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Stage 1
Send us what you have
PDFs, ERP exports, portal downloads, spreadsheets. API connectors are available for most ERPs.
Know what you buy, from whom, at what price.
Your invoice data is full of answers. Pearstop makes them usable. Your data doesn’t need to be cleaned first. That’s the work we do.
Trusted by leading organisations
“Most companies are flying blind, and only find out when someone asks a question they cannot answer.”
Procurement Lead, Infrastructure“You cannot negotiate what you cannot see.”
Head of Procurement, Facilities Management“If you cannot defend your cost baseline, you are bidding on a feeling.”
Commercial Director, Construction
See it work on your own data
Send a representative sample of your invoice lines – up to 200 lines, or a handful of invoices (max 10) – and we'll classify them and send them back labelled. No cost, no setup, nothing to install. It's the fastest way to see exactly what Pearstop does before you commit to anything.
How it works
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Stage 2
We clean, enrich, and classify every line
We extract everything we can find on the line, fill in what’s missing using supplier and purchasing history, and classify it to UNSPSC – down to the granularity that actually answers your questions, not just a top-level category.
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Stage 3
Your spend stays classified
As new invoices arrive, they're classified the same way - no re-cleaning project every year.
| As it arrives | What Pearstop adds | ||||
|---|---|---|---|---|---|
| Invoice description | Supplier | UNSPSC | Category | Unified supplier | Confidence |
| PMP FLTR 20X24 CS/6 | AAF INTL | 40161505 | Air filters | AAF International | High |
| FILTER,AIR,20X24,MERV8 | AAF FLANDERS | 40161505 | Air filters | AAF International | High |
| Air Flt 20x24x2 (6/box) | AAF | 40161505 | Air filters | AAF International | High |
| GEN PURP CLNR 5L | ISS FACILITY | 47131805 | General purpose cleaners | ISS Facility Services | High |
| Multi-surface cleaner 5ltr | ISS | 47131805 | General purpose cleaners | ISS Facility Services | High |
| Additional hours | M&P CONTRACTING | 80111613 | Temporary manual labour* | M&P Contracting Ltd | Medium |
Illustrative example: six invoice lines from three suppliers. The original description and supplier are kept exactly as they arrived – Pearstop only adds the columns on the right.
* Category inferred from additional data (purchase history and contract context), not stated directly on the invoice — flagged at medium confidence rather than high.
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.
SegmentFamilyClassCommodity
Healthcare services$37,592
Office equipment and accessories$29,578
Domestic appliances and supplies$28,880
Cleaning equipment and supplies$25,921
Paper materials and products14000000 · $25,438
Distribution and conditioning systems$24,968
Personal and domestic services$23,838
Paper products14110000 · $25,171
Industrial use papers$267
Personal paper products14111700 · $24,905
Printing and writing paper$267
Toilet tissue14111704 · $16,751
Paper towels$7,417
Paper napkins or serviettes$737
BreakdownToilet tissue$16,751 · 300 lines · 14111704
Suppliers
Bunzl CHS$6,579 · 212 lines
Nordhall Hygiene$6,299 · 61 lines
Castleford Supplies$2,718 · 18 lines
Kestrel Facility Products$1,156 · 9 lines
Line items
DescriptionQtyUnitTotal
Toilet roll, case of 36Bunzl CHS
12case$292.61TLT TISSUE 2PLY 9PKNordhall Hygiene
30pack$217.17Loo roll 2ply x48Castleford Supplies
6box$164.59Toilet rolls (24)Kestrel Facility Products
10pack$188.98See it in action
How Pearstop extracts, classifies, and normalizes supplier and spend data.
Who it's for
Facilities Management
Your data arrives from every service line in a different format.
See how it applies →Construction
You're estimating bids from memory because nobody can retrieve historical actuals.
See how it applies →Infrastructure
A savings target has been named and the data can't show where it sits.
See how it applies →Manufacturing
One entity already runs UNSPSC and another needs to align to it.
See how it applies →“Our data isn’t clean enough for this.”
That's the most common thing we hear – and it's the reason to start now rather than wait. Cleaning the data is the first thing Pearstop does, not a prerequisite for working with us.
“Won’t it be cheaper to build this ourselves?”
In-house gives you complete control, but expect to dedicate two data or AI specialists to build it properly and keep maintaining it as your data changes. We've seen an internal build start as an IT team's side project, ship without procurement involved, and turn into a spreadsheet nobody owns within months. Pearstop is that system already built – with a team whose only job is to keep developing it.
Cases
Infrastructure Contractor
A named savings target. The data couldn't locate it. Pearstop made it visible.
“We used to have two full-time staff working on category assignment. Now the system does this for us – which has unlocked margin estimations further down the line too. It's more reliable at a fraction of the cost.”Head of Procurement, Infrastructure
Read the case →Facilities Management Provider
9,175 → 1,493 supplier variants consolidated across 204,029 asset records. 73.1% confirmed matches.
“Our asset lists worked for mechanics on-site, but did not allow us to plan smart maintenance or manage bid risk in a data-driven way.”Asset Manager, Facilities Management
Read the case →Cleaning Services Company
~300. invoices a month
“It would have taken five engineers and a full year to clean this up. So we decided to look for a better solution.”Head of Operations, Cleaning Services
Read the case →Send us 200 lines. We will send them back labelled.
The question we get most
We already tried ChatGPT or Copilot on our data - why would this be different?
Because Pearstop isn't a general-purpose AI tool pointed at your data - it's a dedicated pipeline built specifically for procurement and asset data: deterministic matching first, a large language model for the genuinely ambiguous cases, and a human review step for anything still uncertain. Teams who've tried a general AI tool on messy spend data consistently find it works fine in a quick trial and breaks down at real volume. Pearstop is built to hold up at that volume, not just in a demo.
Frequently asked questions
What does Pearstop do?
Pearstop helps facilities management, infrastructure, and hard services companies clean procurement and asset data so teams can see what they are buying, plan maintenance more reliably, and feed trustworthy data into AI and reporting tools. If you need one plain answer, it is this: we turn messy operational data into something your business can actually use.
What is UNSPSC classification?
UNSPSC is a global standard for categorising products and services into a consistent hierarchy. It lets you compare spend across suppliers, sites, and time periods using the same categories, instead of whatever free-text description each invoice happened to use.
How do you classify spend data that isn't clean?
Your data doesn't need to be clean first - that's the work we do. We take invoices, ERP exports, portal downloads, or spreadsheets in whatever state they're in, and extract and classify every line automatically.
Can you extract data from PDF invoices?
Yes. Pearstop reads PDF invoices, scanned documents, and portal exports directly, so you don't need a clean digital export to get started.
How accurate is automated spend classification?
Around 95% of lines are classified automatically. The rest are flagged and routed to a human reviewer, so accuracy stays high without every line needing manual checking.
How long does spend classification take?
A first sample of 200 lines is typically turned around within a few working days. Ongoing classification runs continuously as new invoices arrive.
