dress.

Logo

Inspiration

As young people entering our 20s, there's lots of milestones such as graduations, birthdays, weddings and many more events. A common problem that we run into each one is the question, 'What do I wear?' that is both affordable and personalised to who we are. This is where the idea of 'dress.' came in, we hope to transform the clothing rental market to give our users the best choices to be the best dressed.

What it does

'dress.' addresses the clothing rental market's gap in personalisation to users' unique styles. By feeding in inspiration into 'dress.' via a Pinterest moodboard or images of desired styles, 'dress.' will present users with tailored choices based on AI intent prediction of rental clothing choices. Conducting market research, we found that personalisation was missing from the competition landscape. This makes it easier for the user to select the perfect clothing item for the occasion unique to them. On our lending side, 'dress.' will help lenders suggest the best times to lend specific items of clothing on popular occasions. By doing so, our lenders can feel confident in renting out their clothing in the current market.

How we built it

Our current technology stack looks like: Front End

Using Expo & React Native to build a cross-platform mobile app using Expo framework for iOS/Android development
TypeScript as the primary programming language for type safety and better development experience Navigation & Routing:
Expo Router as a file-based routing system (evident from the _layout.tsx and folder structure in app/)

Backend Services: Firebase as authentication and database using Firebase Auth and Firestore (configured in config/firebase.js) Google Cloud Vision API for image analysis and embedding generation (implemented in services/visionEmbeddingService.ts)

Development Tools: Babel - JavaScript transpilation with Expo preset and React Native Reanimated plugin (babel.config.js) ESLint - Code linting and formatting TypeScript - Type checking and compilation

Challenges we ran into

Understanding Start Up Culture Being from technology heavy backgrounds as computer science students, we were new to the startup environment. Through all the FoundersHack workshops, we were able to validate a problem and research on how to approach building a start up. With the guidance of the rubric, and putting our heads together, we are proud of what we learnt about Australia's start-up culture. Pinterest API access Our concept idea with feeding in data from the user's social media accounts like Pinterest was challenged as we have to apply for access to Pinterest API data and that would've been processed after the hackathon. However, we were able to use sample Pinterest data from one user to emulate what it would as a core concept

Complexities in vision AI Our team was new to vision AI's intricacies. In particular, we had to direct the AI to look for what we needed explicitly and prompt for clothing choices only. However, after much trial and error, with prompting and zeroing down how exactly the vision AI gets to its conclusion, we are excited to say that we have learnt how to navigate vision AI.

Accomplishments that we're proud of & what we learnt

On our way to being Founders We are proud with building basics of a start-up that we can launch into the market. In particular, finding and validating a market problem. We're proud of coming far in our learning and understanding how start-ups are built step by step. We look forward to employing these skills to engage with Australia's start-up culture even more Technology Stack Being unfamiliar with some of the tools used in our tech stack, we are proud of having seaminglessly integrated everything together to work from point A to point B. By mapping out everything, we could see everything in full scope and understood how each part of our app helped each other.

What's next for dress.

Further an development for our app functionalities such as the Wishlist, and to tailor our clothing choices even more. We hope to conduct market research more extensively over different age groups and other demographics. We ultimately hope to pilot and launch our product to the wider market after thorough feedback and even further improved functionalitiy