Auto Notes System

Pioneered AI-powered auto note generation from video content at Slid

Description:

Pioneered the development of AI-powered auto note generation from video content at Slid, starting as a side project before the AI boom. Built an end-to-end system that transforms video content into structured, actionable notes using advanced AI processing, achieving significant cost optimization and establishing new revenue streams.

Project Duration:

2024 (Principal AI Engineer at Slid)

Key Technical Achievements:

  • AI Innovation Pioneer: Started developing AI note generation before ChatGPT era, positioning Slid as an early innovator
  • End-to-End System Architecture: Built complete pipeline from video input to structured note output
  • Smart Markdown Conversion: Developed intelligent markdown to rich-text editor conversion maintaining formatting fidelity
  • Cost Optimization: Achieved 60% API cost reduction through intelligent buffering and provider optimization
  • Real-time Processing: Implemented streaming architecture for progressive note generation during video playback
  • Multi-provider Integration: Seamlessly integrated OpenAI GPT-4, Anthropic Claude, and Google Gemini for optimal performance

Technical Implementation:

  • AI/ML Stack: OpenAI GPT-4, Anthropic Claude, Google Cloud Speech, LangChain
  • Backend: Python FastAPI, WebSocket for real-time communication, Redis for caching
  • Frontend Integration: React 18, Redux for state management, Custom editor plugins
  • Processing Pipeline: Audio extraction → Transcription → AI summarization → Format conversion
  • Optimization: Request batching, Token usage optimization, Provider fallback mechanisms

Business Impact:

  • Revenue Growth: Transformed premium feature adoption, establishing new AI-powered revenue streams
  • User Engagement: Significant increase in user retention and premium subscriptions
  • Market Positioning: Established Slid as AI-first educational technology leader
  • Cost Efficiency: 60% reduction in API costs while improving output quality

Technical Innovations:

  • Intelligent Buffering: Custom algorithm to optimize API calls without sacrificing real-time feel
  • Format Preservation: Advanced AST manipulation for markdown to rich-text conversion
  • Context Management: Sliding window approach for maintaining context in long videos
  • Quality Assurance: Multi-stage validation pipeline ensuring high-quality note output

Skills Demonstrated:

AI/ML Engineering, System Architecture, Cost Optimization, Real-time Processing, API Integration, Product Innovation, Full-stack Development