Document and data extraction

Stop retyping what you are sent

Invoices, contracts, delivery notes, application forms, supplier statements. If your business reads documents and types what it finds into a system, that is the most mechanical cost you carry and the easiest to lift.

Document extraction is where most UK businesses get their first genuine return from AI, because the work is high volume, obviously repetitive and easy to measure. The honest part of the pitch is accuracy: no extraction is right every time, so the design question is not "is it perfect" but "what happens to the ones it is unsure about".

Also sold as automated data capture, intelligent document processing, IDP, OCR and invoice automation.

What it actually does

The work it takes
off your desk

Purchase invoices into the ledger

Supplier, date, net, VAT, total, line items and purchase order reference, read and posted, with anything that does not reconcile held back for a person.

Key terms out of contracts

Renewal dates, notice periods, liability caps and payment terms pulled into a register you can actually search, instead of a folder nobody opens until it is too late.

Forms and applications into records

Whatever arrives as a PDF, a scan or a photograph taken on site, turned into a structured record without somebody transcribing it.

Delivery notes against orders

Matched line by line, with the discrepancies surfaced rather than discovered at month end.

What you would get

No surprises,
in writing.

Scope and price agreed before anything is built. If we think you do not need this, we will tell you that instead.

Get a quote
  • Extraction running on your real documents, not a clean sample
  • A confidence threshold agreed with you, and a review queue for everything below it
  • The structured output written into the system you actually use
  • Accuracy measured on your own documents before you commit further
  • A record of what was extracted from which document, for audit
The honest bit

Where this
goes wrong

Every supplier will tell you what their service does. These are the ways it fails, and what we do about each one. If a supplier cannot tell you this, they have not built enough of them.

Assuming an accuracy figure

Vendor accuracy percentages are measured on clean documents. Yours include a photograph of a crumpled delivery note taken in a van. We measure on your documents first, and tell you the real number.

No confidence threshold

A system that returns an answer for everything will confidently invent a VAT number. Everything we build scores its own certainty and sends the doubtful ones to a person.

Forgetting the review queue

The exceptions still need somebody. If the design has no queue, the exceptions end up in an inbox and the saving quietly disappears.

Losing the original

If you cannot get from a posted figure back to the document it came from, you have created an audit problem. Every extracted value keeps a link to its source.

Before you brief us

What everyone
asks us

Ask us anything

On clean, consistent documents it is very good. On photographs, handwriting and unusual layouts it is not, which is why the useful measure is what happens below the confidence threshold rather than the headline figure. We measure accuracy on a sample of your own documents before you commit.

PDFs, scans, photographs, emails and the structured formats your suppliers send. If a person can read it, extraction is usually possible; how reliably depends on how consistent the layout is.

Into whichever system you already use, so nobody has to check a second place. That is the point.

No. We never use your business data to train public models, and wherever possible the processing happens inside your own systems. We put the specific arrangement in writing for the setup we propose.

Start with
one job.

Tell us the task that eats the most time. We will tell you honestly whether AI is the right answer for it, and what it would cost to find out.

Get a quotation