You need the numbers from a PDF invoice, bank statement or report in a spreadsheet. You select the table, copy it, paste — and get a single column of values with the structure gone.
That is not a bug in Excel. A PDF table has no rows and columns; it is text placed at coordinates, with lines drawn around it to look like a grid. Every method of getting it into a spreadsheet is a way of guessing the structure back.
For a simple, well-ruled table, paste into a spreadsheet and use Text to Columns with the delimiter set to space or tab. It is free, instant and works more often than people expect.
It fails predictably: cells containing spaces get split, cells spanning two lines break apart, and merged headers land in the wrong place. When you see that, move on rather than fixing hundreds of cells by hand.
Messy layouts — multi-line cells, tables continuing across pages, values in columns without ruling lines — need something that judges where the table begins and ends. That is what the AI extraction in Abzar's PDF to Excel does: the page content goes to a model, which returns rows and columns as a spreadsheet.
The trade-off is explicit. It runs in the cloud rather than in your browser and costs credits, because there is a real per-task cost behind it. For a sensitive document, weigh that before uploading.
A scanned statement is a picture. Run text recognition first to turn the page into text, then structure the text. Accuracy compounds: an OCR error in a number becomes a wrong number in your spreadsheet, so check figures against the source rather than assuming.
Whatever method you used, spend two minutes on these checks — they catch almost every serious extraction error: