Choose Draft for a PDF that is already mostly searchable; choose High for a scan or image-only document. In PDF4me’s REST API, the two values select different processing paths, not points on a universal OCR accuracy scale. Draft is a light pass documented at one API call per file. High performs full recognition page by page and is documented at two API calls per page.
For files that mix born-digital pages with scans, pair either quality mode with ocrWhenNeeded set to the string "true". That lets the service skip pages that already contain searchable text. The setting is separate from qualityType, so selecting Draft or High alone does not describe how mixed pages will be handled.
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Quick answer: which PDF4me OCR mode should you select?
| PDF condition | qualityType |
ocrWhenNeeded |
Documented API usage |
|---|---|---|---|
| Mostly born-digital, with a usable text layer | Draft |
"true" when you want searchable pages skipped |
One API call per file |
| Scanned or image-only pages | High |
"true" is still useful when some pages already contain text |
Two API calls per page |
| Mixed PDF containing both text and scans | Choose the mode that matches the pages requiring recognition | "true" to avoid reprocessing searchable pages |
Depends on how many pages require OCR |
PDF4me requires the REST request field qualityType, and the documented choices are exactly Draft and High. Capitalization matters. The published call counts are usage figures, not accuracy scores: no percentage improvement, benchmark corpus, or character-error measurement is established for High versus Draft.
What the quality parameter actually controls
The word “quality” can suggest a slider from poor to excellent. That is not how this API is documented. qualityType tells PDF4me which OCR path to use for the input file.
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Draft is a light pass for normal PDFs
Draft is intended for a normal PDF that mostly has selectable text already. The service describes it as a light pass and publishes an allowance of one API call per file. It is therefore the practical first choice when the PDF’s text layer is intact and you are adding or repairing searchability rather than rebuilding every page from pixels.
A text layer can exist even when a page looks like a scan. Before choosing Draft, test the actual file: try selecting a sentence, copying it into a plain-text editor, and searching for a word that is visibly present. If copied text is empty, nonsensical, or missing on many pages, treat those pages as image-based instead of assuming that a visual PDF is searchable.
High performs full per-page recognition
High is built for scanned documents and image-based PDFs where every page needs recognition. PDF4me documents two API calls per page for this mode. That figure describes processing consumption, not a guaranteed accuracy level. High can be the appropriate path for a clean, high-resolution scan, but the result still depends on image quality, typography, page layout, language, and the source file.
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Why the two modes are not an accuracy ranking
The available PDF4me wording does not provide a measured character-accuracy benchmark comparing Draft and High. There is no supported percentage that tells you how many more characters High will recognize correctly. The meaningful distinction is whether the service should make a light pass over a mostly text-based file or perform recognition on each page’s image content.
“Draft costs 1 API call per file and suits normal PDFs. High costs 2 API calls per page and is built for scanned documents where every page needs recognition.”
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ocrWhenNeeded is a separate decision
ocrWhenNeeded controls whether PDF4me can leave an already-searchable page alone. In the REST examples, its value is a string: "true" or "false".
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Use "true" for mixed files when preserving good existing text matters and unnecessary processing would add cost or latency. Setting it to "false" is an explicit instruction to run OCR throughout the file; it is not a way to make Draft become High.
A single quality label does not automatically explain every mixed-page outcome. The skip control determines whether searchable pages are eligible to bypass OCR, while Draft or High determines the OCR path for pages that are processed.
Choose by document type, not by the label alone
Mostly born-digital PDF
- Open the file in a PDF viewer and select text from several pages, including tables and headings.
- Search for words that are visibly present and paste selected text into a plain-text editor to check whether characters survive correctly.
- Set
qualityTypetoDraft. - Set
ocrWhenNeededto"true"if pages with a valid text layer should be skipped.
This path aligns with PDF4me’s documented one-call-per-file usage for Draft. If the file contains a few pages that are actually images, the skip setting gives the service permission to avoid reprocessing pages that are already searchable.
Scanned or image-only PDF
- Check whether selecting text returns nothing or whether every page is effectively a picture.
- Set
qualityTypetoHigh. - Budget around the published two API calls per page. This is a planning figure from PDF4me, not a promise about completion time or recognition accuracy.
- Use
ocrWhenNeededset to"true"if the file also includes some pages with a reliable text layer.
High is the documented full per-page path for this input. If the scan is skewed, blurred, heavily compressed, or handwritten, changing the quality value cannot repair missing image information; improve the source scan or prepare for manual correction.
Mixed PDF
Mixed files are common in contracts, multipage submissions, and reports assembled from several sources. A text-based cover page may be followed by scanned exhibits. Set ocrWhenNeeded to "true" so searchable pages can be skipped, then select Draft or High according to the recognition path you need for the pages that are not searchable.
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Do not infer an exact call total without knowing how many pages the service decides require OCR. The published figures establish one call per file for Draft and two calls per page for High; they do not publish a universal mixed-document formula.
Build a correctly typed REST request
Many integration failures come from sending the right words with the wrong JSON types. PDF4me’s REST samples use strings for ocrWhenNeeded and outputFormat, but JSON booleans for isAsync and mergeAllSheets.
| Field | Type shown in REST samples | What to check |
|---|---|---|
qualityType |
String | Use exactly Draft or High. |
ocrWhenNeeded |
String | Send quoted "true" or "false", not a JSON boolean, when following the REST shape. |
outputFormat |
String | Send the format as a quoted value accepted by the endpoint. |
isAsync |
JSON boolean | Use true or false without quotation marks. |
mergeAllSheets |
JSON boolean | Use true or false without quotation marks where this option applies. |
Example payload shape
The following illustrates the types and the two quality choices. Replace the double-curly variables with values required by your implementation; they are shown inside code so the JSON shape remains unambiguous.
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{
"qualityType": "Draft",
"ocrWhenNeeded": "true",
"outputFormat": "{{OUTPUT_FORMAT_STRING}}",
"isAsync": false,
"mergeAllSheets": false,
"docContent": "{{BASE64_PDF}}"
}For a scanned file, change only the quality decision to "High" unless your workflow requires different skip, language, or output settings:
{
"qualityType": "High",
"ocrWhenNeeded": "true",
"outputFormat": "{{OUTPUT_FORMAT_STRING}}",
"isAsync": false,
"mergeAllSheets": false,
"docContent": "{{BASE64_PDF}}"
}Use the exact property names and required fields for the endpoint version you are calling. The important interoperability rule is not to “normalize” quoted values into booleans or vice versa.
When to use asynchronous processing
For large files or workloads that should not hold an HTTP connection open, use the endpoint’s asynchronous behavior. PDF4me documents a 202 response for an asynchronous job and a Location header containing the URL to poll.
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- Submit the request with asynchronous processing enabled according to the endpoint’s documented option.
- When the response is
202 Accepted, read and store theLocationURL. - Poll that URL using the method and interval required by the API documentation.
- When the job is complete, parse the returned JSON and retrieve the output content.
Do not treat the 202 body as the finished PDF. It represents an accepted job; the polling URL is the next operation.
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The endpoint returns JSON containing the PDF as Base64 data rather than raw PDF bytes. Read the docContent field from the completed response, Base64-decode it, and write the resulting bytes as a PDF file. If your application saves the JSON text itself with a .pdf extension, the file will not open because it has not been decoded.
- Parse the HTTP response as JSON.
- Read the response’s
docContentvalue. - Decode the Base64 string using your language’s standard Base64 decoder.
- Write the decoded byte array to a binary file.
- Open the file and verify that text selection and search work before distributing it.
Set the source language when detection is wrong
Automatic language detection can produce garbled recognition. PDF4me advises supplying the source language when detection gets it wrong. In its REST examples, a full language name such as English is used.
Do not copy a language value from one integration into another without checking that surface’s schema. PDF4me’s cross-platform comparison shows examples in several forms: a full name such as English, a two-letter code such as en, or a three-letter code such as eng. The accepted representation can vary by connector. Send the format documented for the specific REST, Power Automate, n8n, Zapier, or Make interface you are using.
Language selection cannot compensate for a poor scan. If letters are missing because of blur, low contrast, or compression artifacts, correct the input image where possible and then rerun OCR.
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Terminology changes across PDF4me integrations
PDF4me’s authored comparison maps the labels this way:
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| Integration surface | Quality labels reported |
|---|---|
| REST | Draft and High |
| Power Automate | Draft and High |
| n8n | Draft and High in the setting description |
| Zapier | Standard and Expert |
| Make | Standard and Expert |
If a connector says Standard or Expert, do not send those words to a REST endpoint that requires Draft or High. Map the concept using that connector’s own documentation and field names.
The unexplained “Archival” value in n8n
The n8n response schema is reported to list Archival, while the setting description specifies only Draft and High. That mismatch does not establish a third selectable quality tier. Treat Archival as an unresolved schema discrepancy rather than a value to set in production.
Troubleshoot the failures that matter most
The API rejects qualityType
- Check spelling and capitalization: the documented values are
DraftandHigh. - Confirm that the request is going to the REST surface whose schema you are following; another connector may expose different labels.
- Ensure the field is present rather than relying on an undocumented default.
The request fails type validation
- Send
ocrWhenNeededas the quoted string"true"or"false"when using the REST shape. - Send
isAsyncandmergeAllSheetsas JSON booleans, not quoted text. - Send
outputFormatas a string accepted by the endpoint.
Searchable pages are processed again
Inspect ocrWhenNeeded. A value of "false" explicitly forces OCR on every page. Change it to "true" when the workflow should skip pages that already have searchable text.
The output looks like JSON instead of a PDF
Remember that the service returns Base64 inside JSON. Extract and decode docContent; do not save the response body directly as a PDF.
The job never returns a finished file
If the initial response is 202, follow the Location polling URL. A 202 response means the job was accepted asynchronously, not that the output is ready in that response.
Words are recognized as the wrong characters
- Supply the source language in the format required by the integration.
- Compare results from a representative page rather than judging the entire file from a title page.
- Check scan resolution, skew, contrast, and compression before changing quality modes.
Plan usage without confusing it with price or accuracy
PDF4me publishes Draft at one API call per file and High at two API calls per page. These figures help estimate service consumption, but they are not a retail price, a time guarantee, or an OCR accuracy measurement. Your account’s billing terms, quotas, and any connector-specific accounting are separate questions.
For a 20-page scan processed with High, the documented planning figure is two calls per page, or 40 calls for that file. That arithmetic is a usage estimate based on the vendor’s published rule; it does not claim that every connector exposes or bills the calls identically. For a mostly searchable file using Draft, the published figure is one call for the file rather than one call for each page.
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On mixed documents, ocrWhenNeeded: "true" can reduce unnecessary processing by allowing searchable pages to be skipped. The exact total still depends on which pages require recognition and how the integration accounts for the operation.
A practical validation checklist
- Confirm the PDF’s text layer on several representative pages.
- Choose
Draftfor mostly searchable files andHighfor scan-heavy or image-only files. - Set
ocrWhenNeededto the quoted string"true"when searchable pages should be skipped. - Use the source-language format required by the integration if automatic detection is wrong.
- Preserve the documented string-versus-boolean types.
- Handle a
202response by polling itsLocationURL. - Base64-decode
docContentbefore saving the output PDF. - Verify search, copying, and a few difficult pages in the resulting file.
Bottom line
Draft and High are PDF4me processing choices tied to the character of your input, not universal OCR grades. Use Draft for a normal PDF with an existing text layer, High for scanned pages that need full recognition, and ocrWhenNeeded: "true" to avoid reprocessing pages that are already searchable. Treat the one-call and two-calls-per-page figures as vendor-published usage guidance, keep REST field types exact, and decode the Base64 result before treating the job as complete.
Quick Recap
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