OCR resource center

Extract document data with AI OCR on Windows

Read the page. Check the details. Illustrative example.

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

Recover text, tables, and key-value pairs from image-only PDF files using AI

Extract scanned PDF text, fields, and tables with AI OCR in Dynamite Docs. Compare uncertain values with the source before exporting reviewed data.

Extract invoice totals, taxes, and line items using AI OCR

Extract invoice totals, taxes, and line items with AI OCR in Dynamite Docs. Review supplier fields and table rows beside the source before export.

Read merchant data, transaction dates, and totals from scanned receipts with AI

Read receipt scans and photos with AI OCR in Dynamite Docs. Check merchant names, dates, tax, tips, and faded totals against the source before export.

Extract statement transactions using AI for reconciliation review

Extract bank statement transactions with AI OCR in Dynamite Docs. Review dates, debits, credits, and balances before preparing reconciliation rows.

Extract structured rows from photos, screenshots, and raw image files using AI

Extract structured fields and tables from images with AI in Dynamite Docs. Review document photos, screenshots, and scans beside the source before export.

Extract data from low-resolution and skewed scans with AI

Extract fields and tables from low-resolution or skewed scans with AI in Dynamite Docs. Check uncertain values and page order before exporting.

Extract borderless and multi-page tables using AI OCR

Extract borderless and multi-page tables with AI OCR in Dynamite Docs. Review columns, wrapped text, and continued rows before spreadsheet export.

Extract handwritten annotations, totals, and form fields into clean tables using AI

Extract handwritten form fields, notes, and totals with AI OCR in Dynamite Docs. Review unclear characters beside the source before exporting values.

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.

Extract invoice fields and line items with AI for accountants: Extract invoice data from a PDF, scan, or photo, then check every field beside the original.
Convert PDFs to Excel using AI for accounting teams: Turn a native or scanned PDF into Excel rows without cleaning up a broken copy-paste.
Extract multi-page PDF tables using AI: Extract tables from a PDF without rebuilding every row by hand.
Convert bank statements to Excel with AI for bookkeepers: Convert bank statements into Excel-ready rows, then check them beside the source.
Extract receipt data using AI for small businesses: 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.