Inspiration
We were inspired by the limitations of traditional education, where students often follow the same learning approach despite having different strengths, weaknesses, and learning speeds. We wanted to create a platform that combines personalized learning, AI assistance, and collaborative study.
What it does
Catalyst provides AI-generated assessments, personalized learning paths, performance-based roadmaps, practice questions, career recommendations, and an AI study assistant. It also supports study groups, real-time chat, and video meetings with whiteboard collaboration.
How we built it
We built Catalyst using React.js, Node.js, Express.js, MongoDB, Gemini AI, Groq AI, Socket.IO, WebRTC, JWT Authentication, and Tailwind CSS. AI powers personalized learning and assessments, while Socket.IO and WebRTC enable real-time communication and video collaboration.
Challenges we ran into
Our main challenges were integrating multiple AI features, maintaining personalized recommendations, and implementing real-time chat, video meetings, whiteboard, and collaboration within one platform.
Accomplishments we're proud of
We are proud of combining AI-powered personalized learning and real-time collaborative learning into a single platform instead of building just another AI chatbot.
What we learned
We learned how to integrate AI APIs, build full-stack applications, manage real-time communication with Socket.IO, implement video communication using WebRTC, and connect multiple modules into one platform.
What's next for Catalyst
We plan to improve AI personalization, advanced learning analytics, collaborative features, and educator-focused insights to make Catalyst a more complete AI-powered learning ecosystem.