# Check whether scanned PDFs can be searched

Canonical page: https://agents.paretoid.com/workflows/check-whether-scanned-pdfs-can-be-searched/

Category: Operations & Reporting

Practice relevance: cross-practice. A general operational method. Review the stated tool and jurisdiction limits before use.

Jurisdiction/provider scope: 

Find image-only pages, broken OCR, and missed sample strings without overwriting originals.

Status: Proposed / not tested. The public source describes the problem. Documentation supports only the stated method components; no result from this recipe has been verified.

Verification: Source methods and reported problems have been reviewed. We have not run the adapted workflow. The sample below describes expected behavior on synthetic data, not a customer result.

## The problem

Find image-only pages, broken OCR, and missed sample strings without overwriting originals.

Why it matters: A PDF may appear searchable while its text layer omits words or misreads numbers. Testing known strings and inspecting suspect pages helps staff understand what search can miss without treating OCR as authoritative text.

## Sources and evidence

- pain: [Pain evidence: Large-document PDF search help](https://www.reddit.com/r/paralegal/comments/vmzbg0)
  Large-document PDF search help, 2022-06-28, older: a paralegal receiving extensive PDF discovery asks how to search it. Adobe Help, 2024-04-01, provides a specific failure: combining a transcript and scans makes OCR insert spaces between letters, defeating search. OCR questions, 2022-04-08, reports number-recognition errors and large-document crashes.

- pain: [Pain evidence: Adobe Help](https://www.reddit.com/r/paralegal/comments/1bt5rb2)
  Additional self-reported public account; no independent identity or outcome verification.

- pain: [Pain evidence: OCR questions](https://www.reddit.com/r/paralegal/comments/tyqqpv)
  Additional self-reported public account; no independent identity or outcome verification.

- method: [Method: Adobe: fix text recognition errors](https://helpx.adobe.com/acrobat/desktop/create-documents/scan-documents-to-pdfs/fix-scanned-text.html)
  Adobe: fix text recognition errors documents recognized-text review and suspect-word correction.

Source checked: October 15, 2026. Pain accounts are self-reported. Documentation supports components; this adapted recipe and prompt have not been tested.

## Suggested approach

Start when: A scan batch or combined reference PDF is received

1. inspect text-layer coverage and test known sample phrases/numbers

2. Keep source references and report unknowns instead of filling gaps.

3. The responsible reviewer checks the report before any separately approved action.

## What you need

- Existing Acrobat desktop with Scan & OCR access (use the firm’s approved licensed installation).

- Working copies of synthetic/public PDFs and a reviewer who can read the original images. Never overwrite evidentiary originals.

- Optional firm-approved Excel Copilot access for organizing the deidentified test log; native OCR/search tests work without AI.

- Use synthetic inputs first. Keep real data in firm-approved accounts and processing, with appropriate access, confidentiality and retention controls. Aliases alone do not anonymize records. Never paste credentials, API keys or unnecessary client details.

## How to use

Documentation-verified native OCR and manual QA route; no automatic whole-file AI certification

- The kit extraction.csv is a manually captured page/test log here, not a documented Acrobat one-click per-page CSV export.

- Acrobat AI answers are not proof that every page has a text layer or that OCR is accurate. Whole-file coverage requires checking every relevant page; sampling must be labeled sampling.

Access and setup:

- Acrobat edition/version and OCR tool access were not tested.

- No native per-page extraction CSV or automatic mixed-page completeness detector was verified.

### 1. Create the test baseline

Tool: Acrobat desktop and a text editor

Location: Open a separately named working copy; Select text tool

Before OCR, record file_id, source_version and displayed page_count. Visually read a distinctive phrase and, where available, an important number/date on each tested page; enter each as a separate known-strings.csv row. For each page, select and copy all available page text to a plain-text editor and store exactly ONE aggregate extraction.csv row for that file_id/page. Record complete_page_capture, partial_page_capture or unselectable/empty in extraction_status. If only part was copied, record that scope in extraction_status. All known strings for a page will be checked as substrings of that one captured text value.

Expected output: files.csv and known-strings.csv plus initial extraction.csv rows (file_id,page,extracted_text,extraction_status). All are manual QA logs.

Next step: Keep the original and baseline log unchanged; process only the working copy.

Check before continuing: Distinguish a PDF page index from printed/Bates page labels. Copy failure may reflect restrictions, not just image-only content; stop rather than bypass restrictions.

Execution status: Official documentation checked 2026-10-15; product account and workflow not personally tested

Step documentation: https://helpx.adobe.com/acrobat/using/reusing-pdf-content.html

### 2. Run OCR on the working copy

Tool: Acrobat desktop

Location: All tools > Scan & OCR > In this file

Choose the intended page range and document language, then Recognize Text. For a batch use In multiple files > Add files and select a separate output folder/filenames. Preserve existing digital-text pages rather than rewriting them indiscriminately.

Expected output: Searchable working PDF with an OCR text layer where processing succeeded.

Next step: Reopen the output and rerun the baseline copy/search tests.

Check before continuing: Record OCR errors, skipped pages and the chosen language/page range. A completed OCR job is not a passing QA result.

Execution status: Official documentation checked 2026-10-15; product account and workflow not personally tested

Step documentation: https://helpx.adobe.com/ca/acrobat/desktop/create-documents/scan-documents-to-pdfs/recognize-text.html

### 3. Review OCR suspects and test known strings

Tool: Acrobat desktop

Location: Scan & OCR > Correct recognized text > Review recognized text; Find/search in the PDF

Compare each flagged word to its image. Correct only the OCR working-copy text when unambiguous; use Accept to advance. Independently search each known phrase/number and copy the result into the test log, including spaced-out words or digit mismatches. Keep one aggregate post-OCR extraction row per file_id/page and compare each expected string against that row. Never silently pair several per-page extracts by order.

Expected output: Per-tested-page pass/fail/uncertain evidence and corrected working-copy text where justified.

Next step: Populate extraction.csv from the observed post-OCR text and statuses.

Check before continuing: Review even when no suspect is flagged. Test coverage must list pages checked and unchecked; a failed search does not prove absence of source content.

Execution status: Official documentation checked 2026-10-15; product account and workflow not personally tested

Step documentation: https://helpx.adobe.com/acrobat/desktop/create-documents/scan-documents-to-pdfs/fix-scanned-text.html https://helpx.adobe.com/acrobat/using/reusing-pdf-content.html

### 4. Summarize the actual test results

Tool: Excel Copilot, optional; or manual review

Location: Alias-only QA workbook > Copilot icon at lower right > Chat only

Place the deidentified known-string and one-row-per-page extraction logs in an Excel workbook. Open Copilot in Chat only and paste the prompt, or manually search each expected string within the corresponding extracted_text cell.

Prompt:

```text
Use only these manually observed PDF searchability logs. Join expected strings to exactly one aggregate extraction row using file_id and page; report duplicate extraction rows as an error. Check each expected phrase/number as a literal substring of that page’s extracted_text, not as equality with the whole text cell. Flag mismatches, spaced-out words, empty extraction and partial/untested page coverage. Quote the expected string and observed evidence. Return file_id,page,expected_string,observed_excerpt,issue,review_action and coverage count. Do not certify the whole PDF, infer untested content, interpret legal substance, edit the workbook or alter PDF files.
```

Expected output: Exception queue with file_id,page,known string,observed text,issue,review action; coverage summary.

Next step: Human reads each queued original image and verifies corrected working copy.

Check before continuing: Require literal examples and page references; do not let an assistant invent untested page coverage.

Execution status: Official documentation checked 2026-10-15; product account and workflow not personally tested

Step documentation: https://helpx.adobe.com/ca/acrobat/desktop/create-documents/scan-documents-to-pdfs/recognize-text.html https://support.microsoft.com/en-us/excel/copilot/get-started-with-copilot-in-excel

### 5. Release the searchable reference copy

Tool: Document reviewer

Location: Approved local working-copy folder and QA log

Save the searchable reference PDF under a distinct name with its test log. Resolve or clearly flag failed/uncertain pages; retain original scans unchanged.

Expected output: Searchable working copy with an honest page-coverage and exception record.

Next step: Staff use it for search while consulting original images for substantive accuracy.

Check before continuing: Numbers, names and dates require visual verification before reliance; no claim that OCR is an authoritative transcript.

Execution status: Official documentation checked 2026-10-15; product account and workflow not personally tested

Step documentation: https://helpx.adobe.com/ca/acrobat/desktop/create-documents/scan-documents-to-pdfs/recognize-text.html https://helpx.adobe.com/acrobat/desktop/create-documents/scan-documents-to-pdfs/fix-scanned-text.html

## What you will get

searchability-review.csv: file_id, source_version, page, test_string_id, finding, source_locator, visual_check_needed

## Human review and limits

Staff compare suspect text with rendered originals, especially dates/numbers. Test mixed digital/scanned pages, rotated scans and deliberately degraded text. Never overwrite evidence originals.

The assistant drafts or reports only. Check source records and review the output before a human performs any separately approved send or change. No automatic legal decision, money movement, account connection or publication is included.

What to measure: In a synthetic pilot, count correctly found exceptions, false alarms, and unresolved inputs. No time or cost saving is assumed.

## Original prepared-input schema

files.csv: file_id, source_version, page_count; known-strings.csv: file_id, page, expected_public_or_synthetic_string

extraction.csv: file_id, page, extracted_text, extraction_status; rendered synthetic/public PDFs for visual comparison

Synthetic example input:

```text
P1: image-only page with empty extraction
P2: known word extracted with spaces between letters
P3: expected number differs from OCR
```

Expected synthetic output:

```text
P1: no searchable text
P2: phrase-search failure
P3: number mismatch for visual review
```

Failure check: Staff compare suspect text with rendered originals, especially dates/numbers. Test mixed digital/scanned pages, rotated scans and deliberately degraded text. Never overwrite evidence originals.

## Starter files

Native blank scaffolds and original synthetic examples may use different schemas. Follow NATIVE-INPUT-MAPPING where supplied. These files do not connect accounts or install automation.

- [Download starter kit](https://agents.paretoid.com/assets/starter-kits/s03-starter-kit.zip) — All inputs, synthetic examples and review notes in one ZIP. No automation is installed.

- [Start here: get the sources and prepare the review](https://agents.paretoid.com/assets/starter-kits/s03/START-HERE.txt) — Documentation-checked acquisition, explicit manual mapping, exact prompts and human review limits

- [files.csv](https://agents.paretoid.com/assets/starter-kits/s03/files.csv) — Blank input template with exact recipe headers.

- [files.example.csv](https://agents.paretoid.com/assets/starter-kits/s03/files.example.csv) — Separate synthetic fixture input. Do not mix these rows into real exports.

- [known-strings.csv](https://agents.paretoid.com/assets/starter-kits/s03/known-strings.csv) — Blank input template with exact recipe headers.

- [known-strings.example.csv](https://agents.paretoid.com/assets/starter-kits/s03/known-strings.example.csv) — Separate synthetic fixture input. Do not mix these rows into real exports.

- [extraction.csv](https://agents.paretoid.com/assets/starter-kits/s03/extraction.csv) — Blank input template with exact recipe headers.

- [extraction.example.csv](https://agents.paretoid.com/assets/starter-kits/s03/extraction.example.csv) — Separate synthetic fixture input. Do not mix these rows into real exports.

- [Expected fixture findings](https://agents.paretoid.com/assets/starter-kits/s03/expected-fixture-result.txt) — Read-only expected output and failure conditions for the included synthetic input files.

- [Setup and review checklist](https://agents.paretoid.com/assets/starter-kits/s03/README.txt) — Recipe-specific prerequisites, file mapping, prompt, setup steps, checklist and limits.

## Optional original prepared-input prompt

Destination: Excel Copilot, optional; or manual review · prepared inputs

This original prompt uses its own prepared-input schema. Do not mix it with native-step tables without the supplied mapping.

```text
For these public or synthetic PDFs, prepare a searchability QA checklist. Identify image-only pages, empty text extraction, spaced-out words and mismatches against the supplied known strings. Cite page numbers. Preserve the original scans and existing digital text. Do not interpret documents, correct substantive wording or treat OCR as an authoritative transcription. Queue uncertain pages for visual review.

INPUTS
files.csv: file_id, source_version, page_count; known-strings.csv: file_id, page, expected_public_or_synthetic_string
extraction.csv: file_id, page, extracted_text, extraction_status; rendered synthetic/public PDFs for visual comparison

OUTPUT
searchability-review.csv: file_id, source_version, page, test_string_id, finding, source_locator, visual_check_needed

Use only these synthetic or firm-approved inputs and preserve source row/page IDs. Keep missing or conflicting evidence unresolved. Return a draft for the named reviewer. Do not send messages, connect accounts, change records or permissions, move money, or make legal decisions. Keep source files unchanged. List missing prerequisites before continuing.
```

Proposed / not tested · editorial prompt

Published by Law Firm Agents. Proposed adaptation; not tested. Not legal advice.
