Weave

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Inspiration

Getting dressed should be easy, but often it’s anything but. Whether you're rushing out the door, feeling unmotivated, or physically unable to change multiple outfits, trying on clothes is a hassle. Our team saw an opportunity to create a seamless, AI-powered solution that makes outfit planning effortless—especially for those who find physical try-ons inconvenient. Weave was inspired by two key challenges:

👥 Accessibility & Physical Limitations – People recovering from injuries, individuals with mobility challenges, or those who simply find changing clothes tedious shouldn’t have to struggle with outfit decisions. We wanted to build a tool that lets users visualize their wardrobe on their own body—without needing to physically try anything on.

⏳ Convenience & Decision Fatigue – Choosing an outfit takes time, and many of us default to wearing the same things over and over. Weave eliminates the guesswork by allowing users to upload their actual wardrobe, try on outfits digitally, and preview how they’ll look in real life. Beyond solving these pain points, we wanted to make fashion more interactive and social. Instead of texting friends “Does this look good?”, Weave will soon allow users to share outfit ideas, get fit recommendations, and even ‘try on’ clothes from online stores before purchasing. At its core, Weave is about making fashion effortless, accessible, and fun. Whether you're recovering from an injury, planning an outfit ahead of time, or just avoiding the hassle of changing—Weave helps you dress smarter, faster, and with more confidence. 🚀

What It Does

Weave takes the hassle out of outfit planning by letting you see how your clothes look on you—without ever trying them on. Whether you're in a hurry, feeling lazy, or unable to change outfits, our AI-powered virtual dressing room makes styling effortless. Unlike other styling apps that simply suggest outfits, Weave allows you to upload your actual clothes and try them on virtually using a mannequin—or even on your own image. Key Features: 👕 Upload & Virtual Try-On – Upload photos of your wardrobe and create a digital closet.

🛍 Smart Shopping Integration – Browse clothes from your favorite brands and see how they pair with your existing outfits before you buy.

🖱 Drag & Drop Styling – Mix and match clothing on a custom mannequin to visualize different looks.

📸 AI Fit Preview – Upload a photo of yourself and see an accurate, AI-generated preview of how an outfit will look on you.

📂 Save & Share – Store outfits in your Lookbook, track past outfits, and share looks with friends for instant feedback.

From daily outfit planning to social fashion recommendations, Weave is redefining how people interact with their wardrobe—without the hassle of physically trying things on.

How We Built It

Our team set out to build Weave as a fast, intuitive, and AI-powered styling tool that seamlessly integrates personal wardrobes with outfit visualization. From the beginning, we prioritized realism, usability, and efficiency, ensuring that users could easily upload their clothes, try on outfits virtually, and share looks with friends—all within a clean and responsive interface. The name Weave reflects our vision: bringing together different elements—technology, fashion, and personalization—into one seamless experience. Just like threads in fabric, Weave interconnects clothing, AI, and user preferences to create a tool that makes outfit planning effortless and engaging. Tech Stack & Architecture

🔹 Frontend: Built with Next.js, leveraging React components for a modular and responsive UI. Styled with Tailwind CSS and ShadCN for a sleek and intuitive design.

🔹 Backend: Developed in Go (Golang) for a lightweight yet powerful server-side architecture, ensuring fast processing and low latency.

🔹 AI Integration: Weave utilizes the FashnAI API, integrated via Go endpoints, to generate outfit previews. By optimizing calls to the API, we ensure that users get realistic clothing visualizations while maintaining high image quality.

🔹 Image Processing & Storage: Amazon S3: Secure and scalable cloud storage for user-uploaded clothing images. AWS Lambda + Neural Networks: Preprocesses images to remove backgrounds and cleanly integrate clothing items into Weave’s digital wardrobe.

🔹 Deployment & Infrastructure: Coolify: Self-hosted deployment with a GitHub integration for CI/CD Docker: Ensures consistency across development environments, so every team member can work efficiently without worrying about dependencies.

Key Innovations in Our Stack One of our biggest technical breakthroughs was optimizing how Weave processes outfit layering. The FashnAI API processes only one clothing item per call, meaning that generating a complete outfit was a challenge. To solve this, we engineered an iterative layering system, where the output of one API call is fed into the next, stacking multiple clothing pieces while preserving realism and fit. Additionally, our AWS Lambda-powered image pre-processing pipeline allows users to upload photos with automatic background removal, ensuring that garments are cleanly integrated into the mannequin and AI-generated previews. This not only improves accuracy but also speeds up rendering times for a smoother user experience.

Challenges We Ran Into

Building Weave was no small feat. Our team faced several technical and logistical hurdles, which pushed us to think creatively and problem-solve under pressure.

🔹 AI Integration Complexity We needed to generate a fully dressed virtual preview, but the FashnAI API only processes one clothing item at a time. Our first approach—combining multiple clothing items into a single composite image—led to poor alignment and resolution issues. To fix this, we developed a sequential layering approach, where items are processed individually and then overlaid dynamically onto the user’s image. This allowed us to preserve quality while generating realistic multi-item outfits.

🔹 Time Constraints & Feature Prioritization Building a fully functional AI-powered outfit visualization tool within a hackathon timeframe was ambitious. Our team had to carefully prioritize features, optimize workflows, and quickly debug issues to ensure a polished final product. Through agile task delegation and continuous iteration, we successfully built a working prototype with key functionalities without sacrificing performance or usability.

🔹 Creating a Dynamic & Interactive Mannequin Designing a mannequin that allowed users to drag and drop clothing items while maintaining accurate proportions and styling was a unique challenge. We experimented with different Next.js state management techniques before finding an optimal solution that balanced interactivity, performance, and visual appeal.

🔹 Seamless Cross-Device Experience Since Weave is an application meant to be used on mobile and desktop, we focused on ensuring a consistent experience across different screen sizes. Implementing responsive UI components with Tailwind CSS helped us maintain a smooth user experience regardless of the device being used.

Accomplishments That We’re Proud Of

🎉 It Works—And It Works Well! Weave isn't just an idea; it's a fully functional product. Our AI successfully processes wardrobe images, applies them to a digital mannequin, and generates realistic outfit previews with minimal latency. Seeing our concept come to life in a working application is something we’re truly proud of.

🧠 Optimizing AI for Real Use Cases We didn’t just integrate AI for the sake of it—we designed a practical, user-friendly AI implementation that directly enhances convenience, accessibility, and styling efficiency. Our layered approach to outfit rendering solves real challenges in AI-powered fashion visualization.

🎨 A Thoughtfully Designed User Experience We put significant effort into making Weave intuitive, clean, and engaging. From the drag-and-drop outfit styling to the seamless AI-generated previews, every aspect of the UI was built with ease of use in mind.

🚀 A Tool We’d Actually Use We set out to create something that would genuinely improve the way we get dressed—and Weave delivers. Whether it’s for daily outfit planning, getting a second opinion from friends, or making smarter shopping decisions, Weave is a tool that we’d all love to have in our daily lives.

🤝 Teamwork & Growth Building Weave pushed us to learn new technologies, refine our problem-solving skills, and work efficiently under time constraints. From backend API optimization to UI/UX refinements, each team member played a vital role in shaping Weave into what it is today.

What We Learned

🚀 Passion Drives Innovation What kept us pushing through sleepless nights, last-minute bug fixes, and endless iterations was our shared frustration with a real problem. Standing in front of a full wardrobe yet feeling like we have nothing to wear is a universal struggle, and Weave was built to solve exactly that. We learned that when you're truly invested in solving a problem, the work never feels like a burden—it becomes something exciting to bring to life. Our passion made sure Weave wasn’t just a project, but a tool we’d genuinely use ourselves.

🤝 Teamwork Makes the Dream Work We quickly realized that no one builds a great product alone. From the start, we focused on playing to our strengths while staying adaptable. Whether it meant learning a new skill on the fly, troubleshooting technical issues, or refining UI design at the last minute, we worked as a team to ensure everyone’s contributions aligned with our shared vision. More than just technical skills, we learned that the key to great teamwork is trust, flexibility, and a shared commitment to execution.

⏳ Time Is Never on Your Side No matter how strong an idea is, execution is everything. We had to move fast, prioritize ruthlessly, and accept that not everything would be perfect. Instead of overanalyzing, we focused on the core experience, identified must-have features, and streamlined our development process. The hackathon format forced us to be decisive, make quick calls, and adapt under pressure. And yes, we also learned that missing an alarm can mean the difference between a smooth morning and a full-speed sprint to the finish line.

In the end, Weave taught us more than just technical problem-solving. It reinforced the power of passion, collaboration, and smart decision-making. No matter what we build next, these lessons will stay with us. 🚀

What’s Next for Weave?

While Weave is already a powerful tool for AI-driven outfit visualization, we see huge potential for future growth. Here’s what’s next:

🔹 Social Integration – We’re working on a feature that will let users share their outfits with friends, receive fit recommendations, and vote on outfit choices.

🔹 AI-Powered Shopping – Users will soon be able to browse online clothing stores and virtually "try on" items with their existing wardrobe, making smarter purchase decisions before buying.

🔹 Advanced Styling Recommendations – We plan to enhance Weave’s AI with style analysis, color coordination advice, and seasonal outfit suggestions, ensuring users always look their best.

🔹 Sustainability Insights – To promote sustainable fashion, Weave will introduce a wear-tracking system to help users maximize their wardrobe, reduce fast fashion waste, and make conscious shopping choices.

Built With

• amazon-web-services
• cloudformation
• coolify
• docker
• github
• go
• lambda
• nextjs
• s3
• tailwind