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Horizon is a mental health journal app that analyzes daily entries for sentiment and predicted conditions, tracks mood/sleep patterns, and generates weekly/monthly reports with risk and trend insights.

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Horizon

AI‑Powered Mental Health Journal, Sentiment Analyzer & Report Generator

Horizon is a mental health journaling platform built with Next.js that helps users reflect on their daily life, track emotional and behavioral patterns, and generate meaningful insights over time.

AI in Horizon is an enhancement layer, not the product itself. The core of Horizon is structured journaling, analytics, and reflection, with AI used carefully to support understanding, summarization, and long‑term pattern recognition.


✨ Key Features

📝 Daily Journaling

  • Write and save daily journal entries
  • Encourages self‑reflection and emotional awareness
  • Helps users build consistency through daily tracking
  • Calendar‑based journal history

🧠 AI‑Powered Insights

AI helps interpret data — it does not replace human judgment.

  • Sentiment analysis for journal entries
  • Non‑clinical condition signals based on trends
  • Time‑aware insights (recent days vs long‑term patterns)
  • Better long‑term emotional and behavioral trend tracking

AI explanations are grounded in structured analytics, not raw text guesses.


🔍 Smart Search

  • Search past journal entries using keywords
  • Quickly find specific events, triggers, or emotional states
  • Useful for reflection and therapist consultations

📊 Structured Tracking

Each journal entry can optionally include:

  • Mood / happiness score
  • Confidence level
  • Sleep hours and sleep quality
  • Stress and overthinking level
  • Productivity
  • Exercise, diet, and screen time
  • Physical problems or symptoms
  • Exception notes
  • Location (optional)

These structured signals power analytics and AI‑assisted insights.


🧭 Onboarding Survey

When a user opens Horizon for the first time, they complete a short onboarding survey to capture a personal baseline, including:

  • Typical happiness level
  • Normal sleep duration and quality
  • Common problems or stressors
  • Known mental conditions (optional)
  • Location (optional)

Why this matters

  1. Personal Baseline Setup Helps Horizon understand what is normal for the user.

  2. Improved Insights Baselines are used for comparisons, trends, and AI explanations.

  3. Anonymous Community Insights (Optional) Aggregated trends may be shown without exposing personal identity.


📄 Report Generation (For Psychiatrists / Therapists)

Horizon can generate structured mental health reports that users may choose to share with professionals.

Reports may include:

  • Weekly / monthly mood trends
  • Sentiment distribution
  • Sleep‑mood correlations
  • Journaling consistency scores
  • Highlighted improvement or deterioration periods
  • Clear summary insights

These reports help professionals:

  • Understand patterns quickly
  • Reduce reliance on memory‑based recall
  • Make data‑backed decisions

🧠 How AI Is Used in Horizon

AI is one component of Horizon, not the entire system.

  • Raw journal data is never sent directly to AI

  • Data is normalized and analyzed in code first

  • Trends, correlations, and risk signals are computed deterministically

  • AI is primarily used for:

    • explanation
    • reflection
    • summarization

This design keeps Horizon safe, explainable, and reliable.


🗃️ Journal Data Stored

Each journal entry may store:

  • Journal text
  • Sentiment label and score
  • Condition signal (non‑clinical)
  • Mood / happiness score
  • Confidence
  • Sleep hours and sleep quality
  • Stress and overthinking level
  • Productivity
  • Exercise, diet, and social interaction
  • Physical problems
  • Exception notes
  • Location
  • Created timestamp

AI works on derived features, not raw journal text.


🗃️ Tech Stack

Frontend

  • Next.js (App Router)
  • React
  • TypeScript
  • Tailwind CSS
  • Data visualizations & animations

Backend

  • Next.js API routes
  • TypeScript
  • Redis (caching & performance optimization)
  • Structured analytics pipelines

Data

  • Supabase (PostgreSQL)
  • Supabase Auth
  • Normalized journal schema
  • Derived analytics layer

AI / Analytics

  • Sentiment analysis
  • Time‑series trend analysis
  • Statistical metrics
  • Rule‑based intelligence
  • Controlled LLM usage (explanation only)

🚀 Future Enhancements

  • Alerts when mental health deteriorates over time
  • Weekly / monthly reflection summaries
  • Downloadable report export (PDF)
  • Nearby doctor suggestions (opt‑in, location‑based)
  • Advanced analytics dashboard
  • Long‑term progress visualization

⚠️ Disclaimer

Horizon is not a medical device and does not provide diagnosis or treatment. It is a self‑reflection and insight tool intended to support mental well‑being.


🛠️ Project Setup

git clone https://github.com/your-username/horizon.git
cd horizon
npm install
npm run dev

Final Note

Horizon is built as a product first:

  • journaling
  • reflection
  • structure
  • analytics

AI exists to support these goals, not replace them.

About

Horizon is a mental health journal app that analyzes daily entries for sentiment and predicted conditions, tracks mood/sleep patterns, and generates weekly/monthly reports with risk and trend insights.

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