Traffic that does not convert
The campaigns work. The page they land on undoes the work.
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A person reads a document and types what it says into a system, every day.
Invoices, delivery notes or forms arrive as PDFs and scans
Someone opens each one and copies fields into software
Mistakes surface weeks later during reconciliation
Nobody can say how many documents came in last month
This is the single most common shape of work we are asked about, and it is rarely described as an AI problem when it arrives. It is described as being short-staffed.
The cost is not only the typing. It is the delay between a document arriving and the business knowing about it, the errors that are found long after the fact, and the fact that the knowledge of how to read these documents lives in one person's head.
We watch the actual task before designing anything — which fields matter, which are ignored, what a difficult document looks like, and what they do when something is ambiguous. That last one becomes the review rule.
We take a sample of real documents, including the awkward ones, and label the correct answer. Nothing goes to production until it scores acceptably against that set, and the set stays as the regression test.
Documents are read into typed fields and written to the system of record. Anything the model is not confident about stops in a review queue instead of being written and quietly being wrong.
Every correction a reviewer makes is captured as a new evaluation case, so the queue gets shorter over time rather than staying constant.
Deliberately no percentages here. What a change is worth depends on your volumes and your costs, and we would rather work that out with you against your own numbers than quote someone else’s.
The campaigns work. The page they land on undoes the work.
Read →Sending more email to a decaying list, and wondering why replies dried up.
Read →Thousands of contacts, and a sales team that does not trust any of them.
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