OCR Tools and API

OCR.space

An online OCR website and API for extracting text from images and PDFs, with searchable PDF and developer workflow options.

Known for

Online OCR and OCR API

Input types

Images and PDFs

Domain created

November 11, 2015

The OCR.space logo used as the brand image for the website page.View logo on OCR.space

What OCR.space is

OCR.space official site is a web OCR service for turning images and PDF files into machine-readable text. Its homepage combines a browser upload tool with links to an OCR API, searchable PDF creation, and OCR software options.

Online OCR workflow

The public tool accepts image or PDF input by file upload or by pasted source URL. The page describes common steps as upload file, start OCR, and view the result, which keeps the workflow understandable for people who only need a quick text extraction job.

Image and PDF recognition

OCR.space positions the service around extracting text from scanned images, photos, and multi-page PDF documents. That makes it useful when text is visually present in a file but cannot be copied, searched, or processed as ordinary digital text.

OCR API

The OCR API page describes a REST API that returns extracted text results in JSON format. It supports image and multi-page PDF input, includes examples for languages such as C#, Java, JavaScript, Node.js, PHP, Python, Ruby, and cURL, and distinguishes GET URL-based calls from POST uploads or base64 submissions.

Plans and limits

The API documentation says the free OCR API plan has a limit of 500 requests per day per IP address, with file-size and PDF-page limits shown in the plan table. Paid PRO and PRO PDF plans are presented for higher limits, faster response times, regional endpoints, and on-premise options.

Searchable PDF output

Besides plain text extraction, OCR.space highlights searchable PDF creation. This is useful for scanned documents because the visible page can remain familiar while a hidden text layer makes search, copy, indexing, and accessibility workflows easier.

Who uses OCR.space

OCR.space is used by students, researchers, office workers, developers, archivists, support teams, and small businesses. Typical jobs include extracting text from screenshots, scanning receipts or forms, making PDFs searchable, testing OCR before choosing a platform, and adding OCR to a lightweight app or automation script.

How it compares

Compared with broad PDF toolkits such as Smallpdf, iLovePDF, PDF24 Tools, and PDF Candy, OCR.space is more focused on text recognition. Compared with general converters such as CloudConvert or Convertio, it is less about changing file formats and more about recovering text from visual documents.

Why it matters

OCR helps bridge the gap between visual documents and usable data. A quick online OCR tool can save manual retyping, while an API can turn the same capability into part of a document intake, indexing, compliance, education, or research workflow.

WHOIS domain data

Data pulled: May 22, 2026View current WHOIS record

Domain: ocr.space
IP address: 172.67.208.182
Registrar: NameCheap, Inc.
WHOIS server: whois.namecheap.com
Referral URL: https://www.namecheap.com/
Created: November 11, 2015
Updated: August 1, 2025
Expires: November 11, 2034
Nameservers: jonah.ns.cloudflare.com (108.162.193.186); sara.ns.cloudflare.com (108.162.192.144)
Domain status: clientTransferProhibited
Contact privacy: Registrant, admin, and technical contact details are redacted by Withheld for Privacy ehf.

Key concepts

OCR, or optical character recognition, converts text visible in an image or scan into text that software can process.
Searchable PDFs usually keep the page image while adding an invisible text layer for search and copying.
OCR quality depends on scan clarity, language, layout, image noise, handwriting, and the recognition engine.

Common workflows

Upload a PNG, JPG, WebP, or PDF and extract text from the file.
Paste a URL to a source file and run OCR without first downloading it locally.
Call the OCR API from scripts or applications and consume extracted text as JSON.

Common misconceptions

OCR output is not guaranteed to be perfect, especially with low-quality scans, small fonts, tables, or unusual layouts.
Making a PDF searchable does not automatically prove that every character was recognized correctly.
An OCR API is not the same as a full document-understanding system; downstream validation is still important.

Open questions

How will OCR tools combine text recognition with layout detection, translation, and document summarization?
Will privacy expectations push more OCR processing toward browser-side or on-premise options?
How should OCR services communicate accuracy limits before users rely on extracted text in important workflows?