Coursify empowers Queen’s students to make data-driven course decisions through comprehensive grade analytics and AI-powered insights. The platform features a RAG chatbot trained on thousands of student reviews from Reddit and RateMyProfessors, providing personalized recommendations on professors, workload, and teaching styles. Historical grade distributions spanning 10+ semesters reveal true course difficulty trends. Built with a multi-repository microservices architecture, automated web scrapers continuously gather data from Queen’s calendars and student review platforms, storing vector embeddings for semantic search.
Launch is coming next semester.
Coursify landing page
Tech Stack
Next.js · TypeScript · Python · Playwright · RAG · PostgreSQL · Vercel
Key Features
- RAG-powered AI chatbot delivering personalized course and professor recommendations
- Historical grade distribution analytics across 10+ semesters (2015–present)
- Automated web scraping pipeline for Reddit, RateMyProfessors, and Queen’s calendar data
- Vector database with semantic search for intelligent course matching
- Real-time course search with advanced filtering and comparison tools
- Multi-repository microservices architecture for scalable data processing
- Mobile-responsive UI built with Next.js
- PostgreSQL backend managing authentication and data
Gallery
Queen's Answers AI chatbot
Course search
Grade distribution analytics
Student comments and reviews
Data upload pipeline