Plan OCR review for a long scanned PDF

The browser processor handles the first 25 PDF pages per request. For a longer scan, sample every layout and quality change, split the file into traceable batches, retain original page identifiers, and merge output only after weak or rotated pages have been corrected.

Drop a representative PDF batch

Start with pages that cover every layout and scan-quality change

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Recognition settings

Choose the primary language in your document.

Private by design. Files are processed in temporary storage and removed when processing finishes. Avoid sensitive uploads when online processing is not appropriate.

A controlled review queue for long scanned documents

Test and process long scanned documents in controlled page batches while preserving page boundaries and a review queue.

Practical useLong scans that can be divided into reviewed batches of up to 25 pages.
Batch riskOne global setting may fail on inserts, rotated pages, tables, or changing scan quality.
Capability boundaryCurrent limit: up to 25 PDF pages per request, with explicit page labels in the text output.
OCR.now social preview for Long PDF OCR with a source-specific recognition workflow

The live processor accepts the first 25 pages per request. This route explains how to sample difficult pages and divide longer documents without suggesting that a browser request is an unattended batch system.

The live request limit is 25 pages. The value of this route is a safe batching and review method, not a false promise of unattended long-document processing.

Design the review sample with Sample-Based OCR Quality Assurance for Large Collections before dividing the file. Use Multi-Column OCR and Reading Order Review to keep difficult layouts in sequence when batches are reunited. For a single scanned file or a different output, compare PDF to Text and OCR Document Compare.

Sample, divide, recognize, and merge by page identity

Sample front matter, dense text, tables, inserts, and damaged pages.

Process no more than 25 pages in one browser request.

Retain page identifiers and merge only after weak pages are corrected.

Long-document batching scenario

For a 140-page archive scan, sample front matter, ordinary text, foldouts, tables, and the weakest paper. Divide the document at stable boundaries, then maintain a queue of pages needing rotation, recapture, or manual review. Merge corrected text by original page ID, not by processing order.

Find pages that need a different treatment

Review pointLikely failureValidation action
SamplingOnly easy opening pages are testedInclude tables, inserts, damage, rotation, and small print
Batch identityOutput loses its original page referenceName batches and retain explicit page labels
Setting driftOne configuration fails on later sectionsStart a new batch when layout or scan quality changes

When browser OCR is not an appropriate batch system

Use a managed batch OCR system when unattended processing, retries, audit logs, and very large collections are required. Extract native text instead when the PDF already contains a reliable searchable layer.