AI PDF Accessibility Audit Tool
Audit, triage, and remediate PDFs at scale. ASAP PDF AI helps agencies discover, audit, prioritize, and remediate PDFs across their public websites, combining traditional ML and LLMs to reduce the work needed for ADA and WCAG compliance.
By April 26, 2026, ADA-compliant government websites must meet WCAG 2.1 AA accessibility standards. PDFs are often the final remaining barrier to full compliance.
Government and university websites often host hundreds or thousands of PDFs accumulated over years. Manual accessibility auditing is impractical at scale. ASAP PDF AI automates the discovery, classification, and remediation prioritization so your team can focus on fixing the right documents first.
Technical overview
ASAP PDF AI combines three main layers to automate the accessibility audit workflow.
Discovery
A web crawler identifies all PDF documents across your public website, building a complete inventory of documents that need accessibility review. Works across any CMS without code changes.
Classification and Extraction
Traditional ML classifies documents by type, complexity, and remediation priority. Text extraction identifies accessibility barriers: missing alt text, untagged content, reading order issues, and more.
AI-Assisted Decisioning
LLMs generate document summaries, check for exception conditions, and produce remediation recommendations. The system flags which PDFs to fix first, which to archive, and which to replace with web content.
What the audit covers
A complete PDF accessibility audit powered by AI, designed specifically for the scale of government and university websites.
Code for America launched pilots with Salt Lake City and the state of Georgia. We support onboarding for other governments and universities seeking to meet the April 2026 WCAG 2.1 AA deadline.
The ASAP PDF AI audit tool is available at no cost for government agencies and accredited universities. Contact us to confirm eligibility and begin your audit.
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