A complete AI-powered client acquisition and engagement system built for ZehraSec, a cybersecurity company. This system includes lead generation, client engagement (chatbot), product recommendation, CRM, analytics dashboard, and email automation.

• AI-Powered Chatbot: Intelligent conversation handling with OpenAI integration
• Lead Generation: Automated lead capture and scoring system
• CRM Integration: Complete customer relationship management
• Email Automation: Automated email campaigns and nurture sequences
• Analytics Dashboard: Real-time insights and performance metrics
• Product Recommendations: AI-driven product suggestions
• Appointment Scheduling: Integrated booking system
• Real-time Chat: WebSocket-based live communication

• Flask Backend: RESTful API with comprehensive endpoints
• SQLite Database: Local storage with ORM-like data models
• WebSocket Support: Real-time communication with Socket.IO
• Modern UI: Bootstrap-based responsive design
• Admin Dashboard: Complete management interface
• Export Functionality: CSV/PDF export capabilities
• Search & Filtering: Advanced search and filtering options

• Python 3.8+
• Flask 2.3.3 - Web framework
• SQLite - Database
• OpenAI API - AI integration
• Socket.IO - Real-time communication
• Pandas - Data processing
• Scikit-learn - Machine learning

• HTML5/CSS3/JavaScript
• Bootstrap 5.1.3 - UI framework
• Chart.js - Data visualization
• Font Awesome - Icons
• Socket.IO Client - Real-time communication

• Flask-SQLAlchemy
• Flask-CORS
• Flask-SocketIO
• OpenAI
• Requests
• Schedule
• APScheduler
• And more (see requirements.txt)

zeo/
├── app.py                 # Main Flask application
├── config.py              # Configuration settings
├── models.py              # Database models and ORM
├── requirements.txt       # Python dependencies
├── routes/
│   ├── api_routes.py      # REST API endpoints
│   ├── chat_routes.py     # Chat functionality
│   └── dashboard_routes.py # Admin dashboard
├── services/
│   ├── ai_service.py      # AI and OpenAI integration
│   ├── analytics_service.py # Analytics and reporting
│   ├── crm_service.py     # CRM functionality
│   ├── email_service.py   # Email automation
│   └── lead_service.py    # Lead management
├── templates/
│   ├── index.html         # Main website
│   ├── chat.html          # Chat interface
│   └── admin/
│       ├── dashboard.html # Admin dashboard
│       ├── leads.html     # Lead management
│       ├── analytics.html # Analytics page
│       └── campaigns.html # Email campaigns
└── static/
    ├── css/
    │   ├── style.css      # Main website styles
    │   └── admin.css      # Admin dashboard styles
    └── js/
        ├── main.js        # Main website scripts
        └── admin.js       # Admin dashboard scripts

• Python 3.8 or higher
• pip (Python package manager)
• OpenAI API key (optional, for AI features)

git clone <repository-url>
cd zeo

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

pip install -r requirements.txt

Create a .env file in the root directory:

SECRET_KEY=your-secret-key-here
OPENAI_API_KEY=your-openai-api-key
DATABASE_URL=sqlite:///zehrasec.db
EMAIL_HOST=smtp.gmail.com
EMAIL_PORT=587
EMAIL_USER=your-email@gmail.com
EMAIL_PASSWORD=your-email-password

python -c "from models import init_db; init_db()"

python app.py

The application will be available at http://localhost:5000

• Visit http://localhost:5000 for the main website
• Use the chat widget in the bottom-right corner to start conversations
• Fill out contact forms to generate leads

• Visit http://localhost:5000/admin/dashboard for the admin interface
• Manage leads, view analytics, and create email campaigns
• Monitor real-time chat activity and system performance

The system provides comprehensive REST API endpoints:

• GET /api/leads - Get all leads
• POST /api/leads - Create new lead
• PUT /api/leads/<id> - Update lead
• DELETE /api/leads/<id> - Delete lead

• POST /api/chat/start - Start new conversation
• POST /api/chat/message - Send message
• GET /api/chat/history - Get chat history

• GET /api/analytics - Get analytics data
• GET /api/dashboard/stats - Get dashboard statistics

• GET /api/campaigns - Get all campaigns
• POST /api/campaigns - Create new campaign
• PUT /api/campaigns/<id> - Update campaign

• Intent recognition and response generation
• Context-aware conversations
• Product recommendations based on user needs
• Fallback handling for complex queries

• Automatic lead scoring based on multiple factors
• Lead qualification and prioritization
• Engagement tracking and analytics

• Automated welcome sequences
• Nurture campaigns based on lead behavior
• Personalized product recommendations
• A/B testing capabilities

• Real-time performance metrics
• Lead generation trends
• Conversion funnel analysis
• Email campaign performance

• Input validation and sanitization
• SQL injection prevention
• Cross-site scripting (XSS) protection
• CORS configuration
• Rate limiting (configurable)

• Database indexing for faster queries
• Caching for frequently accessed data
• Optimized API responses
• Efficient WebSocket handling
• Static file optimization

python -m pytest tests/

• Unit tests for all services
• Integration tests for API endpoints
• Frontend functionality tests

Currently, the system uses session-based authentication. API keys can be implemented for programmatic access.

All API responses follow this format:

{
  "success": true,
  "data": {...},
  "message": "Success message",
  "timestamp": "2025-01-13T10:30:00Z"
}

Errors are returned with appropriate HTTP status codes:

{
  "success": false,
  "error": "Error message",
  "code": "ERROR_CODE",
  "timestamp": "2025-01-13T10:30:00Z"
}

1. Set up production environment variables
2. Configure production database (PostgreSQL recommended)
3. Set up email service (SendGrid, AWS SES, etc.)
4. Configure web server (Nginx + Gunicorn)
5. Set up SSL certificates
6. Configure monitoring and logging

# Build the image
docker build -t zehrasec-app .

# Run the container
docker run -p 5000:5000 zehrasec-app

• SECRET_KEY: Flask secret key
• OPENAI_API_KEY: OpenAI API key for AI features
• DATABASE_URL: Database connection string
• EMAIL_HOST: SMTP server host
• EMAIL_PORT: SMTP server port
• EMAIL_USER: Email username
• EMAIL_PASSWORD: Email password

Configure in config.py:

• Database settings
• Email settings
• AI service settings
• Product information
• Company information

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Write tests for new functionality
5. Submit a pull request

This project is licensed under the MIT License - see the LICENSE file for details.

• User authentication and role-based access
• Advanced analytics and reporting
• Integration with popular CRM systems
• Mobile app for iOS and Android
• Advanced AI features (sentiment analysis, etc.)
• Multi-language support
• Advanced email templates
• Integration with social media platforms
• Video chat capabilities
• Advanced security features

For support and questions:

• Email: support@zehrasec.com
• Documentation: [Link to documentation]
• Issues: GitHub Issues

• OpenAI for AI capabilities
• Flask community for the excellent framework
• Bootstrap for UI components
• All contributors and testers

ZehraSec AI-Powered Client Acquisition System - Building the future of cybersecurity sales and engagement.