MindMate

MindMate is an AI-powered mental health companion designed to help users track their moods and provide personalised activity suggestions based on their emotional state.

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Inspiration

Mind Mate is inspired by the urgent need for accessible, AI-powered mental health support in today’s world. According to the World Health Organization, nearly 1 in 8 people globally are affected by mental health disorders. Many people hesitate to reach out due to stigma, cost, or lack of access to traditional mental health services. Survey data suggests among the most impacted, young adults—feel “serious loneliness,” highlighting the widespread need for new kinds of support.
Mind-Mate is a personal mental wellness companion that combines empathetic AI chat support with intelligent mood tracking.
It offers a safe, always-available space to talk, while also suggesting science-backed activities to ease anxiety and improve mood. By tracking daily check-ins, Mind-Mate helps users recognize emotional patterns and fosters greater self-awareness, making mental health support more accessible and personalised.

Category

Healthcare & Well-being – AI for mental well-being, disease identification, and accessibility.

What it does

Mind Mate is an AI-driven mental wellness companion. It enables users to log their moods, receive tailored activity recommendations, and interact with a conversational AI.
Features include:

  • Mood tracking with visual charts
  • AI-powered chat support
  • Activity suggestions
  • Calming, accessible design

How we built it

The project consists of:

  • Frontend: Built with React (Vite, Chart.js, Framer Motion, CSS Modules).
  • Backend: Developed with FastAPI (Python). Integrates Gemini LLM for AI responses.
  • Multi-agent architecture: Specialized agents handle mood analysis, activity recommendations, coversational processing.
  • Integrated Social login for easier login functionality.
  • Deployed on Google Cloud Platform using Cloud Run.

Challenges we ran into

  • Integrating AI mood analysis and mapping it to meaningful activity recommendations.
  • Efficiently processing and storing user mood data.
  • Leveraing knowledge of GCP services (like Cloud Run, Firestore) but same time troubleshooting issues related to permissions, deployment, and service integrations.
  • Implementing robust authentication, secure storage of data required extra diligence.

Accomplishments that we're proud of

  • Successfully built a modular, multi-agent system for mental health support.
  • Achieved seamless integration between AI-driven backend and a modern, calming frontend.
  • Implemented mood tracking and personalised activity suggestions tailored to user emotions.

What we learned

  • Building AI-powered wellness tools requires a balance between technology and sensitivity to user privacy and experience.
  • Multi-agent architectures can effectively divide complex tasks like mood tracking, activity recommendation, and chat processing.
  • Capabilities of different AI models and how prompt engineering plays a crititcal role defining the agents within the application.

What's next for Mind-Mate

  • Mood Collages: Automatically generate visually appealing collages that capture a user’s mood history.
  • Mood Journals: Introduce a personalised journaling feature that allows users to record their thoughts and emotions.
  • Gamification and Achievements: Motivate users with mood-boosting challenges, streaks, and badges. -Voice Input: Let users log moods and journal notes via voice commands.
  • Performance: Asynchronous background processing for heavy tasks.
  • Dynamic Visualisation: Enhance accessibility by offering customisable visual elements and multiple display options to suit different user preferences and needs.

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