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Created by team trescomas on February 23, 2024

WebAlly is an AI-powered code-writing software that helps developers and designers create ARIA-compliant websites, focusing on improving web accessibility for the disabled, particularly those with visual impairments. By simply pasting your webpage URL, WebAlly generates a detailed accessibility report for your website, an ARIA (Accessible Rich Internet Applications) compliance score , and updated code to implement those recommendations! The tool leverages GPT-4 to analyze website code (we use BeautifulSoup for scraping your website's content and code), identifying accessibility issues and calculating an ARIA compliance score on a 0-10 scale. This score assesses adherence to the W3C (World Wide Web Consortium’s) ARIA accessibility standards. WebAlly's not only pinpoints issues but also generate revised code using OpenAI, enabling developers to easily implement changes and make their websites more inclusive for users with disabilities. We use TrueLens text-to-text eval to log and get feedback for our LLM Key Functionalities: Website Scraping: Upon receiving a URL input from the user, the application extracts HTML and CSS content from the specified website. This process forms the basis for a thorough accessibility evaluation. Accessibility Report Generation: Using the scraped website content, the web app analyzes the site for potential accessibility issues. This function leverages the capabilities of a GPT-4 to interpret the website's content and identify areas that might hinder accessibility. ARIA Compliance Scoring: The application calculates an ARIA compliance score on a scale of 0 to 10. This score quantitatively reflects how well the website adheres to established accessibility standards, particularly those pertinent to creating accessible web applications.

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"I love how in depth and specific this implementation is and I can tell that this would be a powerful tool for web devs and even for people into cybersecurity. I like how creative and original this product is and how it takes the time to give a better front end code for a better ARIA score. Great job"


Shebagi Mitra

Technical Mentor

"Great work, need to work a little more on the presentation side but I love the love the in-depth explanation of the app and the overall architecture. Good work! "


Muhammad Inaamullah

Machine Learning Engineer