SBIR Phase II: The Automated Digital Navigability Testing and Remediation Platform

Award ID: 2540148

The broader impact of this SBIR Phase II project is to make digital experiences fully navigable for artificial intelligence agents, web crawlers, and all Americans. The project advances scientific understanding by introducing novel algorithms that automatically trace usability violations detected at runtime in web browsers back to their precise locations in source code. This capability enables automated remediation rather than static reporting, establishing a durable competitive advantage as the only platform offering end-to-end compliance correction. The resulting subscription-based software platform initially targets eCommerce organizations. By reducing compliance timelines from six months to approximately two weeks at substantially lower cost than manual audits, the technology supports rapid commercial adoption. This SBIR Phase II project addresses a longstanding and unsolved technical challenge in digital accessibility by automating navigability compliance through direct source code analysis and remediation. Existing tools can detect usability violations in rendered web pages but are unable to trace those issues back to specific source code locations or generate corrective actions, leaving remediation costly and largely manual. This project will integrate artificial intelligence, automated keyboard navigation testing, virtual screen reader emulation, computer visionbased zoom testing, and cross-platform orchestration frameworks to identify at least 75 percent of World Wide Web Consortium WCAG compliance issues for web applications and 25 percent for mobile applications, while automatically remediating 50 percent of web violations and delivering the first automated fixes for mobile environments. The core technical advance is a novel staticdynamic re-association algorithm that maps runtime Document Object Model violations to corresponding Abstract Syntax Tree nodes in source code, enabling precise, one-click remediation at the line level. Phase II outcomes will include a validated platform that achieves the highest level of automated navigability coverage in the industry across both web and mobile applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Lindsay Portnoy