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MentorMatchAI
Inspiration of MentorMatch.AI
Finding the right mentor is often a long and frustrating process. Many students and professionals struggle to connect with experienced guides who understand their goals and challenges. This gap in mentorship opportunities inspired us to create MentorMatch.AI, a platform that makes the mentor-mentee connection simple, smart, and accessible for everyone.
What It Does
- Matches mentors and mentees using Vector Searches
- Offers separate profile registration for mentors and mentees
- Delivers a clean, user-friendly interface for easy navigation
How We Built It
- Designed the frontend with React.js and Tailwind CSS
- Developed backend logic using Django
- Embedded mentor/mentee profiles into vectors for efficient searching (using the all-MiniLM-L6-v2 model)
- Stored records in MongoDB and vectors in Pinecone
- Implemented AI matching using Pinecone’s vector search
Challenges We Ran Into
- Ensuring accurate AI matching between mentors and mentees
- Creating an easy-to-use yet professional user interface
- Coordinating tasks effectively among team members remotely
Accomplishments We’re Proud Of
- Built a fully functional prototype within a limited time
- Designed a clean and professional UI that’s easy for all users
- Worked collaboratively as a team despite varying skill levels
What We Learned
- Gained hands-on experience in building a real-world ML-powered project
- Effective team communication and task distribution
- The incredible power and uses of vector databases
- Learned how to combine technology with social impact
What’s Next for MentorMatch — AI-Powered Career Mentorship Finder
- Adding video conferencing for in-platform mentorship sessions
- Introducing a mentor rating and review system
- Providing AI-generated career roadmaps for mentees
- Supporting multiple languages for global reach
Built With
- django
- github
- machine-learning
- mongodb
- pinecone
- react
- recommendation
- tailwindcss
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