Table OCR that understands rows and columns
Standard OCR turns an image into text — accurate, but flat. It doesn’t know that “Item” and “$1,020” belong in the same row. Table OCR does, which is the difference between a wall of text you’d still have to structure yourself and a spreadsheet you can use immediately.
Last updated: September 2026
5 of 5 extractions left this month on the free plan
You can also paste with Ctrl / Cmd + V · JPG, PNG, WEBP up to 10 MB · PDF (Premium) · Select several at once (Premium)
How it works
- 1
Upload the image or PDF
A screenshot, photo, scan, or PDF page with a visible table.
- 2
The AI locates rows, columns, and headers
Not just characters — the grid structure itself, even when the table has no visible border lines.
- 3
Review and export
Every cell lands in its correct row and column, editable before you download .xlsx or .csv.
Plain OCR vs. table OCR
Both read the text. Only one reconstructs the grid it belongs to.
| Plain OCR | ShotToSheet | |
|---|---|---|
| Output format | A flat block of text, line by line | Structured rows and columns |
| Keeps a value in its correct column | No — you re-align it by hand | Yes, automatically |
| Ready to sort, filter, or sum | No — needs restructuring first | Yes, right after export |
| Handles tables with no visible border lines | Reads the text, loses the layout | Detects the grid from spacing and alignment |
How it detects structure
Most tables aren’t drawn with a full grid of visible lines — they rely on whitespace and alignment for a person to read them as columns. The model locates that structure the way a person does: by position on the page, consistent column starts, and header rows that read differently from the data below them — then maps every value to a specific row and column instead of just transcribing text top to bottom.
Frequently asked
OCR (optical character recognition) that additionally detects a table’s row and column structure, so extracted text lands in the correct cell instead of coming back as one undifferentiated block.
Those tools return text and, at best, rough bounding boxes — reconstructing rows and columns from that output is still manual work. This does that reconstruction step for you and hands back an editable table directly.
Yes — most real-world tables (spreadsheet screenshots, printed price lists) rely on spacing rather than drawn borders, and that’s the common case this is built for.
It attempts them, but they’re the hardest case for any table OCR approach — review those specific cells closely before exporting.
If you’d rather run this yourself in code, img2table is an open-source Python option — see the comparison for what each approach actually requires.
Related
AI Table Extractor
What separates a good AI table extractor from a gimmick.
img2table Alternative
The no-code version of this same comparison, for developers.
Extract Table from Image
The general-purpose converter this page is built on.
Image to Excel
For any image source or format.
vs. Excel’s picture import
The same comparison against Excel’s built-in feature.
Pricing
Free tier, plus Pro and Premium for higher monthly limits.