CUNY Guide

Cuny Tech Prep Cohort 10 Hackathon

Made by Daniel, Jair, Ahmad, and Kazi

Demo Video

Try out the App here

🚀 Inspiration

CUNY students often struggle to find and access campus resources. We were inspired to create a solution that makes essential information easily accessible to all students, regardless of their campus or background.

🔍 What It Does

CUNY Guide is an AI-driven platform that assists CUNY students in locating campus resources. It provides personalized information on various topics, such as:

• Food pantry locations
• Study spots
• Other essential services across all CUNY campuses

🛠 How We Built It

We developed CUNY Guide using the following technologies:

• React: For the frontend, ensuring a responsive and user-friendly interface.
• Express.js: For the backend API.
• MongoDB: For storing user feedback and enhancing our knowledge base.
• OpenAI's GPT Model with RAG (Retrieval-Augmented Generation) Technology: For intelligent responses.
• Chakra UI: For sleek, accessible design components.
• Web Scraping Tools: To collect data from CCNY's official websites.
• Data Cleaning and Processing Scripts: To prepare the scraped information for our system.

🤖 RAG (Retrieval-Augmented Generation)

⚠️ Challenges We Ran Into

• Implementing RAG technology to provide accurate, campus-specific information.
• Designing a system that could scale across multiple CUNY campuses.
• Balancing the need for personalized information with user privacy concerns.
• Scraping and cleaning data from various CCNY web pages to create a comprehensive, accurate dataset.

🏆 Accomplishments That We're Proud Of

• Successfully integrating AI technology to provide personalized guidance.
• Creating a user-friendly interface that makes complex information easily accessible.
• Developing a system that learns and improves from user feedback.
• Building a robust dataset of CCNY resources through web scraping and data cleaning.

📚 What We Learned

• The importance of user-centered design in creating accessible technology.
• How to effectively combine AI with traditional web technologies.
• The complexities of managing and presenting campus-specific information at scale.
• Techniques for efficient web scraping and data cleaning to build a reliable knowledge base.

🔮 What's Next for CUNY Guide

• Expanding our web scraping and data processing pipeline to cover all CUNY campuses.
• Implementing user authentication for personalized chat experiences and chat history.
• Developing a more robust feedback system to continuously improve our knowledge base.
• Creating mobile apps for iOS and Android for easier access.
• Partnering with CUNY administration to integrate official resources and updates.
• Enhancing our RAG system to better handle diverse queries.