Sales & Intelligence Platform

An enterprise-grade AI-powered platform for automating and optimizing B2B digital advertising campaigns across LinkedIn Ads and Google Ads platforms.

Features

• 🤖 AI-automated campaign structure generation
• 🎯 Intelligent audience targeting and segmentation
• 📊 Real-time performance analytics and optimization
• 🔒 Enterprise-grade security and compliance
• ⚡ High-performance microservices architecture

System Architecture

graph TD
    A[Web Application] --> B[API Gateway]
    B --> C[Campaign Service]
    B --> D[AI Service]
    B --> E[Analytics Service]
    B --> F[Audience Service]
    
    C --> G[(PostgreSQL)]
    D --> H[ML Models]
    E --> I[(MongoDB)]
    F --> J[Redis Cache]

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Prerequisites

• Node.js >= 18.17.0
• Python >= 3.11.0
• Docker >= 24.0.0
• Docker Compose >= 2.20.0
• NVIDIA Container Toolkit (for GPU support)
• AWS/GCP/Azure credentials
• LinkedIn and Google Ads API access

Quick Start

1. Clone the repository:

git clone <repository-url>
cd sales-intelligence-platform

2. Configure environment variables:

cp .env.example .env
# Edit .env with your configuration

3. Start services with Docker:

docker-compose up -d

4. Access the application:

• Frontend: http://localhost:3000
• API Documentation: http://localhost:8000/docs
• Monitoring: http://localhost:3000/monitoring

Development

Project Structure

sales-intelligence-platform/
├── src/
│   ├── web/                 # Next.js frontend
│   ├── backend/            # Python microservices
│   ├── common/             # Shared utilities
│   └── test/              # Test suites
├── docs/                  # Documentation
├── monitoring/           # Monitoring configuration
└── deployment/          # Deployment manifests

Available Scripts

# Frontend Development
cd src/web
npm install
npm run dev

# Backend Development
cd src/backend
python -m venv venv
source venv/bin/activate  # or `venv\Scripts\activate` on Windows
pip install -r requirements.txt
python -m uvicorn main:app --reload

# Testing
npm run test              # Run all tests
npm run test:unit        # Run unit tests
npm run test:integration # Run integration tests
npm run test:e2e        # Run end-to-end tests
npm run test:security   # Run security tests

Security Features

• OAuth 2.0 / OpenID Connect authentication
• Role-based access control (RBAC)
• AES-256-GCM encryption (FIPS 140-2 compliant)
• API security with rate limiting
• GDPR and CCPA compliance
• Regular security audits and penetration testing

Deployment

Production Setup

1. Build production images:

docker-compose -f docker-compose.prod.yml build

2. Deploy with high availability:

docker-compose -f docker-compose.prod.yml up -d

Cloud Infrastructure

• Kubernetes orchestration
• Multi-AZ deployment
• Auto-scaling configuration
• Load balancing
• CDN integration
• Disaster recovery

Monitoring & Observability

• Prometheus metrics
• Grafana dashboards
• Jaeger distributed tracing
• ELK Stack logging
• Real-time alerts

Access monitoring:

• Grafana: http://localhost:3000
• Prometheus: http://localhost:9090
• Jaeger: http://localhost:16686

Performance Optimization

• Server-side rendering (SSR)
• Redis caching
• Database connection pooling
• Message queue batching
• GPU acceleration for AI services
• CDN for static assets

Documentation

• API Documentation
• Frontend Documentation
• Backend Documentation
• Security Guidelines
• Deployment Guide

Contributing

1. Create a feature branch
2. Make your changes
3. Run tests and security checks
4. Submit a pull request

Support

For support and issues:

1. Check documentation
2. Contact development team
3. Create GitHub issue

License

Proprietary - All rights reserved

Copyright © 2024 Sales Intelligence Platform Team