If nobody reads the invoice, the data inside it does not exist.
PDFs, scans and delivery notes arrive faster than anyone can read them. Pearstop turns that paperwork into structured, labelled line items automatically.
Every invoice is a record of work done on a site. If nobody reads it, nobody can check it.
Why spend data stays unusable months after the invoice arrives
Our internal systems are lacking. I'd say we're at ground level. Somewhere underground.
Every supplier lays out an invoice differently. The same supplier changes layout depending on the depot or system that sent it. Plenty still arrive as a scan or a photo of a paper delivery note. Someone has to read each one before anything can be categorised, compared or reported on. At volume, that step becomes the permanent bottleneck.
Unread in the inbox
One supplier, many layouts
A cycle behind
Stale on arrival
From unread document to classified line item
Ingest, in any format
No fixed template per supplier, and no supplier has to change how they send anything.
Read, labelled and checked
Line items, quantities and unit costs are structured, and every line gets a standard label (eg. UNSPSC), so the same item compares one-to-one across suppliers. Your own labels can sit alongside. Anything uncertain goes to a person, and each correction teaches the pipeline that supplier.
Structured output, ready to use
See it in Pearstop's dashboards, or send it back into SAP or any other ERP, P2P or BI tool, in the format each one expects.
What comes out the other side
Every line gets the same columns, whatever the supplier's layout. The one line we could not read with confidence goes to a person instead of into your data.
| Description | Qty | Unit | Unit cost | Cost code | Supplier | Status |
|---|---|---|---|---|---|---|
| Toilet roll, case of 36 | 12 | case | £19.20 | CC-4410 | Bunzl CHS | Read |
| Multi-surface cleaner 5L | 8 | each | £6.45 | CC-4420 | Bunzl CHS | Read |
| Nitrile gloves, medium, box of 100 | 20 | box | £4.10 | CC-4520 | Bunzl CHS | Read |
| Delivery charge, site 14 | 1 | each | £12.00 | CC-9100 | Bunzl CHS | Read |
| Handwritten amendment: +2 mop heads | 2 | each | unclear | n/a | Bunzl CHS | To review |
The same label on every supplier's line
Each line gets a UNSPSC label as it is read. Toilet tissue from four suppliers ends up in one place, so you can compare it one-to-one.
What becomes possible once the invoice is read
Spend visible the same week
Ready to compare
No more keying and correcting
Invoices checked against the contract
“Doing that manually absolutely has its own risks. It might be borderline impossible at this stage while keeping operations going.”
What is invoice data extraction and why does it matter for procurement data quality?
Invoice and document data extraction is the process of automatically reading PDF invoices, scanned paper records, and delivery notes, then converting them into structured, classified line-item data. For facilities management, construction, and manufacturing procurement teams, this is the step that has to happen before spend analysis or reporting is even possible — at Pearstop, classification (UNSPSC or a client's own taxonomy) happens in the same pass as extraction, not as a separate project afterwards. Manual data entry cannot keep pace with invoice volume across multiple sites and suppliers, which is why unread invoices and stale spend data are one of the most common blockers to category management and AI-driven spend analysis. Pearstop combines OCR with an AI extraction layer and a human review step for low-confidence lines, so the output is structured, classified data, not another manual bottleneck.
Frequently asked
Can Pearstop extract data from scanned paper invoices, not just digital PDFs?
Yes. The extraction layer handles digital PDFs, scanned paper documents, photographed delivery notes, and email attachments. It does not require a fixed template per supplier, which matters because most procurement teams receive the same information laid out differently by every supplier, and often differently by the same supplier month to month.
How accurate is automated invoice data extraction?
First-pass accuracy depends on document quality and supplier variability, but improves over time. On one cleaning services client's invoice stream, first-pass extraction accuracy rose from roughly 70% to 99% as the pipeline learned that supplier base's formats and edge cases. Anything below a set confidence threshold is flagged for human review rather than guessed at.
Does extraction replace our ERP, or feed it?
It feeds it. Pearstop extracts and structures the data, then delivers it in the format your ERP, P2P platform, or BI tool already expects, so it plugs into what you run today (SAP, Oracle, Business Central, and others) rather than requiring a new system.
Still keying invoices in by hand?
Send us up to ten invoices, in whatever state they are in. We send them back as structured line items, so you see your own invoice stream read.
