Far future goals

[ERLindeman]

Scattered points of future research for future features

• Model type

• Data pre-tokenization for model training

• Monetization

• Local health data

• Mobile app integration

  • ios
  • android

• Same-device web to app data sync

• Implement API integrations (for realtime data retrieval, not storage; in rough order of market share)

  • Apple Healthkit
  • Google Fit API
  • Fitbit API
  • Garmin health api
  • Oura ring API

• Local Data Sync

• Implement API data sync (for storage and restore)

  • Apple health sync
  • Fitbit Sync

• Local Data Storage

• interaction analytics

  • Time spent on item, navigation patterns, etc.
  • User feedback, surveys interface
  • pipe all relevant feedback data into context of Enterprise llm for development feedback loop

• Determine implications of the addition of mental health to model

  • Implement personalized mental health analytics on top of existing medical framework

• determine best way to integrate risk factor tracking into model

• Decentralize servers (web, training; over ICP?)

• Determine average and distribution of lifetimes of wellness saas subscriptions to calculate marginal cost of user acquisition target

• determine telemedicine integrations

  • how to correctly correlate and manage symptom changes and treatment recommendations across multiple providers

• Decorative design beneath widget columns

• referral program implementation details

• paid plan feature segregation

• paid plan platforms

• gifted subscriptions

• add other third-party device tie-in widgets

• Brainstorm, design, and implement app soundscape

  • Composed of entirely E notes and E major chords (and informed design a la google)
  • Played with pure sine synth (no intra-note harmonics)
  • Sonic design should be portable from ux design through to video background music

• Implement 2FA Requirement

• add "Wait for Wifi" setting

• Add on-device LLM integration to better understand patient needs and filter possible treatments and presentation accordingly

  • Integrate (possibly second, separate) LLM to aid patients in selection of telehealth providers to their comfort

• Maintain scroll position when switching from landscape to portrait and vice-versa

• implement graphRAG on local medical data to help patients understand correlations between health factors through llm interstitial patient advocate between Time series transformer and telehealth provider or outputted PDF for established in-person care provider

• Determine if and how to take on capital

  • Small business development center grants
  • In-kind services for startups
  • try to remain self-funded

• Determine how to hybrid source repo

  • proprietary: (for now)
    • ML source code
    • premium features source code
    • executables
  • MPL-2: all else

Check only when integrated into standalone issue