howami.ai

Inspiration

Mental health is a critical aspect of well-being, yet many people lack access to the resources they need. We wanted to create a tool that not only helps users assess their mental health risks but also connects them with nearby support services. Our goal was to make mental health support more accessible and personalized.

What it does

Howami.ai analyzes users' mental health by evaluating their responses to a series of questions. The AI-powered tool then provides an assessment of potential mental health risks and suggests nearby resources for support. This empowers users to take proactive steps toward better mental well-being.

How we built it

We used machine learning models to analyze user inputs and assess mental health risks. The frontend was built using modern web technologies, while the backend leverages AI models trained on mental health data. We integrated location-based services to provide tailored support recommendations.

Challenges we ran into

One of the biggest challenges was ensuring the accuracy and sensitivity of mental health assessments. We also faced difficulties integrating location-based resources while maintaining user privacy and data security. Balancing performance with accuracy was another challenge during model training. Integrating machine learning model was also hard and we had to create a separate python server

Accomplishments that we're proud of

We're proud to have built a functional, user-friendly tool that addresses a significant societal need. Successfully integrating AI-powered assessments with local resource recommendations was a major milestone for us.

What we learned

We learned a lot about balancing technical accuracy with ethical considerations, especially when dealing with sensitive data. Additionally, we gained experience in developing AI models that are both effective and respectful of users' privacy.

What's next for howami.ai

We plan to improve the accuracy of our mental health assessments and expand our database of support resources. In the future, we aim to incorporate multilingual support and enhance accessibility features to reach a broader audience.

Built With

• https://github.com/thelemon404/hackslu.git
• python
• svelte
• typescript