Inspiration

I previously worked at a mental health platform startup and wanted to explore how an agent could deliver more personalized mental health care.

What it does

Empathetic Chat – AI-powered conversations offering emotional support Daily Check-ins – Structured mental health questionnaires Health Evaluation – Quantitative analysis of mental health trends Personalized Recommendations – Tailored content and activities Proactive Companion – Intelligent scheduling of check-ins Privacy-First – Secure data handling and user confidentiality Cloud-Ready – Deployable on Streamlit Cloud or AWS infrastructure

How we built it

We developed a modular Python project with a Streamlit UI, integrating an LLM through AWS Bedrock (boto3).

Challenges we ran into

I spent significant time figuring out how to deploy the agent on AWS Cloud in a way that securely stores user profiles.

Accomplishments that we're proud of

The project was completed within just one week.

What we learned

This was my first experience adding user profiles to an agent and designing it to act proactively.

What's next for Mental Health Companion Agent

I aim to enhance the agent’s ability to recommend more diverse information from a wide variety of sources.

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