EqualWeb PDF Tools vs PAVE 2.0

EqualWeb PDF Tools combines PDF accessibility checking, automated remediation, expert manual remediation, and an accessible in-browser viewer. Its checker performs more than 80 automated checks across eight categories and returns a score from 0 to 100 with a detailed report. AI remediation can address document structure, reading order, alternative text, tables, forms, fonts, text encoding, contrast, language, and metadata. Scanned PDFs can receive OCR and remediation, up to 400 pages. Batch processing supports up to 1,000 PDFs; individual files can be as large as 400 pages and 100 MB, though larger files may be uploaded and flagged during an audit. Word, Excel, and PowerPoint files can be converted to accessible PDF or HTML, and PDFs to accessible HTML. The product says it remediates and validates against WCAG 2.2, PDF/UA-1 and PDF/UA-2, Section 508, and EN 301 549. A REST API handles uploads, audits, reports, remediation, downloads, and batches, with access requested from EqualWeb. Auto AI Tag is optimized for English and Latin-script documents.

PAVE 2.0 is a free, web-based, AI-powered tool for remediating PDF documents. Developed by the ICT Accessibility Lab at the ZHAW Institute of Computer Science, it guides users through an eight-step workflow. Users can group and adjust regions such as paragraphs, headings, figures, tables, formulas, and captions. They can set the reading order of page regions for screen readers, organize heading levels, and define table and list structures. The tool supports adding or editing alternative text for figures and mathematical formulas. A final check lets users review results and add metadata; the page states that an accessible PDF needs at least a title, author, and language. PAVE 2.0 lists PDF tagging, reading-order, alternative-text tools, and PDF/UA support. It is not suitable for confidential information, particularly sensitive personal data involving health, political, religious, or ethnic origin. The tool warns that editing may change PDF content or presentation, leaving users responsible for reviewing generated files. ZHAW states that it assumes no liability for generated PDFs.