MALENIO Project Definition

MALENIO will transform Gmail users' ability to manage and discover email patterns through intelligent, privacy-preserving AI that operates locally using Ollama. By providing smart auto-tagging, pattern recognition, and organizational capabilities, MALENIO will reduce email management time while improving information retrieval and workflow integration.

Project Vision

MALENIO will transform Gmail users’ ability to manage and discover email patterns through intelligent, privacy-preserving AI that operates locally using Ollama. By providing smart auto-tagging, pattern recognition, and organizational capabilities, MALENIO will reduce email management time while improving information retrieval and workflow integration.

Core Problem

Email overload and inefficient categorization lead to:

  • Information buried in overflowing inboxes
  • Inconsistent manual tagging practices
  • Privacy concerns with cloud-based AI email analysis
  • Time wasted on email organization and retrieval
  • Difficulty identifying important patterns in communication

MALENIO addresses these challenges by providing intelligent, local-AI powered organization that learns from user behavior while preserving privacy.

Project Goals

  1. Primary Goal: Create a Chrome extension that enhances Gmail management through AI-powered auto-tagging and pattern recognition using local Ollama models.

  2. Secondary Goals:

    • Improve email discovery and retrieval speed by 50%+
    • Reduce manual tagging and organization time by 75%
    • Maintain complete privacy by processing all data locally
    • Enable users to discover valuable insights and patterns in their emails
    • Provide a seamless, intuitive extension of Gmail’s native interface

Project Scope

In Scope

  • Chrome extension development for Gmail
  • Local AI integration with Ollama
  • Email analysis and auto-tagging capabilities
  • Pattern recognition and insight generation
  • User-controlled tagging system with AI suggestions
  • Gmail UI integration and enhancement
  • Local data storage and processing

Out of Scope (Initial Release)

  • Support for email clients other than Gmail
  • Browsers other than Chrome/Chromium
  • Mobile application
  • Cloud-based processing options
  • Email content generation or automatic replies
  • Calendar or task integration
  • Offline capability when Ollama isn’t running

Target Users

Primary Users

  • Knowledge Workers: Professionals managing high email volumes who need better organization
  • Privacy-Conscious Individuals: Users concerned about AI services analyzing their emails
  • Gmail Power Users: People who heavily use Gmail and want enhanced functionality
  • AI Enthusiasts: Users interested in applying local AI models to productivity tools

User Needs

  1. Efficiently categorize and retrieve emails
  2. Discover patterns and insights in communication
  3. Maintain privacy while leveraging AI capabilities
  4. Reduce time spent on manual email organization
  5. Access a solution that works within their existing Gmail workflow

Key Features and Capabilities

  1. Intelligent Auto-Tagging
    • AI-suggested tags based on email content and context
    • Learning from user tagging behavior
    • Consistent taxonomy enforcement
  2. Pattern Recognition
    • Identification of communication patterns
    • Highlighting of important trends
    • Visualization of email analytics
  3. Local AI Processing
    • Integration with Ollama for local model inference
    • No email content sent to external services
    • Model selection based on user hardware capabilities
  4. Seamless Gmail Integration
    • Native-feeling UI extensions
    • Keyboard shortcuts and workflow enhancements
    • Gmail search integration with tags
  5. User Control and Transparency
    • Explanations for AI suggestions
    • Override capabilities for all automated actions
    • Progressive learning from user corrections

Success Metrics

Quantitative Metrics

  1. User adoption and retention rates
  2. Time saved in email management (user-reported)
  3. Tag utilization and consistency
  4. Search time reduction
  5. Feature engagement rates

Qualitative Metrics

  1. User satisfaction with auto-tagging accuracy
  2. Perceived value of pattern recognition
  3. Comfort with privacy aspects
  4. Integration quality with existing workflow
  5. Net Promoter Score (NPS)

Constraints and Assumptions

Constraints

  1. Local AI performance limited by user hardware
  2. Chrome extension capabilities and security model
  3. Gmail API limitations and changes
  4. Ollama model availability and performance

Assumptions

  1. Users will have Ollama installed and configured
  2. Target users primarily manage email through Gmail web interface
  3. Users are willing to grant necessary permissions to the extension
  4. Local processing will be sufficiently fast on average hardware
  5. Gmail’s interface will remain relatively stable

Project Timeline (Preliminary)

  • Research & Definition: 4 weeks
  • Design & Prototyping: 6 weeks
  • Development Phase 1 (Core functionality): 8 weeks
  • Alpha Testing: 2 weeks
  • Development Phase 2 (Refinement): 4 weeks
  • Beta Testing: 3 weeks
  • Release Preparation: 2 weeks
  • Initial Release: TBD (approximately 6 months from project start)

Stakeholders

  • Project Owner: [Name]
  • Development Team: [Names]
  • Design Team: [Names]
  • Test Users: To be recruited during alpha and beta phases
  • Advisors: [Names if applicable]

Integration Requirements

  1. Gmail Integration
    • Access to Gmail DOM for UI enhancement
    • Compliance with Gmail’s extension policies
  2. Ollama Integration
    • Local API communication
    • Model management and optimization
  3. Data Storage
    • Local browser storage for user preferences
    • Secure handling of analyzed email data

Initial Risk Assessment

  1. Technical Risks
    • Local AI performance may vary widely across user hardware
    • Gmail interface changes may break extension functionality
    • Ollama limitations or changes could impact capabilities
  2. User Adoption Risks
    • Installation friction (requiring Ollama setup)
    • Learning curve for AI-assisted email management
    • Chrome extension permission concerns
  3. Privacy Risks
    • User misconceptions about data handling
    • Security of local processing
    • Browser extension security model limitations

Next Steps

  1. Complete market and user research
  2. Develop detailed technical specifications
  3. Create initial UI/UX design concepts
  4. Prototype core functionality
  5. Establish development environment and workflow
  6. Begin technical architecture documentation

Note: This project definition is a living document and will evolve as the project progresses through research and development phases.