Recover text, tables, and key-value pairs from image-only PDF files
Run OCR on scanned PDFs, recover text, fields and tables, then review the result before exporting to Excel, CSV or JSON.
OCR resource center
Turn scans, photos, and messy PDFs into structured spreadsheet rows
Recover the fields and rows trapped in scans or images, then check the result before it reaches a spreadsheet or API.
Traditional OCR turns pixels into characters. That is enough when you need searchable text. OCR data extraction has a harder job: it must keep a supplier name attached to its label, place an amount in the right column and carry a table row across the page without inventing a new record.
Dynamite Docs combines document OCR with structure and review. Use the guides below to choose the right path for scanned PDFs, invoices, receipts, bank statements, photos, tables and handwriting, then test the result on your own files.
OCR is one stage, not the finished dataset
Text OCR
Produces a text layer or reading-order transcript. It works for search and copying, but it may flatten tables or separate labels from their values.
Document OCR
Uses page position and layout to keep headings, key-value pairs, paragraphs and page regions connected.
OCR data extraction
Returns named fields, rows and typed values for Excel, JSON, an accounting system or an API.
OCR guides by source and layout
Read invoice totals, tax breakdowns, and line items with vision OCR
Extract supplier details, invoice numbers, tax, totals and line items with AI invoice OCR. Review the result before Excel, JSON or API export.
Read merchant data, transaction dates, and totals from scanned receipts
Extract merchant, date, tax, tip, total and item rows from receipt scans or photos. Review faded digits before exporting expense data.
Turn statement scans into clean transaction tables ready for reconciliation
Extract dates, descriptions, debits, credits and balances from bank statement PDFs or scans, then reconcile the rows before export.
Extract structured rows from photos, screenshots, and raw image files
Extract text, fields and tables from document photos, screenshots and scanned images, then review the structured data before export.
Extract verified data records from low-resolution and skewed paper scans
Convert scanned documents into searchable text, named fields and tables while preserving page order, layout and source evidence for review.
Reconstruct borderless, dense, and multi-page tables into structured rows
Extract rows and columns from scanned tables, screenshots, borderless layouts and multi-page PDFs into Excel, CSV or JSON.
Extract handwritten annotations, totals, and form fields into clean tables
Extract clear handwriting from forms, notes, receipts and scans while keeping confidence and source context for field-level review.
A practical OCR workflow
- Inspect the source: Check whether the file already contains reliable text. Digital PDFs may be parsed directly. Scans and photos need visual recognition.
- Read text and layout: Character recognition reads the page. The document model groups that text into fields, paragraphs, tables and repeating rows.
- Apply a useful schema: A useful schema keeps dates, amounts, identifiers and line items separate instead of returning one long text block.
- Review uncertain values: Compare uncertain text, totals, row boundaries and ambiguous characters with the source before export or automation.
Free OCR tools
Test one supported document and review the extraction before creating an account.
- Free AI tool to extract invoice data and line items into spreadsheets: Extract invoice data from a PDF, scan, or photo, then check every field beside the original.
- Free tool to turn PDF documents and scans into Excel spreadsheets: Turn a native or scanned PDF into Excel rows without cleaning up a broken copy-paste.
- Free tool to extract multi-page tables from PDFs without lost rows: Extract tables from a PDF without rebuilding every row by hand.
- Free converter for bank statements into clean Excel transactions: Convert bank statements to Excel without uploading. Processed in browser RAM.
- Free scanner to extract merchant names, dates, and receipt totals: Pull the merchant, tax, tip and line items from a receipt photo.
OCR software questions
What is the difference between OCR and AI OCR?
OCR recognizes characters in an image. AI OCR also uses layout and document context, which lets it return named fields and tables instead of only a transcript.
Can OCR extract data from scanned PDFs?
Yes. Each scanned page is treated as an image. Results depend on resolution, rotation, compression, contrast, handwriting, and whether important text is hidden by stamps or folds.
What should an OCR API return?
That depends on the job. Search needs text and page coordinates. Automation usually needs named fields, typed values, repeating rows, page references, confidence, and a way to inspect the source.
Is OCR output accurate enough to automate without review?
Some clean, repeated layouts can reach straight-through processing after testing. Financial totals, account numbers, handwriting, and unfamiliar layouts should start with human review and explicit validation rules.