AI-Assisted Content Pipeline
Hybrid "Briefs → Articles" system that transforms content creation into a semi-autonomous publishing process with human oversight and quality control.
View Documentation🔍 Topic Discovery
Automatically monitors RSS feeds, Reddit communities, and Google Trends to identify emerging privacy topics and content opportunities.
Learn more →📝 Brief Generation
Clusters similar topics using ML algorithms and creates structured briefs with titles, outlines, keywords, and search gap analysis.
View samples →✅ Quality Control
Human editors review and approve briefs through GitHub Issues before AI expands them into full articles.
See workflow →✍️ Article Generation
Approved briefs are expanded into comprehensive, fact-checked, SEO-optimized articles with proper schema markup.
View demo →🔬 Verification System
RAG-based fact-checking against authoritative sources like EFF, Mozilla, and IETF documentation ensures accuracy.
Technical details →📊 Feedback Loop
Continuous improvement using Cloudflare analytics to identify high-performing content and optimization opportunities.
Explore metrics →System Architecture
The pipeline consists of three main phases that work together to create a sustainable, high-quality content generation system:
Phase 1: Discovery & Clustering
- Monitor RSS feeds and APIs
- Extract and normalize content
- Generate embeddings for similarity
- Cluster related topics using DBSCAN
- Identify content gaps in search results
Phase 2: Brief Creation & Approval
- Generate structured briefs with outlines
- Analyze search intent and keywords
- Create GitHub Issues for human review
- Wait for editorial approval
- Track approval metrics
Phase 3: Article Generation & Publishing
- Expand approved briefs into full articles
- Fact-check against trusted sources
- Optimize for SEO and AI discoverability
- Generate schema markup and metadata
- Create pull requests for review
Key Features
🎯 SEO Optimization
Built-in SEO intelligence:
- Automatic keyword targeting from trend analysis
- Topical clustering for internal link strength
- Schema markup (Article, HowTo, FAQPage)
- Metadata optimization and social tags
- Lighthouse SEO score monitoring (≥90)
🤖 AI-Friendly Content
Optimized for AI scraping:
- Predictable layout structure
- Key takeaways blocks for summarization
- Short paragraphs and bullet lists
- Rich alt text and descriptive filenames
- Citation formatting for AI recognition
📈 Quality Assurance
Multi-layer quality control:
- RAG-based fact-checking system
- Flesch Reading Ease 55-75 target
- Minimum word count thresholds
- Human approval gates
- Automated CI/CD checks
⚡ Performance Monitoring
Data-driven optimization:
- Cloudflare analytics integration
- Page performance metrics tracking
- Content gap identification
- Automated improvement suggestions
- ROI and cost tracking
Sample Generated Content
See examples of what the AI pipeline generates:
📱 Browser Privacy Guide
Complete 2025 guide comparing Chrome, Firefox, Safari, and Edge privacy settings with step-by-step configuration instructions.
Read Article🛡️ VPN Comparison 2025
Comprehensive review of top VPN services including Mullvad, ProtonVPN, and IVPN with detailed privacy analysis and testing results.
Read Article⚙️ Pipeline Demo
See the complete workflow from topic discovery to published article, including sample briefs, fact-checking results, and SEO optimization.
View DemoTechnology Stack
Core Technologies:
• Python 3.11+ with asyncio for pipeline orchestration
• GitHub Actions for CI/CD and automation workflows
• OpenAI/Anthropic APIs or local Ollama for LLM processing
• FAISS/Chroma for vector embeddings and similarity search
• PyYAML for configuration management
• Cloudflare Pages for hosting and analytics
Data Sources:
• RSS feeds (EFF, Mozilla, Proton, etc.)
• Reddit API for community discussions
• Google Trends for search volume data
• GitHub API for issue and PR management
Quality Control:
• RAG knowledge base with authoritative sources
• Lighthouse for SEO and performance scoring
• Custom fact-checking prompts and validation
• Human approval workflows via GitHub Issues
Ready to Explore?
Dive deeper into the system architecture, view sample outputs, or explore the codebase.