Mindhaven - Women's mental health platform

Game Section (in resources page)
Landing Page
Dashboard
Communities
Game havenshot
Bookings
Profile Section
Resources page
Courses Complete page
Mindhaven Psychological Metrics
Courses
Footer Landing page

Inspiration

Mental wellness apps exist in large numbers, but most either rely on generic advice or simulate AI without using real data. The idea behind Mindhaven came from the need to build a platform that genuinely helps users, particularly women, by providing personalized and data-driven mental health support. The goal was to avoid superficial features and instead build something that actually works using real machine learning and psychology-backed content.

What it does

Mindhaven is a mental health platform focused on women's wellness. It provides personalized mental wellness support using machine learning models, structured quizzes, curated courses, and relaxing games. The app tracks user progress and adapts based on interactions, offering smart recommendations and a safe space to explore mental health.

How we built it

Frontend is built using React and Tailwind CSS. Backend is with Firebase for authentication and data storage. Machine learning models are trained in Python using real datasets to power assessments and personalized suggestions. Games are integrated from open-source wellness projects and re-themed for Mindhaven. User data is securely stored with encryption in place.

Challenges we ran into

Integrating machine learning with the frontend in a real-time, user-friendly way
Ensuring the tone of the app remained supportive without sounding clinical
Working with mental health datasets that are relevant, inclusive, and reliable
Designing a UI/UX that is simple yet scalable
Ensuring performance on low-end devices and poor network conditions

Accomplishments that we're proud of

Successfully integrated real ML into user-facing features
Built a working MVP with quizzes, games, course modules, and data tracking
Achieved a balance between technical performance and user-centered design
Designed the system to allow future updates without breaking the core flow
Developed a solution that could genuinely assist someone in managing stress or anxiety

What we learned

Real AI-backed wellness tools require attention to both data accuracy and UX
User experience in mental health apps depends heavily on tone, language, and visuals
It's possible to create a full-stack AI product within limited time when components are well-structured
Thoughtful UI/UX decisions can impact how comfortable users feel while using the app