AI AccessGuard

Inspiration

The inspiration behind AI AccessGuard came from the observation that many websites still contain accessibility barriers that prevent users with disabilities from having equal access to digital experiences. Developers often want to create accessible applications, but identifying and understanding accessibility issues can be time-consuming and requires specialized knowledge.

We wanted to build a tool that makes accessibility testing easier by combining automated analysis with AI-powered explanations, helping developers understand not only what problems exist but also how to fix them.

What we built

AI AccessGuard is an AI-powered accessibility auditing platform that analyzes websites for potential accessibility issues and provides clear, developer-friendly recommendations.

The MVP focuses on creating the foundation for an intelligent accessibility analysis system. The platform is built with a modern full-stack architecture, with a React frontend for user interaction and a FastAPI backend prepared for future scanning and AI analysis capabilities.

How we built it

The frontend was developed using React, Vite, and Tailwind CSS to create a responsive and clean user interface.

The backend was developed using Python FastAPI and Uvicorn, with a structured API architecture, environment configuration, and CORS integration between frontend and backend.

The current foundation includes:

• React frontend setup
• FastAPI backend setup
• API health-check endpoint
• Environment configuration
• Full-stack project structure

Future versions will expand this foundation with website scanning, WCAG compliance analysis, AI-generated explanations, accessibility reports, and automated improvement suggestions.

Challenges

One of the main challenges was designing a scalable architecture that could support future AI-powered accessibility analysis while keeping the MVP lightweight.

Another challenge was selecting tools and frameworks that allow fast development while maintaining clean separation between frontend, backend, and future AI services.

Through this project, we learned how to design a full-stack application foundation and prepare it for advanced AI-driven features.

Built With

• accessibility
• api
• cors
• css
• fastapi
• frontend
• full
• github
• html
• javascript
• json
• learning
• machine
• node.js
• npm
• python
• react
• rest
• stack
• tailwind
• uvicorn
• vite
• wcag
• web