Automatically detect and locate signatures in PDFs using advanced vision AI. Identifies handwritten signatures, printed signatures, and signature blocks with precise bounding box coordinates. Perfect for contract verification, document authentication, and compliance workflows.
// Detect all signatures in a document
const formData = new FormData();
formData.append('document_file', pdfFile);
const response = await fetch('/api/signature-detection', {
method: 'POST',
headers: { 'X-API-Key': 'your-api-key' },
body: formData
});
const result = await response.json();
// Get all detected signatures with coordinates
console.log('Total signatures found:', result.signature_items.length);
result.signature_items.forEach(item => {
console.log('Signature found on page:', item.page);
console.log('Bounding box:', item.bbox); // [x1, y1, x2, y2, x3, y3, x4, y4]
console.log('Confidence:', item.confidence); // 0.0-1.0
});
// Page metadata
console.log('Pages processed:', Object.keys(result.page_metadata).length);Detects handwritten signatures, printed signatures, and signature blocks
Get exact bounding box coordinates for every signature
Efficiently processes entire documents with intelligent batching
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Vision AI for contract verification and document authentication
Detect all signatures automatically with precise coordinates and confidence scores. Perfect for contract verification, document authentication, and compliance workflows.
Automatically verify that contracts and agreements have been signed
Common uses:
Verify signature presence
Check signature locations
Verify document authenticity by detecting and locating signatures
Common uses:
Pre-processing signature checks
Document validation workflows
Process legal documents to ensure proper signature placement
Common uses:
Legal document review
Signature verification
Create comprehensive records of signature locations in documents
Common uses:
Signature location mapping
Audit trail generation
Why automation beats manual verification
Stop manually reviewing every page. Use vision AI to automatically detect and locate all signatures.
| NinjadocAI | Template OCR | Generic LLM/AI API | |
|---|---|---|---|
❓Natural Language Questions | ~ | ||
📍Answer + Coordinate Proof | ~ | ||
⚡5-Minute Integration | ~ | ||
💲Transparent Pricing | ~ | ||
🔧TypeScript SDK + React Components | |||
🧠Context Understanding | ~ | ||
🎯Zero Configuration Required | ~ | ||
📐Handles Document Layout Variations | ~ | ||
🔌Developer-Friendly REST API | ~ |
Everything you need to know
The API uses advanced vision AI to detect handwritten signatures (cursive writing), printed signatures (typed text), and signature blocks (lines with text above/below). It returns precise bounding box coordinates and confidence scores for each detected signature.
Our vision AI achieves 95%+ accuracy in detecting signatures. Each detection includes a confidence score (0.0-1.0) and a signature type (handwritten, printed, or signature_block), allowing you to filter results based on your accuracy requirements.
Each signature includes: precise bounding box coordinates (quadrilateral with 8 floats), page number (1-indexed), confidence score (0.0-1.0), and signature type (handwritten, printed, or signature_block).
Signature detection costs 2 credits per page, with coordinates always included. For example, scanning a 50-page document costs 100 credits ($0.40). Credits never expire.
Yes! The API is designed for contract verification, document authentication, legal document processing, and compliance workflows. The coordinate data provides audit trails showing exactly where signatures were detected.
Documents can be up to 10MB in size and up to 50 pages per request. For larger documents, you can split them into multiple requests.
Complete your document intelligence toolkit