Outfit Buddy is a context-aware web application that functions as your personal AI stylist. It solves decision fatigue by proactively suggesting optimal outfits based on your Outlook Calendar schedule and Local Weather conditions, while promoting sustainable fashion habits.
"I have nothing to wear." Even with a full closet, many people suffer from:
- Decision Fatigue: Wasting time in the morning trying to choose an outfit.
- Context Disconnect: Dressing incorrectly for the weather (e.g., canvas shoes in the rain) or occasion (casual wear to a client meeting).
- Asset Underutilization: Using only ~20% of the wardrobe effectively.
- Sustainability Gap: High-quality clothes sit unused instead of being donated.
Outfit Buddy utilizes an AI agent to aggregate your wardrobe inventory with external context. It filters out unsuitable items and ranks the rest based on formality and rotation frequency to suggest the perfect outfit.
"It’s rainy and you have a dinner date → Wear the leather loafers, not the canvas shoes."
Syncs directly with Outlook Calendar and Weather APIs. The app knows if you have a "Weekly Standup" or a "Dinner Date" and checks the forecast (e.g., 13°C & Rainy) to ensure comfort and appropriateness.
- Smart Suggestions: Applies custom filtering algorithms to exclude items unsuitable for the weather.
- Ranking System: Prioritizes items based on formality (0-10 scale) and "Last Worn Date" to maximize wardrobe rotation.
- Scan with AI: Easily add new items. The AI automatically tags attributes like Fabric, Pattern, Category, and rates them on Formal, Warmth, and Relaxed scales.
- Digitized Inventory: View your Tops, Bottoms, Shoes, and Accessories in a clean dashboard.
Promotes circular fashion by tracking item utility. It highlights clothes you haven't worn in a while (e.g., "Beige Trench Coat - Not worn recently") and provides a direct "Find Donation Center" button.
The solution is built on a robust Hybrid Cloud Architecture, leveraging Microsoft Azure and Google Firebase.
| Component | Technology | Description |
|---|---|---|
| Frontend | Next.js | React framework for a fast, server-side rendered (SSR) UI. |
| Hosting | Azure Static Web Apps | Provides global availability, native SSL, and CI/CD via GitHub Actions. |
| Auth | Firebase Authentication | Handles secure user management (Email/Password & Anonymous login). |
| Database | Cloud Firestore (NoSQL) | Stores wardrobe inventory with complex metadata (warmth_rating, formal_rating, etc.). |
| APIs | Weather API & Outlook | External data sources for context awareness. |
- Context: App fetches Weather & Schedule.
- Filter: AI filters wardrobe by Weather (Warmth Rating).
- Refine: AI filters by Schedule (Formal Rating).
- Rank: Items ranked by "Last Worn Date".
- Output: Optimal Outfit Recommendation.
To run this project locally:
-
Clone the repository:
git clone https://github.com/iosifidis/outfit-buddy.git cd outfit-buddy -
Install dependencies:
npm install # or yarn install -
Set up Environment Variables: Create a
.env.localfile and add your Firebase and Azure API keys. -
Run the development server:
npm run dev
-
Open your browser: Navigate to
http://localhost:3000.
- Efstathios Ioasifidis
- Evangelia Tsioumani
- Dimitris Topalidis
- Christos Kopsahilis
- Nalmpanti Effrosyni
Project created: December 7, 2025