Invoice & document processing
Incoming invoices and documents are manually reviewed, categorised, and routed.
Eighty percent of incoming documents have an identical structure. Yet every document is opened individually, read, and entered by hand. That is a solvable problem.
The problem
Organisations processing dozens to hundreds of incoming invoices, order confirmations, or forms each month — trading companies, accounting firms, property managers — spend considerable time on manual document handling. A staff member opens each document, reads the relevant fields, enters them into the system, and routes to the right person or department.
As volume grows, the backlog grows. Hiring more people to handle this work is the most common response — and the most expensive.
What the audit reveals
What an audit in this type of environment almost always reveals: the vast majority of documents follow a near-identical structure. Eighty to ninety percent of the processing is routine work that can be automated based on fixed patterns.
Human attention is being directed at documents that require none, at the expense of the exceptions that do. That is the core of the problem — not the volume.
The approach
Implementation of document recognition that automatically reads and validates relevant fields. Documents matching the expected structure are processed and routed without human intervention. Deviations — missing fields, unusual amounts, unknown senders — are flagged for review.
The accuracy of trained models for structured documents such as invoices and order confirmations typically falls between 95 and 99 percent. The remaining one to five percent are precisely the cases that deserve human attention.
What to expect
Organisations that address this pattern typically report:
Accuracy
95–99% for structured documents
Processing time per document
From minutes to seconds
Human attention
Shifts entirely to exceptions