TeamUP

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  Discover Team mates and hackthons and many more

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What inspired TeamUP-AI? Every hackathon I joined had the same problem — finding teammates was just posting in WhatsApp groups and hoping for the best. You'd end up with people who were available, not people whose skills actually complemented yours. I've seen great ideas die not because of bad execution, but because the team was mismatched from day one. I wanted to fix that. What is TeamUP-AI? TeamUP-AI is a skill-based team discovery platform that matches developers, designers, and creators with the right teammates for hackathons, group projects, and hiring — intelligently, not randomly. Instead of cold-messaging strangers or posting in 10 different groups, you tell the platform what you're building and what you bring to the table. The AI finds people whose skills fill your gaps. How I built it Frontend Built with Next.js and TypeScript — 10 fully responsive screens deployed on Vercel with sub-second load times. Backend & Database Designed the entire backend on Supabase and PostgreSQL with row-level security so users only see data they're supposed to. Real-time sync keeps teammate suggestions live without manual refreshes. Matching Logic Skill-based filtering runs server-side — it doesn't just find people with overlapping skills, it finds people who complement what your team is missing. Infrastructure Stress-tested the architecture to support 5,000+ concurrent users. Currently live with 100+ active users. Challenges I faced The hardest part wasn't the code — it was the matching logic. How do you define compatibility? Skill overlap is easy to compute. But what a team actually needs is someone who fills the gaps, not someone who duplicates what's already there. Getting that recommendation logic right took several iterations. Row-level security in Supabase was another challenge — policies that worked perfectly in development silently blocked legitimate reads in production because the auth context behaved differently. Debugging that taught me more about how production environments differ from local than anything else. What I learned

How to architect a backend that scales, not just one that works That production and local are never the same environment How to ship something real people actually use — and keep it running

Built With

• github
• javascript
• languages-typescript
• react.js-databases-postgresql
• row-level-security-(rls)-tools-git
• sql-frameworks-next.js
• supabase-platforms-&-cloud-vercel-apis-&-services-supabase-auth
• supabase-realtime
• supabase-storage