🚀 Mini CRM System

A full-stack Customer Relationship Management system with AI-powered lead scoring and automatic assignment capabilities.

✨ Features

• 📊 Lead Management: Complete CRUD operations for lead management
• 🤖 AI Lead Scoring: Automatic lead scoring (0-100) using Google Gemini AI
• 🎯 Auto-Assignment: Smart lead assignment based on AI scores:
  • High Priority (70-100): → Senior Sales Rep
  • Medium Priority (40-69): → Junior Sales Rep
  • Low Priority (0-39): → Nurture Later
• 📈 Dashboard: Real-time assignment distribution and lead analytics
• 🎨 Modern UI: Clean, responsive interface with Material-UI components

🛠️ Tech Stack

Layer	Technology
Frontend	React 18, Vite, Material-UI (MUI)
Backend	Node.js, Express.js
Database	PostgreSQL with Sequelize ORM
AI Integration	Google Gemini AI (gemini-1.5-flash)
Styling	Material-UI Components & Custom CSS

📁 Project Structure

crm-system/
├── frontend/          # React frontend application
│   ├── src/
│   │   ├── App.jsx    # Main application component
│   │   ├── App.css    # Styling
│   │   └── main.jsx   # Application entry point
│   ├── package.json
│   └── vite.config.js
├── backend/           # Node.js backend API
│   ├── config/
│   │   └── database.js      # Database configuration
│   ├── controllers/
│   │   └── leadController.js # Lead CRUD operations
│   ├── models/
│   │   └── Lead.js          # Lead database model
│   ├── routes/
│   │   └── leadRoutes.js    # API route definitions
│   ├── services/
│   │   ├── aiService.js     # Gemini AI integration
│   │   └── assignmentService.js # Auto-assignment logic
│   ├── .env             # Environment variables (create from .env.example)
│   ├── package.json
│   └── index.js         # Server entry point
├── .env.example       # Environment variables template
└── README.md         # This file

🚀 Quick Start

Prerequisites

• Node.js (v16 or higher)
• PostgreSQL (v12 or higher)
• Google Gemini API Key (Get it here)

1. Clone the Repository

git clone <repository-url>
cd crm-system

2. Database Setup

1. Install PostgreSQL (if not already installed)
2. Create database and user:

-- Connect to PostgreSQL as superuser
sudo -u postgres psql

-- Create database and user
CREATE DATABASE crm_db;
CREATE USER crm_user WITH ENCRYPTED PASSWORD 'crm_pass';
GRANT ALL PRIVILEGES ON DATABASE crm_db TO crm_user;

-- Exit PostgreSQL
\q

3. Backend Setup

# Navigate to backend directory
cd backend

# Install dependencies
npm install

# Create environment file
cp ../.env.example .env

# Edit .env file with your configurations
nano .env

Configure your .env file:

PORT=5003
DB_HOST=localhost
DB_PORT=5432
DB_NAME=crm_db
DB_USER=crm_user
DB_PASS=crm_pass
GEMINI_API_KEY=your_actual_gemini_api_key_here

Start the backend server:

# Development mode (with auto-restart)
npm run dev

# OR Production mode
npm start

The backend will be running at http://localhost:5003

4. Frontend Setup

# Navigate to frontend directory (from project root)
cd frontend

# Install dependencies
npm install

# Start the development server
npm run dev

The frontend will be running at http://localhost:5173

🔧 Environment Variables

Variable	Description	Example
PORT	Backend server port	5003
DB_HOST	PostgreSQL host	localhost
DB_PORT	PostgreSQL port	5432
DB_NAME	Database name	crm_db
DB_USER	Database username	crm_user
DB_PASS	Database password	crm_pass
GEMINI_API_KEY	Google Gemini AI API key	AIzaSy...

📖 API Documentation

Base URL: http://localhost:5003/api/leads

Method	Endpoint	Description
GET	/	Get all leads
GET	/:id	Get lead by ID
POST	/	Create new lead
PUT	/:id	Update lead
DELETE	/:id	Delete lead
POST	/:id/score	AI Score & Auto-assign lead

Example API Usage

Create a Lead:

curl -X POST http://localhost:5003/api/leads \
  -H "Content-Type: application/json" \
  -d '{
    "name": "John Smith",
    "email": "john@example.com",
    "source": "Website",
    "interestLevel": "High",
    "description": "Enterprise client with $100k budget"
  }'

Score & Auto-assign:

curl -X POST http://localhost:5003/api/leads/1/score

🤖 AI Integration Details

Gemini AI Lead Scoring

The system uses Google Gemini AI to analyze leads based on:

• Interest Level: Customer's expressed interest
• Source: Lead acquisition channel
• Description: Detailed lead information
• Budget Indicators: Financial capability signals
• Urgency Factors: Timeline requirements

Auto-Assignment Logic

if (score >= 70) {
  assignedTo = 'Senior Sales Rep';    // High-value leads
} else if (score >= 40) {
  assignedTo = 'Junior Sales Rep';    // Medium-value leads  
} else {
  assignedTo = 'Nurture Later';       // Low-value leads
}

🎨 UI Features

• 📊 Dashboard: Real-time assignment statistics
• 🔍 Lead Details: Comprehensive lead view with AI analysis
• ✏️ Inline Editing: Edit leads directly in the table
• 🎯 Smart Actions: Context-aware action buttons
• 📱 Responsive Design: Works on all device sizes

🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

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🎉 Happy CRM-ing!