Extract table data from images into Excel.
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Three workflows a generic PDF converter does not cover.
Extract table data from images into Excel.
Turn statement transactions into structured Excel data.
Pull structured fields out of a PDF.
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Extraction, checking and question-answering for when converting a file is not enough.
A scanned document contains no text. It contains a picture of text, which is why you cannot select a word in it and why copying a table out of one gives you nothing. Everything downstream depends on first turning those pixels back into characters. That recovery is imperfect in a specific way worth understanding: OCR does not fail loudly. It does not leave a gap where it was unsure — it produces its best guess, and a wrong guess looks exactly like a right one. An 8 read as a 3 arrives as a perfectly ordinary 3. This is why the useful skill is not finding a better converter. It is knowing which results to check, and giving the scan the best chance before it is read at all.
Skew, almost always. Columns are found from vertical bands of whitespace, and on a tilted scan those bands slant and stop separating the columns. Straighten and try again.
Up to legibility, yes; past it, no. Once the characters are clearly formed, more pixels add file size rather than accuracy. Sharpness matters far more than raw resolution.
Handwritten figures are the least reliable case by a wide margin, and a handwritten table should be checked in full rather than spot-checked. Printed text is what this is good at.
Same process. A PDF with no text layer is a picture in a wrapper, so it is read the same way. Running OCR over the PDF first also makes it searchable, which is useful on its own.
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