Doc Extract
Doc Extract combines a high-fidelity OCR pipeline with specialized language models to automatically extract key information from your documents. The service handles invoices (line items, amounts, VAT), resumes (skills, experience, education), ID documents (name, date of birth, number), and certificates (dates, signatories, references). Extracted data is returned as structured JSON, ready to integrate into your information system.
How it works
Document upload
Send your PDF, image, or DOCX file via the REST API. The service automatically detects the document type.
OCR and pre-processing
The document is analyzed by our OCR pipeline, which corrects orientation, improves contrast, and extracts raw text.
LLM extraction
A specialized language model analyzes the extracted text and identifies the relevant fields based on the detected document type.
Structured data
Extracted data is returned as structured JSON with a confidence score per field, ready for integration.
API call example
import httpx
response = httpx.post(
class="text-teal">"https:class="text-text-faint italicclass="text-teal">">//api.djinn.dev/v1/extract",
headers={class="text-teal">"X-API-Key": class="text-teal">"djinn_live_..."},
files={class="text-teal">"file": open(class="text-teal">"invoice.pdf", class="text-teal">"rb")},
data={class="text-teal">"document_type": class="text-teal">"invoice"},
)
result = response.json()
print(fclass="text-teal">"Vendor: {result['vendor_name']}")
print(fclass="text-teal">"Total (incl. tax): {result['total_ttc']} EUR")
print(fclass="text-teal">"Confidence: {result['confidence']:.0%}")
for line in result[class="text-teal">"lines"]:
print(fclass="text-teal">" - {line['description']}: {line['amount']} EUR")Technical specifications
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