AI Invoice Matching That Doesn't Need Babysitting
Your accounts team spends hours every week opening supplier invoices, comparing them line-by-line to purchase orders, checking quantities against delivery notes, and arguing with the finance system when something doesn't balance. We build AI that does all of that — and only escalates the cases that genuinely need a human.
The promise
Where it hurts
The real friction we hear about.
PDFs arrive in every shape and format
Every supplier has their own invoice layout. Some are PDFs, some are scans, some are Excel files emailed with no body text. Off-the-shelf AP tools struggle when the format drifts.
Three-way matching is mostly clerical
Invoice line → PO line → delivery note. The rules are mechanical but the variations are infinite. Your most experienced person is doing data entry that a machine could finish before they've opened the email.
Discrepancies still need a human — eventually
Wrong price, short delivery, sneaky carriage charge, VAT rate mismatch. You don't want AI silently approving these. You want it to flag the right ones to the right person, with context.
Your finance system doesn't want to play nicely
Sage, Xero, QuickBooks, custom ERPs — getting clean data in is the easy part. Posting matched invoices back with the right cost codes, supplier accounts, and approval state is the bit that goes wrong with cheap tools.
How it works
What we actually build.
Read the invoice
A vision-and-language model extracts line items, totals, VAT, supplier, dates, and PO references — even from scans, even when the layout changes mid-year.
Match against POs and GRNs
Each line is matched to a purchase order line and a goods-received note. Quantities, prices, and units are checked. Tolerances are configurable per supplier or per category.
Resolve or escalate
Clean matches post straight through to your accounting system. Discrepancies get routed to the right person (buyer, ops, finance) with a clear summary of what doesn't match and a suggested action.
Learn from corrections
When a human overrides a decision, the system remembers — supplier-specific rules, recurring carriage charges, known short-delivery tolerances. The auto-match rate climbs over the first three months.
Proof
Real outcomes, not slideware.
AP team went from spending ~8 hours per week reconciling supplier invoices manually to ~20 minutes reviewing flagged exceptions. The clean 95% match through automatically.
"It used to be the worst job of the week. Now we just check what AI flagged."
Industry fit
Where this lands hardest.
Pricing
Fixed fee, phased delivery.
£3,200–£8,500 for build, ~£250–£500/month for hosting + tuning
From £3,200
Typical invoice matching build
- Workflow audit + spec phase
- Build, integrations, and tuning to your data
- Live deployment in your environment
- Monthly support and accuracy monitoring
Questions
Things people ask us about this.
01 Will it work with our weird suppliers?
Yes. The model handles arbitrary PDF layouts — including scans, emailed Excel files, and the occasional invoice that's clearly just a photo of a piece of paper. The first 2-3 suppliers are the slowest because we tune to your real edge cases; after that, adding new suppliers is automatic.
02 What accounting systems do you integrate with?
Sage 50, Sage 200, Xero, QuickBooks, NetSuite, and custom ERPs. If the system has an API, a CSV import, or even an email-in interface, we can post matched invoices back to it.
03 Where does our data go?
Invoices stay in your environment. We use enterprise-grade AI providers (typically Anthropic, OpenAI, or Google Cloud) with zero-retention API contracts. No invoice content is used to train external models. We're happy to sign DPAs.
04 How does it handle VAT and CIS?
VAT rates and codes are extracted per line and reconciled against your supplier records. CIS deductions on subcontractor invoices are recognised and routed differently. UK-specific tax handling is one of the reasons off-the-shelf US tools struggle for UK SMBs.
05 What if the AI gets it wrong?
It will, occasionally — that's why everything is auditable and reversible. Every match decision is logged with confidence scores and the source data. You can always see why a decision was made, and humans always have the final say on anything below the confidence threshold.
06 How long until we see ROI?
Typically 3-6 months on hours saved alone. Most clients see a bigger return on the soft side — fewer payment errors, no duplicate payments, supplier relationships improve when you stop short-paying by accident.
Related
Other AI patterns we deliver.
Let's see if we can help.
A 15-minute chat with Chris & Kay. No slides. No pitch deck. You tell us what's on your plate; we follow up by email with real thinking.