Home
News
Tech Grid
Interviews
Anecdotes
Think Stack
Press Releases
Articles
  • Enterprise AI

Allyant Unveils AI-Powered PDF Accessibility Software


Allyant Unveils AI-Powered PDF Accessibility Software
  • by: Source Logo
  • |
  • July 9, 2025

Allyant, a leader in accessible document solutions, has launched an enhanced version of its CommonLook PDF remediation software, now featuring AI-powered auto-tagging and a web-based interface. This update addresses the critical need for accessible PDFs, ensuring compliance with global standards and supporting users of all abilities.

Quick Intel

  • Allyant upgrades CommonLook PDF with AI-driven auto-tagging for accessibility.

  • Software now offers simplified and advanced editors for all user skill levels.

  • Web-based access supports any browser and operating system, including MacOS.

  • Addresses accessibility issues in over 90% of online PDFs.

  • Helps organizations meet ADA and EAA compliance deadlines by 2026-2027.

  • Includes validation reports to ensure WCAG, PDF/UA, and HHS compliance.

AI-Driven Accessibility for PDFs

Allyant’s latest CommonLook PDF release introduces AI-powered automation, leveraging predictive machine learning to streamline document tagging. This innovation simplifies the remediation process, making it accessible to non-technical users and large teams. Ariel Kunar, Allyant’s Chief Executive Officer, stated, “This expansion marks a pivotal moment in our mission to make digital accessibility scalable for organizations of all sizes. By leveraging the power of AI to accelerate progress and giving users the option of a simplified or advanced editing path, we're breaking down barriers to achieve accessibility.”

Addressing a Global Accessibility Challenge

With over 90% of the trillions of online PDFs estimated to have accessibility issues, organizations face significant challenges in meeting compliance standards. The updated CommonLook PDF software tackles this issue by offering a streamlined interface and powerful automation tools. It supports compliance with the Web Content Accessibility Guidelines (WCAG), PDF/UA, and HHS standards, helping organizations meet regulatory requirements, such as the U.S. Department of Justice’s Title II of the ADA and the European Accessibility Act (EAA), with deadlines in 2026 and 2027.

Flexible and Scalable Solution

The software now offers both simplified and advanced editors, catering to users of varying expertise and PDFs of different complexities. Previously limited to desktop use, CommonLook PDF is now accessible via any browser on any operating system, including MacOS, expanding its reach. Ferass Elrayes, Allyant’s Chief Technology Officer, noted, “This is more than a product expansion—it’s a game-changing step forward for digital inclusion. By bringing our powerful tools to more users, we’re meeting organizations where they are—equipping them to meet impending compliance deadlines and create PDF content that is accessible for all.”

Compliance and Validation

Each remediated PDF comes with a unique Validation Report, verifying compliance with global accessibility standards. This feature ensures organizations can confidently demonstrate adherence to regulations, addressing the urgent need for accessible digital communications in sectors like government, education, and healthcare.

Allyant’s AI-driven CommonLook PDF software represents a significant advancement in digital accessibility, empowering organizations to create inclusive content efficiently. By combining cutting-edge technology with user-friendly design, Allyant is paving the way for scalable, compliant PDF remediation worldwide.

 

About Allyant

Allyant is a leading provider of accessible document, digital, and alternative format print communications solutions, helping organizations achieve compliance with accessibility standards. Allyant empowers businesses, government agencies, and educational institutions with industry-leading software, tools, and expert guidance to create inclusive communications for all users.

News Disclaimer
  • Share