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Solution: Receipt capture and matching

Receipts pile up and expense reports are always late

Staff photograph a receipt in seconds. AI reads the merchant, date, amount and tax, matches the card transaction, suggests the category and project, and sends it for approval.

Sounds familiar?

Signs this is costing you time

Expenses are small individually and painful collectively. Staff lose paper receipts, submit expense reports weeks late, and type details into spreadsheets. Finance chases missing receipts at month end, matches card statements line by line and fixes wrong categories.

For businesses where staff work on client projects or in the field, it matters even more, because costs must be assigned to the right job to bill clients and understand margins.

Capturing receipts at the moment of purchase, with AI doing the reading and matching, removes most of that work and most of the chasing.

  • Paper receipts are lost or handed in weeks later.

  • Expense reports are typed into spreadsheets by hand.

  • Card statements are matched to receipts line by line at month end.

  • Categories and project codes are often wrong or missing.

  • Month-end close waits for expenses to be sorted.

Before and after

How it works today, and how it works after

Before

How it works today

  1. Staff keep receipts in wallets and vehicles.

  2. Expense reports are filled in at the end of the month.

  3. Finance matches card lines to receipts by hand.

  4. Missing receipts are chased by email.

  5. Costs are assigned to projects late or not at all.

After

How it works after

  1. Staff photograph receipts in an app right after purchase.

  2. AI reads merchant, date, amount, currency and tax.

  3. The receipt is matched to the card transaction automatically.

  4. Category and project are suggested from history and the calendar.

  5. Managers approve in one tap, and entries flow into accounting.

What we build

What we build

Capture app

A simple mobile or web app, or an email address to forward receipts to.

AI reading

A vision model extracts the details into structured fields, including from crumpled or foreign receipts.

Card matching

Transactions from card feeds or bank exports matched to receipts by date, amount and merchant.

Coding suggestions

Category, cost center and project suggested from past choices and policies.

Approvals

Policy checks and one-tap manager approval, with exceptions flagged.

Accounting sync

Approved expenses posted to Xero, QuickBooks or your ERP.

In practice

What it looks like in practice

An illustrative walk-through, not a client story.

An engineering consultancy has twenty staff who travel to client sites. Every month, finance spent two days matching card statements to receipts and coding costs to client projects, and chased several people for missing receipts.

Now staff take a photo of each receipt in a small app. AI reads it, matches the card transaction and suggests the project from the staff member's calendar that day. The engineer confirms with one tap. Managers approve weekly. At month end, finance sees a short list of unmatched transactions instead of a pile of paper, and client project costs are up to date for billing.

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.

Cross-platform apps

One codebase for iOS and Android with React Native or Flutter, so both apps ship together.

Computer vision

Software that reads photos and scans: damage checks, stock counts, document capture and quality control.

Industries where it fits best

Honest limits

Limits and human checks

AI reads most receipts accurately, but faded thermal paper, handwriting and unusual layouts cause errors. Every extraction shows the original image beside the data, low-confidence fields are highlighted, and approvers see both before approving.

Expense policies and tax rules vary by country and company. We encode your policy as clear rules, such as limits per category, and flag exceptions rather than rejecting them automatically. Tax treatment should be confirmed by your accountant.

Receipts can contain personal information, such as names on hotel bills. We store images securely with access limited to staff who need them, and follow your retention rules for financial records.

Keep exploring

FAQ

Questions about receipt capture and matching

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