Finance & admin

Receipts to spreadsheet converter

Get receipt tables: merchant text, purchased items, quantity, price, tax, tip, total, payment row, and date when visible.

AI Deep Read · 1 credit per page · free account required
Free: 5 conversions a day · 5 MB each
Deleted after 24 h · never used for training

Before you start

What to expect

Files are retained only for the product retention window and deleted after 24 hours unless your account policy says otherwise.
Uploads are not used to train models; AI Deep Read reads the page only to produce your requested output.
AI Deep Read costs 1 credit per rendered page and still needs human review for financial records.
Receipt totals are especially error-prone on faded thermal paper; treat the spreadsheet as a review aid, not final bookkeeping evidence.

What the output contains

One spreadsheet row set per receipt photo or page, with visible line items and totals kept for review.
Recognizable dates and currency values typed when possible, including tax, tip, subtotal, and grand total rows.
Batch-friendly output that keeps source filename/page context so reimbursements can be traced back to the receipt image.
Ambiguous merchant names, loyalty text, coupons, and payment lines kept instead of silently discarded.

A real run

Expense-report receipt photos

Input: 28 phone photos: restaurants, rideshare, office supplies, and two faded thermal receipts; most were HEIC, three were JPG screenshots.
Output: One workbook with 28 source sections, 146 item rows, typed totals for 25 receipts, and three faded receipts flagged by obvious subtotal mismatches during review.

Known failure modes and how they're handled

Crumpled or faded thermal receipts: AI Deep Read reads what is visible, but low-contrast totals and damaged digits may be wrong. Keep the original image beside the spreadsheet during review.
Long receipts with coupons and loyalty blocks: The workflow preserves suspicious non-item rows so you can delete coupon chatter without losing a real charge.
Batch of many receipt photos: Each image is read independently; filenames and page order are used as trace columns so you can spot duplicate uploads.
Totals do not equal line items: No hidden reconciliation is applied. The output keeps line items and totals so you can compare and correct them manually.

Command line

Do it yourself

ocrmypdf

bash

ocrmypdf receipts.pdf receipts-ocr.pdf && pdftotext -layout receipts-ocr.pdf receipts.txt

Good OCR baseline for PDFs, but it does not structure receipt line items into accounting columns.

pandas concat

bash

python -c 'import pandas as pd, glob; pd.concat(pd.read_csv(f).assign(source=f) for f in glob.glob("receipts/*.csv")).to_excel("receipts.xlsx", index=False)'

Useful after you have per-receipt CSVs; it does not perform OCR by itself.

Questions about this workflow

Can one upload contain many receipt photos?

Batch upload is the intended workflow. Review source filenames in the output so duplicate or blurry photos can be removed.

Will it separate tax, tip, and total?

When those rows are visible, they are included and typed where recognizable. You still need to verify them against the receipt image.

Does this replace an expense-management app?

No. It creates reviewable spreadsheet data from readable receipts; approval workflows and card matching remain outside the converter.

What should I do with dark restaurant receipts?

Crop the receipt, increase brightness, and avoid shadows before upload. AI Deep Read cannot recover text that is not visible.

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