Vendex is an AI-powered B2B supply chain optimization platform that connects store owners, consumers, and manufacturers into a unified smart ecosystem.
It enables real-time inventory tracking, demand forecasting, intelligent reorder recommendations, and intent-based product discovery using data-driven AI models.

• Real-time product availability tracking
• Intent-based shopping (natural language input → structured product suggestions)
• Smart product recommendations

• AI-based demand forecasting using historical sales data
• Optimal reorder quantity recommendations
• Real-time inventory auto-update after transactions
• Staff management (roles, responsibilities, tracking)
• Direct manufacturer connectivity
• Automated receipt generation & downloadable invoices

• Power BI dashboard integration
• Sales trend visualization
• Inventory turnover insights
• Demand prediction reports
• Business performance metrics

Frontend (Consumer / Store Owner Interface) ↓ FastAPI Backend (Business Logic + ML Models) ↓ MySQL Database (Inventory & Orders) ↓ Power BI (Analytics Layer)

• FastAPI (Python)
• RESTful APIs
• Uvicorn Server

• Google Gemini API (LLM integration)
• Pandas
• NumPy
• Scikit-learn
• Time-series forecasting techniques

• MySQL
• Relational schema with inventory & orders

• Microsoft Power BI

• Web UI (AI-generated)

Consumer / Store Owner (Frontend) ⬇ FastAPI Backend (Business Logic + ML Models) ⬇ MySQL Database ⬇ Power BI (Analytics Layer)

git clone https://github.com/Shresth-Agarwal/Vendex.git
cd Vendex/python

python -m venv venv

Activate it:

• Windows:

venv\Scripts\activate

• macOS/Linux:

source venv/bin/activate

pip install -r requirements.txt

If requirements.txt is not present, install manually:

pip install fastapi uvicorn pandas numpy mysql-connector-python scikit-learn

This fixes errors like:

ModuleNotFoundError: No module named 'pandas'

uvicorn main:app --reload

Server will start at:

http://127.0.0.1:8000

API Docs:

http://127.0.0.1:8000/docs

## 📂 Project Structure

Vendex/
│
├── frontend/                 # Frontend application (Next.js / React)
│   ├── node_modules/
│   ├── public/
│   ├── src/
│   └── package.json
│
├── python/                   # FastAPI Backend
│   ├── __pycache__/
│   ├── pydantic_classes/     # Request/Response schemas
│   ├── venv/                 # Virtual environment
│   ├── assign.py             # Assignment logic
│   ├── decision.py           # Decision-making logic
│   ├── demand.py             # Demand forecasting (ML)
│   ├── intent.py             # Intent processing (Gemini integration)
│   ├── main.py               # FastAPI entry point
│   ├── receipt.py            # Receipt generation logic
│   ├── recommender.py        # Recommendation engine
│   ├── routers.py            # API route definitions
│   └── requirements.txt
│
├── Spring_Boot/              # (Optional / Legacy backend module)
│
├── .gitignore
├── README.md
└── requirements.txt

• Time-series based demand forecasting
• Intelligent reorder suggestions
• Intent understanding for consumers
• Automated business insights

Vendex aims to modernize small and medium businesses by:

• Reducing stock shortages
• Preventing over-ordering
• Connecting owners directly with manufacturers
• Providing AI-driven business intelligence