📦 An AI-powered inventory intelligence dashboard for retail chains like Walmart to track, analyze, and optimize clearance strategies by monitoring expiry, urgency, and stock health.

⏯️ Click to watch a live walkthrough of the platform. Delpoyed: http://inventory.darexai.com/

📂 All screenshots are located in the public/screenshots/ folder.

Large-scale retailers often struggle to manage perishable inventory, leading to:

• 🗑️ Product wastage
• 💸 Revenue loss
• 🤯 Missed clearance opportunities

Manual methods are inefficient and error-prone, especially at scale.

Walmart Clearance Optimizer solves this by offering:

• 🎯 Real-time product tracking based on expiry & stock
• 📊 Visual dashboards for urgency & category analysis
• 🔐 Role-based access (Admin, Manager, Staff)
• 📥 CSV downloads and advanced filters
• 💡 Smart recommendations (coming soon!)

• ✅ Add / edit / delete product entries
• 🕒 Expiry & manufacture date tracking
• 🧯 Detects:
  • Expired items
  • Expiring soon
  • Low-stock alerts
• 📊 Dashboard with:
  • Total inventory value
  • Category-wise breakdown
  • Expiry insights
• 🔐 Login with 3 roles (RBAC)
• 📎 Export product list to CSV

walmart-clearance-optimizer/
├── backend/
│ ├── models/
│ ├── routes/
│ ├── app.py
│ └── .env
├── frontend/
│ ├── src/
│ │ ├── components/
│ │ └── App.jsx
│ └── public/
│ └── screenshots/
├── README.md
└── .gitignore

Create a .env file in the model/ directory:

MONGO_URI=mongodb+srv://<username>:<password>@cluster.mongodb.net/walmartDB
JWT_SECRET=your_jwt_secret_key
🛠️ How to Run Locally
▶️ Backend (Flask API)
bash
Copy
Edit
cd backend
pip install -r requirements.txt
python app.py
💻 Frontend (React + Tailwind)

cd frontend
npm install
npm run dev

🧠 Future Scope 🤖 AI-based markdown recommendation

📧 Email alerts for urgent stock

🛒 Customer-side product suggestions

📈 ML-powered sales forecasting

📃 License This project is licensed under the MIT License.

🙏 Acknowledgements Special thanks to Walmart and the hackathon organizers for providing this opportunity. Our solution contributes toward reducing retail waste and maximizing clearance efficiency.

💡 Made with ❤️ by Lincy & Addy (Aditya Kumar)

Would you like:

• A live demo badge to show status?
• Add a Deploy to PythonAnywhere or Render button?
• A README.gif walkthrough animation instead of screenshots?

Let me know and I’ll help instantly!