AutoSEO Engine
An autonomous, open-source AI system that operates as a complete SEO & growth department for businesses.
π Overview
AutoSEO Engine is a multi-agent AI system that performs full-stack SEO with minimal human intervention. The system consists of specialized agents that work together to deliver end-to-end SEO services, from keyword research to link building to conversion optimization.
Key Features
- Multi-Agent Architecture: 10 specialized agents working in coordination
- Full-Stack SEO: Technical, content, link building, and conversion optimization
- Autonomous Operation: Minimal human intervention required
- Revenue Focused: Direct monetization logic tied to SEO outcomes
- Self-Improving: Continuous learning and optimization
- Open Source: Community-driven development with commercial options
ποΈ Architecture
The system uses a multi-agent architecture where each agent is small, specialized, and replaceable:
- CEO Agent: Strategy and business decisions
- SEO Director Agent: Pipeline management
- Technical SEO Agent: Website audits and fixes
- Content & Semantic SEO Agent: Content creation and optimization
- Programmatic SEO Agent: Long-tail content generation
- Link Authority & Outreach Agent: Backlink acquisition
- Conversion & CRO Agent: Landing page optimization
- Client Management Agent: Customer relations
- Automation & Ops Agent: System operations
- Self-Improvement Agent: Continuous learning
π° Monetization Model
The system supports multiple revenue streams:
Tiered Subscriptions:
- Starter: $299/month (basic SEO + 10 content pieces)
- Professional: $799/month (full SEO + 30 content pieces + link building)
- Enterprise: $1,499/month (advanced SEO + 100 content pieces + white-label)
Performance Bonuses: 10% of traffic-to-revenue increase
White-Label Licensing: $4,999/year for agencies
Niche Authority Sites: System-built sites sold for $10K-$50K
Affiliate Revenue: From recommended tools and services
π οΈ Installation
Prerequisites
- Python 3.9+
- pip package manager
Quick Setup
# Clone the repository
git clone https://huggingface.co/[YOUR_USERNAME]/autoseo-engine.git
cd autoseo-engine
# Make deployment script executable and run it
chmod +x deploy.sh
./deploy.sh
Manual Setup
# Install dependencies
pip install -r requirements.txt
# Set up environment
cp .env.example .env
# Edit .env with your settings
# Run the system
python main.py
Docker Setup
# Build the Docker image
docker build -t autoseo-engine .
# Run the container
docker run -d -p 8000:8000 autoseo-engine
π API Usage
The system includes a REST API for monitoring and control:
# Get system statistics
curl http://localhost:8000/stats
# Get revenue dashboard
curl http://localhost:8000/revenue/dashboard
# Create a new customer
curl -X POST http://localhost:8000/customers \
-H "Content-Type: application/json" \
-d '{"name": "New Customer", "tier": "professional"}'
π€ Contributing
We welcome contributions! Please see our contributing guidelines for more information.
Development Setup
# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install development dependencies
pip install -r requirements-dev.txt
# Run tests
python -m pytest
π License
This project is licensed under the MIT License - see the LICENSE file for details.
π Roadmap
Short Term (3 months)
- Enhanced reporting and analytics
- Improved content quality algorithms
- Better integration with popular CMS platforms
Medium Term (6 months)
- Multilingual content generation
- Advanced competitor tracking
- Voice search optimization
Long Term (12 months)
- Video content generation
- Advanced predictive analytics
- Marketplace for custom SEO modules
π― Why AutoSEO Engine?
- Cost Effective: 1/10th the cost of traditional SEO agencies
- Scalable: Same system manages 10 or 10,000 clients
- Autonomous: 24/7 operation without human intervention
- Transparent: Clear metrics and reporting
- Continuous Improvement: Gets smarter with each customer
π Competitive Advantages
- Data Network Effects: More customers = better optimization data
- Workflow Optimization: Years of refined automation processes
- Cost Leadership: Local deployment = lower costs than cloud competitors
- Community: Open-source community contributing improvements
Made with β€οΈ by the AutoSEO Team
For support, please open an issue in the repository or contact us at support@autoseo.engine