I’ve been using Exist for a while now, and I love the insights it provides. However, I feel there is a huge opportunity to extract more value from the daily notes.

Currently, the analysis is mostly limited to word frequency and manual tags. I’d like to suggest implementing AI-driven semantic analysis (via LLMs or NLP) to process these notes. Here’s how I think it could improve the platform:

• Sentiment Analysis: Beyond the 1-9 mood rating, AI could detect nuances like anxiety, gratitude, or burnout levels based on the text.
• Automatic Contextual Tagging: Instead of users having to remember specific tags, the AI could identify recurring themes (e.g., “Family,” “Work Stress,” “Socializing”) even if different words are used.
• Deeper Correlations: The system could find links between specific emotions and quantitative data. For example: “You tend to feel more ‘overwhelmed’ on days when your RescueTime productivity is high but your sleep is under 6 hours.”
• Summarization for Trends: A monthly AI summary of the “qualitative” side of our lives to complement the “quantitative” data.