Best AI Models for Auto-Tagging PDFs in 2025: Fast, Accurate, and PDF/UA-Ready

ADA website accessibility lawsuits surged by 37% in the first half of 2025, with 2,014 cases filed. The problem? Around 90% of PDFs are still partially inaccessible to people with disabilities. Traditional methods of tagging documents for accessibility can be time-consuming, manual, and prone to errors. The solution? AI-powered auto-tagging that works with your specific document types.

We integrate with multiple best-in-class AI engines – IBM Docling, PaddleOCR/PaddleX, and Amazon Textract – giving you the flexibility to choose the AI models that deliver the best results for your documents. Even better, our External Actions framework lets you integrate your own preferred AI models. Keep reading to learn how this enhancements work.

Powerful AI Integrations, One Platform

PDFix now connects with leading AI models for automated PDF tagging and accessibility remediation. All three work seamlessly with PDFix Desktop Pro and PDFix SDK (programmatic automation).

IBM Docling: Free, Local, Enterprise-Grade

Best for: General documents, complex layouts, privacy-sensitive content

IBM Research’s Docling AI model is trained on nearly 81,000 manually labeled document pages. It excels at understanding real-world PDF layouts- multi-column documents, nested tables, mixed formatting.

Docling’s efficacy is DocTags, a universal markup format developed by IBM Research that captures and describes all page elements – charts, tables, forms, code, equations, footnotes, captions and more – as well as their contextual relation to one another and location within a document layout.

Key Features:

100% Free: Open-source model, no licensing costs
Runs Locally: Documents never leave your infrastructure
Fast Processing: Auto-tag complete documents in seconds
Layout Intelligence: Handles multi-column layouts, nested tables, mixed formatting
Template Generation: Create reusable templates for batch processing

Perfect for: Healthcare systems, government agencies, financial institutions

Learn more about AI-Powered Auto-Tagging with IBM’s Docling in our latest article.

Amazon Textract: Cloud-Powered OCR

Best for: AWS-integrated workflows, high-volume processing, distributed teams

PDFix now integrates with Amazon Textract, AWS’s cloud-based OCR and document analysis service designed to extract text, structure, tables, and form data from PDFs and images. This cloud-powered workflow delivers fast, scalable auto-tagging inside PDFix Desktop.

With PDFix + Textract, you can auto-tag PDFs, extract structural information, and generate layout templates that accelerate accessibility remediation.

Key Features:

AWS-Backed OCR: Uses Amazon Textract’s text extraction and layout analysis
Fast & Scalable: Ideal for high-volume or distributed enterprise environments
Cloud Processing: Offloads heavy lifting to AWS infrastructure
Seamless Integration: Convert Textract output into accessible PDF tags
Template Generation: Automatically build reusable PDFix layout templates
Batch Processing Ready: Use Desktop or SDK to process entire folders

Perfect for: Organizations already using AWS, teams needing cloud scalability, distributed processing environments, enterprises requiring managed infrastructure.

Learn more about this AI action in our blog post Automated PDF Accessibility Tagging with Amazon Textract and PDFix

PaddleOCR

PDFix integrates with Paddle’s OCR delivering a Dockerized solution to auto-tag PDFs, extract MathML from images, and generate reusable layout templates. Together, PDFix SDK and Paddle turn complex, untagged PDFs into screen reader-friendly documents entirely on your infrastructure.

Key features:

100% Free to Start: Open-source models
Runs Locally: Process sensitive PDFs on your machine via Docker
Multilingual OCR: 80+ language support
MathML Formula Recognition: Extracts LaTeX/MathML from formulas and attaches MathML as associated files to PDF formula tags
Layout Detection: Leverages Paddle’s advanced structure analysis
Template Generation: Automatically creates PDFix layout templates
Batch Process-Ready: Trigger the same Docker action across files

Perfect for: Academic institutions, research organizations, technical publishers, international corporations, multilingual government agencies, scientific papers

Learn more about this AI-powered action in our blog Smarter PDF Auto-Tagging for Accessibility with Paddle AI and PDFix

How to Choose the Right AI Model for Your Documents

Different document types need different AI strengths. Our recommendation – test all three models on sample documents. The output is a tagged PDF, however it is not guaranteed to comply with accessibility standards such as WCAG and PDF/UA, as you may need to perform further remediation to meet those standards. Each AI has different strengths depending on your content.

Model-specific strengths:

Paddle: Mathematical formulas with MathML, multilingual OCR
Textract: Form data extraction, AWS ecosystem integration
Docling: Superior complex layout understanding, fastest processing

By automating the tagging process, businesses can significantly reduce the time spent on ensuring document accessibility. The Auto-tagging feature improves both speed and accuracy, ensuring compliance with accessibility standards without the need for extensive manual review.

Most customers automate 70-98% of document processing with PDFix SDK, reserving human review only for subjective elements like alt text.

Complete Accessibility Workflow

Auto-Tag with AI → Choose Docling, Paddle, or Textract based on document type
Generate Layout Template → Create reusable patterns for similar documents
Batch Process → Apply templates to entire folders
Validate → Built-in validation tool assesses the document according to the machine-verifiable requirements of PDF/UA and WCAG, provides a detailed accessibility report that identifies errors
Refine → Add alt text and handle edge cases requiring human judgment
Export → Screen reader-ready, compliant documents

Bring Your Own AI Model

Have a favorite AI model that works perfectly for your document types? Our External Actions framework makes it straightforward to integrate any AI model into the PDFix platform. These integrations allow PDF pages to be analyzed visually by AI models, converted into reusable JSON templates, and automatically tagged for accessibility.

Why Multiple AI Models Matter

No single AI model is perfect for every document type. Scientific papers need formula recognition. Scanned contracts need multilingual OCR. Born-digital reports need layout intelligence. Financial tables demand precision.

PDFix gives you choice: free local processing with Docling or Paddle, cloud scalability with Textract, or integration with your own preferred AI model. Test all options and find what works best for your specific content.