Why "PDF to CSV" is harder than it sounds
Most PDF-to-CSV tools just pull raw text and leave you to untangle it. That works for a clean digital table and falls apart on real business documents — invoices with headers and totals, receipts with odd layouts, or scanned pages where the "text" is actually an image. What you usually want isn't the words on the page, it's the fields: the invoice number, the line items, the amounts.
Papersnap converts a PDF into structured data first — it understands what kind of document it is and labels the fields — then exports clean CSV. Digital PDFs are read directly; scans and photos go through OCR. Either way you get columns that mean something, not a wall of text.
What you can convert to CSV
- •Invoices: invoice number, vendor, line items, tax, and total as tidy rows
- •Receipts: merchant, date, items, and total — ready for expense tracking
- •Statements: transactions and balances pulled into a spreadsheet-ready table
- •Reports & tables: tabular data extracted with its structure intact
Digital PDFs and scans both work
- •Born-digital PDFs: text is read directly for the fastest, most accurate result
- •Scanned PDFs & photos: OCR reads the image, so a scan converts just like a digital file
- •Labeled columns: you get named fields, not a raw text dump you have to clean up
- •JSON too: need it for an API instead of a spreadsheet? Export the same data as JSON