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Invoice Number Extractor

Pull the invoice number out of a PDF, a scan or a pile of pasted invoices.

Drop invoice PDFs, scans or photos here — several at once

Quick Tool Overview

The Invoice Number Extractor pulls invoice numbers out of invoice PDFs, scans, photos and pasted text in bulk, showing the line and the label each value came from, and marking anything it inferred rather than read — all in your browser.

What it does
Extracts invoice numbers from invoices
You give it
PDFs, scans, photos or text
You get back
The invoice number and any candidates
Best for
Filing, matching and chasing
Invoice Tools Free, unlimited use No sign-up Runs in your browser

About the Invoice Number Extractor

The invoice number is what everything else is filed under: the payment reference, the credit note, the query, the audit trail. Getting it out of a hundred PDFs by hand is a morning of somebody’s life.

It reads the number the way a person does — from the label beside it. "Invoice No.", "Invoice #", "Rechnung Nr.", "Facture n" and a dozen other wordings are recognised, and where nothing is labelled the candidates are listed rather than guessed at silently.

Drop a PDF, a scan or a photo, or paste the text — several files at once if you have them. Every match is listed with the line it came from, so a value you did not expect can be traced back to the page in a second. Results copy as a list or download as CSV, one row per invoice, ready for a spreadsheet.

Scanned files are read with OCR in your browser and marked as guesses with a confidence figure. Nothing is uploaded: the PDF reader and the OCR engine run on your machine.

Key features of the Invoice Number Extractor

Reads the labels

The way a person does, in several languages.

Shows the evidence

The line every value came from.

Bulk

Many files at once, one row each.

Guesses marked

Inferred values are never presented as certain.

Private

OCR and parsing run on your machine.

How to use the Invoice Number Extractor

  1. 1

    Drop the invoices

    PDFs, scans or photos — or paste the text.

  2. 2

    Read the matches

    Each shows its value and the line it came from.

  3. 3

    Check the unlabelled ones

    Anything inferred rather than labelled is marked.

  4. 4

    Copy or download

    As a plain list or as CSV.

Frequently asked questions

Yes. Drop as many files as you like and each is read in turn, with one row per file in the results.

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