WorkHere

Inspiration

We know that many students struggle to find a suitable study spot and want to have a study group to work on their academics. So we built WorkHere, an interactive web for the Bay Area students to quickly and accurately find the best study spots and connect to study groups around the Bay Area.

What it does

WorkHere lets users find the best study spot through our data model and student-focused filters. Students can also leave reviews, share real-time feedback, and get directions through Google Maps. Moreover, WorkHere lets students have their own profile and connect by invitation and study in the same spot together. -Data model of the study spot, including name, location, and distance -Filter system including WiFi strength, noise level, seating, outlets, and hours -A login page that links to the endpoint table memory to save user information. -Personal Profile includes user name, user image, major, user ID, login information, and history of previous study spots users have visited. -Privacy settings to determine status(open/closed) and invitations(accepting/do not disturb), to ensure users' security.

How we built it

Frontend: React.js Backend: Node.js + Supabase Database: Supabase (PostgreSQL + Auth + Storage)

Challenges we ran into

Integrating friend requests Some images were not rendering properly, had to remove some locations Figuring out closing time logic Working with geolocation, directions, and mapping at the same time required careful coordination. Getting consistent location data and displaying it accurately on the map was more complex than expected. We had to decide which elements were essential (Wifi, noise, hours, outlets) and how to structure them so filtering stayed fast and intuitive. During the hackathon, we had to balance features with time limits. Choosing which features to build was a major challenge.

Accomplishments that we're proud of

We're proud that we built a functional platform that helps Bay Area students quickly find study spots using meaningful filters like WiFi strength and noise level. We also integrated real-time reviews, Google Maps directions, and group invitations—creating a tool that’s both practical and community-focused.

What we learned

We learned how the frontend, backend, and database interact, and how to structure data so features remain scalable.We learned how to think like students and translate actual needs into useful filters and UI.Working under pressure taught us the importance of dividing tasks, communicating clearly, and using GitHub to avoid conflicts.

What's next for WorkHere

-Expand from Bay Area to statewide California coverage -Enable private messaging between friends -Launch native mobile and desktop applications -AI agent to suggest users’ personal best study spot