Part of
AI implementation for business

Nobody should be retyping data out of a PDF

This is work that can be counted in hours per week and whose effect can be measured in errors avoided.

One of the few AI use cases where the return shows up in the first month.

Who it's for
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Who this is for

  • Teams where somebody retypes invoices or orders into a system
  • Companies receiving documents in many formats from many suppliers
  • Departments buried in documents to read and classify
Scope
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What it covers

Recognising the document type

Invoice, order, report, contract — separated automatically on intake.

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Sorting at the door is usually a bigger saving than the extraction itself.

Field extraction with a confidence threshold

Number, dates, amounts, counterparty, line items.

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Every field with a confidence score — anything below the threshold goes to review rather than into the system.

A path for unclear cases

A review screen with the document beside the extracted data.

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This is the part whose absence turns automation into a source of errors harder to catch than the manual ones.

Wired into the target system

Data lands where it was going anyway — in the ERP or the document flow.

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Without that step the project ends in a CSV somebody has to import.

In depth
In depth

How we calculate the case

Documents per month times the time to retype one, minus the time spent reviewing cases below the threshold. That simple difference is usually enough to decide, and it can be worked out before the project starts.

Where we start

With a representative sample, not the tidiest documents. Rollouts like this break on edge cases, so the sample has to contain them — otherwise the accuracy measurement is worthless.

Questions
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Questions about this scope

How accurate is it?

It depends on the quality and consistency of the documents, and we don't give a figure before testing on yours. We usually start with a sample of a few hundred — measuring on those is cheaper than any claim made in advance.

What happens when it gets something wrong?

That is what the confidence threshold and the review screen are for. Automation without a path for doubtful cases pushes errors deeper into the process, where they cost many times more than at data entry.

Will it handle scans and photographs?

Yes, though input quality translates directly into the result. With documents photographed on a phone, the cheapest improvement is usually changing how they are received, not a stronger model.

Got an idea? Let's talk.

The first call is free. We reply within one business day.