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Feelinghub Mental Wellness App

Redefining Digital Mental Wellness

At CodeXae, we created Feelinghub - a secure, empathetic web app that helps users understand and nurture their emotional health through intelligent journaling and mood analysis. This project combines thoughtful design with AI to create a calming digital space for emotional reflection.

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Feelinghub Mental Wellness Platform

With 1 in 5 adults experiencing mental health challenges annually, Feelinghub addresses the growing need for accessible emotional support tools. CodeXae designed and developed this platform from concept to deployment, focusing on privacy, simplicity, and emotional intelligence.

This case study explores our human-centered design approach, technical implementation, and the impact of creating a digital tool that genuinely supports emotional wellbeing.

Project Overview

Emotional Journaling

Create a non-invasive way for users to track daily emotions through intuitive journaling and mood tagging.

Pattern Recognition

Develop data visualization to help users identify emotional trends and triggers over time.

AI Insights

Integrate smart mood analysis to offer personalized feedback and coping strategies.

Privacy First

Ensure all user data remains encrypted and private with GDPR-compliant practices.

Calming Interface

Design a minimalist, soothing UI that encourages regular use without overwhelm.

Mobile Accessibility

Optimize for full responsiveness across all devices with a mobile-first approach.

Technology Stack

Frontend

  • React.js
  • Tailwind CSS
  • Framer Motion

Backend

  • Node.js & Express
  • MongoDB
  • Mongoose ODM

Security

  • JWT Authentication
  • bcrypt Hashing
  • GDPR Compliance

AI Integration

  • OpenAI API
  • Sentiment Analysis
  • Custom Prompt Engineering

1Mood Journaling

Intuitive interface for logging emotions with tags, ratings, and free-form entries. Users can track daily feelings and revisit their history.

2Insights Dashboard

Visual representations of mood patterns including heatmaps, weekly trends, and emotion distribution to identify personal triggers.

3AI Mood Analysis

Generates personalized affirmations, mood summaries, and self-care suggestions based on journal entries using OpenAI's sentiment analysis.

4Self-Care Tools

Curated mindfulness exercises including breathing prompts, gratitude journaling, and guided reflection templates.

Week 1-2: Research & Wireframes

Conducted user surveys, designed low-fidelity wireframes, and created empathy maps to understand emotional journaling needs.

Week 3-4: UI/UX Design

Developed high-fidelity mockups with soothing pastel palette and clean typography. Iterated through 3 feedback rounds.

Week 5-8: Core Development

Built React frontend components, Node.js APIs, MongoDB integration, and implemented JWT authentication with encryption.

Week 9-10: AI Integration

Connected OpenAI API, fine-tuned sentiment analysis prompts, and implemented non-judgmental response generation.

Week 11-12: Testing & Launch

Conducted usability testing with 20+ users, fixed UX bugs, optimized mobile experience, and deployed to production.

User Engagement

5,000+ mood entries logged in first 2 months with 70% mobile usage showing strong adoption.

Emotional Impact

92% of beta users reported improved emotional awareness and self-understanding.

AI Effectiveness

Users described AI suggestions as "comforting" and "surprisingly accurate" in feedback sessions.

Future Potential

Strong interest for expansion into workplace wellness and therapist-assisted versions.

Design & Development Highlights

1. Emotion-Centered UI/UX

We crafted an interface that feels safe and calming:

2. Intelligent Mood Analysis

Our AI integration provides meaningful emotional insights:

3. Privacy Architecture

Security measures to protect sensitive user data:

Key Challenges & Solutions

1. Balancing AI with Emotional Sensitivity

Creating AI responses that felt genuinely supportive without being clinical or generic.

Solution: Extensive prompt engineering and testing with diverse user groups to ensure tone was consistently warm and helpful.

2. Designing for Emotional States

Users might access the app during vulnerable moments needing different UI approaches.

Solution: Context-aware interface that simplifies options during negative mood logs and expands during positive/neutral states.

3. Encouraging Consistent Use

Mental wellness tools often suffer from low engagement after initial novelty.

Solution: Gentle reminders, streak tracking, and showing meaningful insights from minimal data to demonstrate value quickly.

Project Outcomes

Feelinghub launched in beta with 100 users and demonstrated strong product-market fit:

Let's Build Your Wellness Solution

Inspired to create your own mental health, wellness, or emotionally intelligent application?

Contact Our Team

📧 info@codexae.com

🌐 www.codexae.com

Let's create technology that truly supports mental wellbeing.