§ Demo · Finance · Narrated by Lyra

Invoice processing — end to end.

Multi-modal extraction on scanned invoices, three-way match against the PO and receipt, and approval routing — with a human-in-the-loop where confidence dips or a policy check flags something.

Invoice processing — end to end.

Narrated by Lyra · 3:12

The pattern shown here is the one we deliver most often in Finance departments with high invoice volumes and a stretched AP function. The walkthrough uses synthetic supplier data; the shape is real.

Note where the humans stay involved. Extraction confidence gates a review queue; policy exceptions gate an approval; approvals themselves are always human. The AI is doing the tedious triage — not the consequential decisions.

The pattern

What the walkthrough shows.

  1. Ingest and classify.

    OCR + layout detection over the invoice PDF, then structured extraction — supplier, PO number, line items, VAT, totals — with a calibrated confidence score per field.

  2. Three-way match.

    Reconcile the extracted record against the purchase order and the receipt of goods. Discrepancies routed for human review with the specific fields highlighted; clean matches pass through.

  3. Policy check.

    Approval band by amount, GL code sanity check, duplicate-invoice screen. A deterministic layer, not a model call — so it's testable, auditable, and easy to change when the policy does.

  4. Approval routing.

    Slack-native approval flow for the humans who need to say yes, cleanly attributed and audited. Nothing pays until the right person has clicked.

Order-of-magnitude impact

What clients typically see.

78%

Invoices auto-processed

~£32k

Typical annual saving

2.9mo

Typical payback period

Want this shape, for real, in your business?

A 30-minute discovery call. We'll say honestly whether the pattern fits.