Nero Labs Bulk OCR – Image & PDF to Text

x402

Nero Labs Bulk OCR – Image & PDF to Text is a paid API for AI agents from x402-agent-tools.nerolabs.workers.dev, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-22).

Extracts text from up to 10 images or PDFs per call using OCR across 100+ languages, returning per-file and per-page text with confidence scores

Price / call$0.005

Seller volume →—

Success—

StatusUnknown

How this service works

Pay-per-call tools for AI agents, 31 in all: read web pages and RSS feeds, OCR, PDF text, transcription; email, phone and domain checks; UK, Irish and Polish company lookups and UK risk reports; website contacts, tech stack and SEO audits; PageSpeed; AI review, job post and row enrichment; data cleaning, joins, dedupe and diffs; US and EU compliance rules. No account or API key: pay each call in USDC on Base over x402.

Output

A JSON object with a 'rows' array containing one entry per file: the extracted full text, OCR status, page count, pages read, word count, character count, confidence score, file type, blank page count, and optionally a 'pages' array with per-page text, recognition method, confidence, and word count.

Example use cases

Digitise scanned archive documents

“I have 8 scanned TIFF images of old legal contracts — can you run OCR on all of them in English and return the full text per file with confidence scores so I can search them?”

Extract text from multilingual receipts

“Please OCR these 5 receipt JPEGs, they're a mix of French and Spanish text, and give me the per-page breakdown including word counts and confidence.”

Process born-digital PDFs with text layer

“I've got 10 PDF reports — some are scanned, some are born-digital. Can you extract the text from all of them, using the existing text layer where available and OCR where not, up to 20 pages each?”

Technical details

Endpoint

POSThttps://x402-agent-tools.nerolabs.workers.dev/ocr?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need to batch-process multiple image or PDF files (up to 10 per call) with multilingual OCR support, per-page granularity, and confidence scoring. It is especially well suited for scanned documents, mixed born-digital/scanned PDFs, and workflows requiring structured per-file metadata alongside raw text. Prefer it over single-file OCR tools when cost control per file matters (maxPagesPerFile cap) or when processing documents in non-Latin scripts.

Side effects

Invalid or inaccessible file URL returns error status in that row's ocrStatus field
Unsupported file format results in failed OCR status
maxPagesPerFile exceeded silently truncates output (pagesTruncated: true)
Low-quality scan produces low confidence scores or garbled text
Unsupported language code causes recognition failure or falls back to English
Timeout for very large or high-DPI PDFs if processing exceeds worker limits
Payment failure (x402) blocks the call before processing begins

Input

Schema · Request body

Field	Type	Description
dpi	integer	Resolution used to render PDF pages before recognition. 200 suits most scans; 300 helps small print and takes about twice as long; 150 is faster for large clean type. Images are used at their own resolution, enlarged when small and capped at 4000 pixels on the longest side.
fileUrls	array	A plain list of image (PNG, JPEG, WebP, GIF, BMP, TIFF) or PDF links, for a quick one-off run with no spreadsheet. Use the dataset, file or Google Sheet inputs above to keep your own columns alongside the results.
languages	array	Tesseract language codes, one per line, for example eng, deu, fra, spa, por, ita, nld, pol, rus, jpn, chi_sim, chi_tra, ara, hin, kor. Several codes read mixed documents. English is built in; any other language is downloaded once at the start of the run (5 to 15 MB each). Picking the right language
includePageText	boolean	Add a 'pages' array with each page's text, method (OCR or copied text layer), confidence and word count, on top of the combined text. Useful for citing a page number, and it makes rows larger.
maxPagesPerFile	integer	Pages read from each PDF before stopping. This is also your cost ceiling per file: a 300-page scan cannot run up a bill you did not expect. Images always count as one page.
usePdfTextLayer	boolean	A born-digital PDF page already contains its text. When this is on, such pages are copied exactly and charged at the low text-layer rate instead of being rendered and recognised. Turn it off to force OCR on every page, for example when a PDF's text layer is known to be garbage.
pageSegmentation	string	How the engine should look for text. 'Automatic' handles documents, receipts and letters. 'Sparse' finds scattered text on screenshots, slides and product photos. 'Single block' suits a cropped paragraph, 'single column' a narrow receipt, 'single line' a cropped field.
minWordConfidence	integer	Drop words the engine is less sure about than this, from 0 to 100. Leave at 0 to keep everything and judge by the reported confidence instead. Raising it cuts noise out of poor scans at the cost of real words.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "rows": [
      {
        "fileType": "png",
        "ocrPages": 1,
        "charCount": 346,
        "ocrStatus": "ok",
        "pageCount": 1,
        "pagesRead": 1,
        "sourceUrl": "https://nerolabs-samples.nerolabs.workers.dev/sample-receipt.png",
        "wordCount": 65,
        "blankPages": 0,
        "confidence": 91.8,
        "resolvedUrl": "https://nerolabs-samples.nerolabs.workers.dev/sample-receipt.png",
        "statusDetail": null,
        "pagesTruncated": false,
        "textLayerPages": 0
      }
    ],
    "count": 1,
    "_example_note": "Real output, trimmed: long lists cut to their first items, fields and text shortened."
  }
}

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