How AFileFix's Invoice Scanner works

Upload up to 10 invoices or receipts at once — PDFs or photos. AI reads each document and extracts the structured data: vendor name, document number, dates, line items, totals, payment terms, and notes. Results render as per-document cards on the review screen, then export as a DOCX report or a CSV file.

The tool is calibrated for standard business documents. Vendor invoices, retail receipts, vendor statements — these extract cleanly. Handwritten amounts and unusual layouts degrade quality.

Processing takes 15-30 seconds for typical batches; larger batches of 10 documents can take longer. Documents are forwarded to Anthropic's Claude API for extraction and deleted from our server within minutes after processing. Anthropic retains API data for up to 30 days for safety review, then permanently deletes it; data is never used to train AI models.

What does the AI extract from each document?

For every invoice or receipt, the AI extracts:

• Vendor information — Vendor name, address if present, contact details
• Document identifiers — Document number, purchase order reference, invoice type
• Dates — Issue date, due date, service period if applicable
• Currency — Detected per document, no auto-conversion across the batch
• Line items — Description, quantity, unit price, line amount
• Totals — Subtotal, tax, discount, total
• Payment information — Payment terms (Net 30, Due on Receipt, etc.), payment method if specified
• Notes — Free-form notes, payment instructions, vendor messages

Per-document accuracy depends heavily on input quality — see “Photo vs PDF accuracy” below.

What flags does it raise?

The AI applies a few automatic checks across your batch and surfaces flags you should look at before exporting:

Overdue — Documents where today's date is past the due date. Useful when scanning a backlog of invoices for payment workflow.

Math errors — Cases where the line items don't sum to the printed total. The flag includes the currency delta so you can investigate. Common causes: discount lines not visible in extraction, manual adjustments by the vendor, tax calculation differences between line items and totals.

Duplicate document numbers — Two or more documents in your batch with the same invoice number. Useful for catching accidental scans of the same receipt twice.

Missing fields — Cases where the AI couldn't extract a field that's typically present. Note that optional fields (payment method, notes, PO reference) only show as missing when they appear to be standard for that document type but absent.

Photo vs PDF: what to expect on accuracy

Digital PDFs: Highest accuracy. Text is extracted directly from the document structure. Vendor names, amounts, dates, and line items come through cleanly.

Sharp camera photos of printed invoices: Usually fine. AI vision handles printed receipts well as long as the photo is sharp, well-lit, and the receipt is roughly flat. Skewed angles and shadows reduce accuracy.

Wrinkled, blurry, or low-light photos: Accuracy drops noticeably. Specific numbers and small text may be misread. Try retaking the photo before scanning.

Handwritten amounts: Unreliable. AI struggles with handwriting variations. For handwritten receipts (especially personal expense memos), expect to review and correct manually.

Tips for camera capture: flat surface, good lighting, fill the frame, hold steady. A bad photo of a clear invoice produces worse results than a clear photo of a complex invoice.

DOCX vs CSV export — which to pick?

Both export formats include the same extracted data, just structured differently:

DOCX report — One document per invoice, formatted for human review. Useful for: emailing results to a colleague, printing for filing, reviewing before manual data entry. Each invoice gets its own section with the structured fields rendered as readable text.

CSV file — One row per line item (not per invoice), structured for spreadsheet or accounting software import. Columns: vendor, doc number, date, due date, currency, line description, qty, unit price, amount, total, payment terms, status flags. Useful for: bulk import into accounting software, sorting and filtering in Excel or Google Sheets, building reports across batches.

If you're doing payment workflow or accounting reconciliation, use CSV. If you're reviewing or sharing results, use DOCX.

What types of documents work best?

Best results:

• Standard B2B invoices (vendor invoices, professional services invoices)
• Retail receipts from major chains (printed cleanly, consistent format)
• Vendor statements with itemized line items
• Subscription billing receipts

Modest results:

• Handwritten receipts (amounts may be misread)
• Photos at unusual angles or low resolution
• Highly stylized receipts with unusual layouts
• Multi-page invoices (line items aggregated; pages combined into one document record)

Not supported well:

• Receipts in non-English languages (extraction works but field labels may be misclassified)
• Tickets and entry stubs (not the same data structure as invoices/receipts)
• Cryptocurrency transaction receipts (formats vary too widely)

Frequently asked questions

For AI-processing details and Anthropic's API retention terms, see our Privacy page.