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Solution: Invoice processing

Supplier invoices are still entered by hand

Invoices arrive by email, AI reads them in any layout, rules check them against orders and contracts, and approved invoices flow into your accounting software. People handle the exceptions.

Sounds familiar?

Signs this is costing you time

Accounts payable teams in many businesses still work the same way: download the invoice from an email, read it, type the supplier, date, amounts and lines into accounting, check it against the purchase order, chase approval and file the PDF. With dozens or hundreds of invoices a month, it becomes a large part of someone's job.

Manual entry also causes the problems finance teams hate most: duplicate payments, wrong amounts, missed early-payment discounts and late fees.

AI can now read invoices reliably in any layout. Combined with matching rules and a review step, it turns invoice processing into a quick check of exceptions.

  • Invoices are typed into accounting line by line.

  • Duplicate invoices are paid, or invoices are missed entirely.

  • Invoices arrive in several inboxes and formats.

  • Approvals are slow, and late fees or lost discounts follow.

  • Month-end close waits for invoices to be entered.

Before and after

How it works today, and how it works after

Before

How it works today

  1. Invoices arrive by email, post and supplier portals.

  2. Someone types each one into accounting.

  3. Matching to purchase orders is done by hand.

  4. Approval is chased by email.

  5. PDFs are filed in a folder, hard to find later.

After

How it works after

  1. Invoices are collected from a dedicated inbox and portals automatically.

  2. AI extracts supplier, dates, totals, tax and line items.

  3. Rules match invoices to orders and flag differences.

  4. Clean invoices go to approval and then into accounting.

  5. Every invoice is stored with its data, searchable later.

What we build

What we build

Invoice intake

A dedicated email address and portal downloads collect every invoice.

AI extraction

A multimodal model reads the invoice and returns structured fields, with OCR for scans.

Matching and checks

Supplier lookup, duplicate detection, tax checks and purchase order matching.

Approval workflow

Invoices routed to the right approver by supplier, amount or cost center.

Accounting integration

Approved invoices posted to Xero, QuickBooks or your ERP through their APIs.

Exception review

A screen showing the invoice beside the extracted data for quick correction.

In practice

What it looks like in practice

An illustrative walk-through, not a client story.

A construction company receives around three hundred supplier invoices a month for materials, equipment hire and subcontractors. Two people in the office spent most of their week entering and matching them.

Now invoices go to one inbox. AI reads each one, and rules match it to the purchase order and delivery. Most match cleanly and go to the project manager for a one-click approval, then into accounting. The rest, such as a price that differs from the order or an unfamiliar supplier, appear in a review queue with the difference highlighted. The office team now spends its time on supplier queries and cash planning, and month-end close no longer waits for data entry.

Models and tools

AI models and MCP servers that usually fit

We choose models by task, data sensitivity and cost, and test them on your real examples before we commit. These are common starting points, not a fixed recipe.

How we build it

The services behind this solution

Most solutions combine two or three of our services. These are the ones this one usually needs.

Document automation

Read invoices, forms, contracts and IDs, pull out the right fields and route them for review.

API integration

Make two systems share data reliably, with retries, logging and alerts when something goes wrong.

Billing and payments

Checkout, invoices, subscriptions, refunds and the accounting exports your finance team needs.

Industries where it fits best

Honest limits

Limits and human checks

Extraction accuracy depends on invoice quality. Clean, typed PDFs extract very reliably; blurry photos, handwriting and unusual layouts less so. We never post uncertain data automatically. Confidence thresholds and validation rules send anything doubtful to review.

Payment decisions stay with people. The system prepares and checks; approvers decide. We also design against fraud risks such as changed bank details on an invoice, which always trigger a manual check. Invoices contain financial and sometimes personal data, so processing happens with providers and regions that match your policies.

Keep exploring

FAQ

Questions about invoice processing

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