Auto-Tag a PDF with DeepDoctection

Millions of PDFs are generated every day, but most are not accessible and fail PDF/UA or WCAG compliance. Manual tagging is slow, inconsistent, and not scalable. With the PDFix SDK and DeepDoctection, you can automatically detect document layout, recognize structure, and create accessible, machine-readable PDFs in minutes.

DeepDoctection + PDFix: AI-Powered Auto-Tagging

DeepDoctection is a Python toolbox for document layout and structure detection using deep learning models. When integrated with PDFix SDK, it becomes a powerful end-to-end pipeline for analyzing, understanding, and auto-tagging complex PDFs.

You can find the example project on GitHub: PDFix Auto-Tag DeepDoctection Example

This demo shows how to:

Extract layout and reading order with DeepDoctection
Use the output JSON to guide PDFix SDK in creating accessible tags
Automate PDF/UA-ready tagging for large batches of documents

Try DeepDoctection live on Hugging Face: DeepDoctection Demo on Hugging Face

A picture shows an output of the process deepdoctection - document extraction and layout analysis.

New In: Enhanced Auto-Tagging Options in PDFix SDK

Since this original integration, PDFix Auto-Tagging has evolved dramatically.
Today, you can choose between 4 intelligent approaches — each designed for a specific level of automation and accuracy:

Quick Auto-Tagging (No Template) – instantly improves accessibility across large PDF sets.
Auto-Generated Templates (Preflight) – uses layout analysis to refine tagging and structure.
Pre-Created Templates – ensures consistent tagging across invoices, statements, and reports.
AI-Generated Templates – integrates models like DeepDoctection, PaddlePaddle, or Textract for advanced adaptive tagging.

Explore all approaches in detail in our latest guide: Auto-Tagging PDFs with PDFix SDK

Integration with AI Models

Today, PDFix supports multiple AI integrations:

DeepDoctection (Open-Source Python) – layout and document extraction
Amazon Textract – OCR and semantic structure analysis for scanned PDFs
PaddlePaddle – advanced visual document understanding
olmOCR and custom LLMs – coming soon via PDFix Marketplace

Each engine can output a JSON template that PDFix uses for consistent tagging, ensuring that the same logic applies across millions of documents — crucial for enterprise-scale accessibility.

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