AI-powered digital advertising campaign management platform that revolutionizes campaign creation and optimization across LinkedIn Ads and Google Ads platforms.
The Sales Intelligence Platform is an enterprise-grade solution that addresses the complex, time-consuming process of creating effective advertising campaigns by automating campaign structure generation, audience targeting, and performance optimization.
- AI-powered campaign structure generation
- Multi-platform campaign management (LinkedIn & Google Ads)
- Real-time performance analytics and optimization
- Secure authentication and authorization
- Comprehensive monitoring and observability
- Campaign creation time reduction: 80%
- Campaign performance improvement: 40%
- Target response time: <100ms
- System availability: 99.9%
C4Context
title System Context Diagram
Person(user, "Platform User", "Digital marketer, advertiser, or agency")
System(sip, "Sales Intelligence Platform", "AI-powered campaign creation and optimization system")
System_Ext(linkedin, "LinkedIn Ads", "Ad campaign platform")
System_Ext(google, "Google Ads", "Ad campaign platform")
System_Ext(crm, "CRM Systems", "HubSpot/Salesforce")
System_Ext(analytics, "Analytics Platforms", "Campaign performance data")
Rel(user, sip, "Creates and manages campaigns")
Rel(sip, linkedin, "Manages ad campaigns")
Rel(sip, google, "Manages ad campaigns")
Rel(sip, crm, "Syncs customer data")
Rel(sip, analytics, "Tracks performance")
- Frontend: Next.js 14.0.0, React 18.2.0, TypeScript 5.0.0
- Backend: Node.js 18 LTS, Python 3.11+
- Database: PostgreSQL 15+
- Cache: Redis 7.0+
- Infrastructure: AWS EKS, Terraform
- Monitoring: Prometheus, Grafana, ELK Stack
- Node.js >= 18.0.0
- Docker >= 24.0.0
- AWS CLI v2.0+
- kubectl v1.27+
- Terraform v1.5.0+
- Clone the repository:
git clone <repository_url>
cd sales-intelligence-platform- Install dependencies:
# Backend services
cd src/backend
npm install
# Frontend application
cd src/web
npm install- Configure environment variables:
# Backend services
cp .env.example .env
# Frontend application
cp .env.local.example .env.local- Start development environment:
# Start backend services
docker-compose up -d
# Start frontend application
cd src/web
npm run dev├── src/
│ ├── backend/ # Backend microservices
│ │ ├── api-gateway/ # API Gateway service
│ │ ├── auth-service/ # Authentication service
│ │ ├── ai-service/ # AI/ML service
│ │ └── shared/ # Shared utilities and types
│ └── web/ # Frontend application
├── infrastructure/ # Infrastructure as Code
│ ├── terraform/ # Terraform configurations
│ └── docker/ # Docker configurations
└── docs/ # Documentation
# Development
npm run dev # Start development server
npm run build # Build production bundle
npm run test # Run tests
npm run lint # Run linting
# Infrastructure
terraform init # Initialize Terraform
terraform plan # Preview infrastructure changes
terraform apply # Apply infrastructure changes- Build application:
npm run build- Deploy infrastructure:
cd infrastructure/terraform/aws
terraform init
terraform apply- Deploy application:
kubectl apply -f k8s/Required environment variables:
NODE_ENV: Environment (development/staging/production)AWS_REGION: AWS region for deploymentDB_HOST: PostgreSQL database hostREDIS_HOST: Redis cache hostAPI_KEY: Platform API key
- JWT-based authentication with refresh tokens
- Role-based access control (RBAC)
- API rate limiting
- Data encryption at rest and in transit
- Regular security audits
- GDPR compliance
- SOC 2 compliance
- Platform-specific policy compliance
- Regular security assessments
- Prometheus for metrics collection
- Grafana for visualization
- ELK Stack for log aggregation
- Jaeger for distributed tracing
/healthendpoint for each service- Kubernetes liveness/readiness probes
- Automated alerting
- Performance monitoring
- Fork the repository
- Create a feature branch
- Submit a pull request
Proprietary - All rights reserved