The PDF Association has launched a new “Topics” menu on pdfa.org to enhance navigation and access to authoritative, structured information on PDF technologies and standards.
UPDF earns Leader status in G2 Spring 2026, highlighting its AI-powered features, strong usability, and rapid growth to over 4 million users worldwide.
Ensure ADA Title II compliance with WCAG 2.1 AA. Learn how accessible PDFs, proper tagging, OCR, and structured documents reduce legal risk for public entities.
The new pdfRest Python SDK brings fast, typed PDF processing with intuitive functions, reducing boilerplate and accelerating document-driven development.
How do you license (or not!) AIs to mine your PDFs? In this article we clarify the use of TDMRep’s reservation of rights in XMP metadata for PDF and PDF/A.
Hancom releases OpenDataLoader PDF v2.0 with benchmark-leading PDF extraction, a hybrid AI engine for on-premise security, four free AI add-ons(OCR, Table, Formula, Chart), and a switch to Apache 2.0 licensing.
A practical checklist to evaluate whether your document process is ready for generating accessible PDF mass documents. Learn which structural conditions are needed to produce PDF/UA-compliant PDFs automatically and at scale without manual remediation.
The European Accessibility Act (EAA) makes accessible PDF generation for mass documents an architectural requirement. Manual PDF remediation no longer scales: Organizations need system-integrated, reproducible processes to ensure compliant and consistent output.
A document claiming conformance to PDF/A’s conformance level “b” can be visually perfect and machine-unreadable at the same time. This is not a bug — it is what the standard was designed to do. Understanding the difference between rendering a glyph and encoding a character is the first step to building archives that AI can actually use.
Most enterprise AI initiatives are failing not because of the model — but because of the document. This whitepaper examines why flat, image-based PDFs render corporate archives invisible to RAG pipelines and LLMs, and makes the operational case for cloud-native OCR, PDF/A-2u standardisation, and zero-trust document architecture as the three non-negotiable preconditions for an AI-ready data lake.