Buckeye Social

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  Events

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  Friends page

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  Profile

We are on the developer track

Inspiration

We saw many people on campus and social media have difficulties in finding friends/meaningful relationships. We found this to be attributed mainly to anxiety of approaching new people which over 60% of college students face. We wanted to fix these problems by creating a site which helps students find events and people with similar interests to meet up with!

What it does

Buckeye Social is an OSU-exclusive social platform that helps students overcome the anxiety of meeting new people by connecting them based on shared interests. The platform uses AI to generate personalized activity plans in Columbus, allows students to discover and message potential friends with similar hobbies, and provides real-time weather updates and local place recommendations. Users can create profiles highlighting their interests, explore curated Columbus locations with live data from Google Places API, save custom plans, and build meaningful connections through an integrated messaging system.

How we built it

We built Buckeye Social using React and TypeScript for a responsive frontend, with Tailwind CSS and shadcn-ui for modern UI components. The backend runs on Lovable Cloud (Supabase), providing real-time database functionality, user authentication, and serverless edge functions. We integrated Google Places API to fetch live venue data and photos, OpenWeather API for real-time Columbus weather, and Lovable AI for intelligent activity plan generation. The architecture uses Row-Level Security policies to protect user data and real-time subscriptions for instant updates on friend activity.

Challenges we ran into

Integrating multiple external APIs (Google Places, OpenWeather) while maintaining fast load times was challenging. We had to implement location biasing for Columbus-specific search results and graceful fallbacks when API data wasn't available. Managing real-time updates across messaging, activity feeds, and friend requests required careful database design with proper RLS policies. We also faced the challenge of creating an AI prompt system that generates genuinely useful, Columbus-specific activity recommendations based on user interests and budgets.

Accomplishments that we're proud of

We're proud of creating a fully functional social platform in such a short time with real-time messaging, AI-powered recommendations, and live external data integration. The interest-based matching system helps students find like-minded peers without the pressure of random encounters. Our Columbus-focused explore page with live place photos, ratings, and weather data makes it easy for students to discover new spots. The clean, responsive UI makes the platform accessible on any device, and our secure authentication system ensures OSU-only access.

What we learned

We learned how to effectively integrate multiple APIs while maintaining performance and handling API failures gracefully. Working with real-time databases taught us about Row-Level Security and how to protect user data properly. We gained experience designing AI prompts that generate contextually relevant content and building responsive, accessible UIs with modern frameworks. Most importantly, we learned how to scope a project appropriately for a hackathon while still delivering core features that solve real problems.

What's next for Buckeye Social

We plan to add group chat functionality for students to form interest-based communities, implement an interactive map view for exploring Columbus, and enhance the AI to provide even more personalized recommendations. We want to add event creation and RSVP features, integrate campus dining and study spot recommendations, and build a reputation system to encourage positive interactions. Long-term, we'd like to expand to other universities and add features like study buddy matching and campus event discovery.

Built With

• ai
• google-places
• lovable-cloud-(supabase)
• openweather-api
• react
• tailwind-css
• typescript