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Initializing secure environment…
Extract tabular data from a PDF into an editable .xlsx with headers and data rows preserved. The table structure is detected from the text positions rather than guessed, each detected table is previewed so you can correct the column boundaries, and the result opens as a real spreadsheet with numbers as numbers rather than text. Nothing is uploaded, which is what makes this safe for bank statements and client reports. No account, no watermark, and it works offline.
To extract PDF tables to Excel free, add the file and each detected table is previewed with editable column boundaries. Approve and download a real .xlsx with numbers as numbers. 100% local, no upload, no watermark.
Extract, then check that the total row matches the statement's own total before you rely on it. A table extraction that is 98% right is dangerous precisely because it looks right. The total is the cheapest possible validation, and it catches a shifted column immediately.
The header occupies two or three rows and the detector treats them as data. Set the header row count explicitly in the preview, or delete the extra rows in the spreadsheet afterwards. Either way, check that the first data row is the first data row and not a continuation of the heading.
Because extraction reads characters and a scan has none. OCR produces a text layer, and the geometry that table detection relies on comes from the text positions. The chain is scan → OCR → extract, and skipping the middle step gives you an empty sheet rather than a wrong one.
Each detected table becomes its own sheet, so a document with a summary, a breakdown and an appendix produces three sheets. Rename them before you send it on — a sheet named page-4 is not something a colleague can work with, and renaming takes ten seconds.
From the geometry of the text: rows are found by their vertical alignment, columns by the horizontal positions of the words, and a grid is inferred where the alignment is consistent. It is a structural inference, not a tag the file contains, so the preview exists — check the column boundaries before trusting the result.
Because the source table has merged cells, a multi-line header, or a column of wrapped text. The preview lets you correct the boundaries by hand, and a corrected boundary is usually all that is needed. Header rows spanning several lines are the most common case.
Yes. Values that are recognisably numeric are written as numbers, dates as dates, and currency as a number with formatting. That is what makes the output summable rather than a sheet of text that looks like a spreadsheet.
OCR first. Extraction reads characters, not pixels, so a scan has nothing to extract until it has a text layer. OCR the document, then extract from the result — and check the recognition on a few rows, because a misread digit in an amount column is the failure that matters.
Good on a statement generated digitally, where the columns are consistently aligned. Less good on a statement that is a rendering of a web page, where column positions shift between pages. Preview each table and compare the totals against the statement — a total you can check is the cheapest validation there is.
Yes. Lines are not required — detection works from text alignment. A table with no lines and inconsistent spacing is the hardest case, which is why the boundaries are editable rather than fixed.
Yes. Each detected table becomes a sheet, named for its page, and you can exclude the ones you do not want. A document with a summary table and a detail table produces two sheets rather than one mangled one.
Yes. Free, no account, no watermark, and no upload. Financial statements and client data are extracted inside your browser, which is the only acceptable way to handle them.
More convert from pdf — all free, no upload.