's postings alone. Nothing is pooled — one customer's data never reaches another customer's model.

—Built API-first

One REST call. Nothing else required.

A standard REST API, documented the way your developers expect, with no SDK to adopt and no proprietary protocol to learn. Authentication, pagination and error handling behave exactly as your team expects.

api.kaunt.com
GET /v1/tenants/{tenantId}/companies/{companyName}/invoicecodingproposals/{id}
200 OK —

    

Ship AI coding, not an AI team

We build the AI so your team can ship the platform. Get an API key and code your first invoice today.