Genesis

Good for the planet, great for your closet.

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Inspiration

Despite growing up with the pressures of climate change on our shoulders, many youths opt for trendy "fast fashion" options to save their wallet; forgetting to save the planet. We wanted to find a way to help give a second life to already loved clothes while spotlighting current trends, with an aim to reduce fashion-based pollution and avoid overconsumption.

What it does

Genesis allows users to buy and sell used clothes at a reduced rate, or choose to donate them to women's shelters through our company. For each donation, purchase, and sale, our built-in carbon emissions tracker calculates each user's impact and rewards them with discounts on future purchases.

How we built it

We designed the entire app on Figma and used React Native for the frontend and Django (Python) for the backend. Our app is launched through Expo Go. Our Butterfly logo was designed by a team member on ProCreate. We also shared our repository through GitHub.

Challenges we ran into

Our team members took the time within this competition to learn a whole new platform for coding, in hopes of being able to optimize user experience on the platform. We also had issues trying to create a login page for returning users.

Accomplishments that we're proud of

We are proud of having a mostly finished product and for coming into this competition with a cohesive idea that allowed each of our members to shine with their individual talents and skills.

What we learned

We learned two new platforms (Django & React Native), as well as GitHub Copilot, and were able to successfully navigate and implement it into our project.

What's next for Genesis

We would love to take this app into higher production by refining certain functionality within the backend, as well as find local women's shelters to partner with to ensure that the clothes can go to people in need with no burden to them or the shelters. We would also love to implement an AI feature that can help optimize customers' experience on the app and pair them with suggested clothing based on their personal style.

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