POST$0.01/page

https://pdfmage.app/api/v1/document-ocr

Document OCR

Extract structured text and data from PDF documents using Google Document AI. Get detailed text analysis with confidence scores, language detection, and structured elements.

Request

multipart/form-data

Request Body

filefilerequired

PDF file to extract text from using OCR

Maximum 10MB, PDF format only

OCR Technology

Powered by Google Document AI for industry-leading accuracy across 50+ languages with advanced text detection and structure analysis.

cURL Example

curl --request POST \
  --url https://pdfmage.app/api/v1/document-ocr \
  --header 'Accept: application/json' \
  --header 'Authorization: Bearer pk_live_abc123...' \
  --form 'file=@/path/to/document.pdf'

JavaScript Example

const formData = new FormData();
formData.append('file', pdfFile);

const response = await fetch('https://pdfmage.app/api/v1/document-ocr', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer pk_live_abc123...'
  },
  body: formData
});

if (response.ok) {
  const ocrResult = await response.json();
  console.log('Extracted text:', ocrResult.extractedText.fullText);
  console.log('Pages processed:', ocrResult.extractedText.pages.length);
} else {
  const error = await response.json();
  console.error('Error:', error);
}

Response

application/json

Response Body

fileNamestring - Original filename of processed document

processedAtstring (ISO 8601) - Processing completion timestamp

documentIdnumber - Unique identifier for this OCR operation

extractedTextobject

Complete text extraction results with metadata

fullTextstring - Complete extracted text from all pages

pagesarray - Per-page text extraction results

• pageNumber: number - Page number (1-based)

• text: string - Extracted text for this page

• confidence: number - OCR confidence score (0-1)

metadataobject - Processing metadata

• pageCount: number - Total pages processed

• language: string - Detected document language

• processingTime: number - Processing time in ms

structuredElementsobject

Document structure analysis results

textBlocksnumber - Number of text blocks detected

paragraphsnumber - Number of paragraphs detected

linesnumber - Number of text lines detected

tokensnumber - Number of individual tokens detected

Success Response Example

{
  "fileName": "contract.pdf",
  "processedAt": "2024-01-15T10:30:45.123Z",
  "documentId": 12345,
  "extractedText": {
    "fullText": "Employment Agreement\n\nThis Employment Agreement is entered into between John Doe and Acme Corporation...",
    "pages": [
      {
        "pageNumber": 1,
        "text": "Employment Agreement\n\nThis Employment Agreement is entered into between John Doe...",
        "confidence": 0.98
      },
      {
        "pageNumber": 2, 
        "text": "Compensation and Benefits\n\nThe Employee shall receive an annual salary of $75,000...",
        "confidence": 0.96
      }
    ],
    "metadata": {
      "pageCount": 2,
      "language": "en-US", 
      "processingTime": 1247
    }
  },
  "structuredElements": {
    "textBlocks": 15,
    "paragraphs": 8,
    "lines": 42,
    "tokens": 387
  }
}

Response Headers

HTTP/1.1 200 OK
Content-Type: application/json
X-Credits-Used: 0.02
X-Credits-Remaining: 4.98
X-Credits-Currency: USD
X-Processing-Time: 1247

Error Responses

400

Bad Request

Invalid file format, missing file, or corrupted PDF

401

Unauthorized

Invalid or missing API key

402

Payment Required

Insufficient credit balance

413

Payload Too Large

File exceeds maximum size limit (10MB)

422

Unprocessable Entity

PDF contains no extractable text (blank pages, images only)

Error Response Example

{
  "error": "Bad Request",
  "message": "Invalid file format", 
  "details": {
    "code": "INVALID_FILE_FORMAT",
    "allowedFormats": ["pdf"],
    "receivedFormat": "docx"
  },
  "timestamp": "2024-01-15T10:30:00Z",
  "requestId": "req_abc123"
}

Processing Error Example

{
  "error": "Unprocessable Entity",
  "message": "No extractable text found",
  "details": {
    "code": "NO_TEXT_CONTENT",
    "pageCount": 3,
    "reason": "Document contains only images"
  },
  "timestamp": "2024-01-15T10:30:00Z", 
  "requestId": "req_def456"
}

OCR Capabilities

Multi-Language Support

Supports 50+ languages including English, Spanish, French, German, Chinese, and more.

High Accuracy

Industry-leading OCR accuracy with confidence scores for quality assurance.

Structured Output

Get structured text with paragraph, line, and token-level analysis.

Our OCR service uses Google's enterprise-grade Document AI technology, the same technology used by major corporations for critical document processing.

Common Use Cases

Document Digitization

Convert scanned PDFs and image-based documents into searchable, editable text for digital archiving and processing.

Data Extraction

Extract structured data from invoices, contracts, forms, and reports for automated processing workflows.

Content Analysis

Analyze document content for compliance, classification, or information extraction in legal and regulatory contexts.

Multi-Language Processing

Process international documents with automatic language detection and accurate text extraction across multiple languages.

Quality Assurance

Use confidence scores and structured output to validate OCR results and ensure data quality in production systems.

Preprocessing

Prepare documents for form filling or data mapping by extracting clean, structured text content.