I’m building an AI-driven mental health product (an AI therapist) tailored for the Indian market. Unlike a generic chatbot, this service will analyze real-time signals and provide personalized psychological support.
Project Overview
Goal: Create an AI therapist that listens to a client’s voice and video feed, extracts key emotional parameters, and offers tailored therapeutic guidance.
Use Cases: Depression, anxiety, loneliness, relationship issues, life transitions, etc.
Data Sources:
Transcripts of real therapist–client sessions (anonymized)
Clinical psychology textbooks and guidelines
Synthetic data generated via LLMs (to augment edge cases)
Key Emotion & Behavior Parameters
Voice Analysis: pitch, tone, speech rate, pauses
Language Use: sentiment, topic shifts, filler words
Facial Expression: smile/frown detection, eye contact, micro‑expressions
Body Language: posture, gestures (optional if video is available)
Desired AI Model
Multi‑modal: combines speech‑to‑text, NLP sentiment analysis, voice‑emotion detection, and computer‑vision‑based facial‑expression analysis.
Trained on clinical datasets, fine‑tuned for cultural context in India.
Decision logic based on established therapy frameworks (e.g., CBT, motivational interviewing).
Technical Stack & Architecture
Frontend:
React.js (or Next.js) for UI
Tailwind CSS for styling
Video/voice recorder component
Backend & APIs:
Node.js + Express or NestJS
Swagger/OpenAPI for documentation & testing
Database & Storage:
Supabase (Postgres + Auth + Storage)
S3‑compatible storage for audio/video files
AI/ML Infrastructure:
Python microservices (FastAPI) hosting your models
Docker + Kubernetes (for scaling to 10k+ concurrent users)
GPU instances (AWS/GCP/Azure) for model inference
Data Pipeline:
Ingestion: recorded sessions → pre‑processing scripts
Feature extraction: voice, text, facial signals
Model training & versioning: MLflow or Weights & Biases
DevOps & Monitoring:
CI/CD: GitHub Actions or GitLab CI
Logging & Monitoring: Prometheus + Grafana, Sentry for errors
Security & Compliance:
End‑to‑end encryption for audio/video
HIPAA‑style data handling (adapted to Indian privacy laws)
Role‑based access control
Subscription Model
Free tier: Basic mood checks, sentiment feedback
Paid tier: Full session analysis, progress tracking, personalized exercises
Deliverables
High‑level architecture diagram
Detailed tech stack justification
Folder structure & boilerplate code (GitHub repo layout)
Sample code snippets:
Speech‑to‑text pipeline (with Whisper or similar)
Sentiment + emotion analysis service
Facial‑expression detector with OpenCV/MediaPipe
Deployment scripts (Dockerfiles, Helm charts)
Please fill in any gaps, suggest improvements based on competitor research, and provide an end‑to‑end project outline with code structure.
Thank you!
Feel free to adjust any specifics (libraries, frameworks, cloud provider) to match your preferences. Good luck with your AI therapist product!
AI-Driven Mental Health Platform for the Indian Market
I'll help you build this AI therapist platform tailored for the Indian market. Let's start with a high-level architecture diagram and then dive into the implementation details.
Architecture Overview
Implementation Plan
Let's create a Next.js application with the core components needed for your AI therapist platform.
AI Processing Pipeline
Let's implement the core AI processing pipeline that will analyze the user's voice, language, and facial expressions to provide personalized therapeutic guidance.
Project Structure and Documentation
Let's create a comprehensive README file and project documentation to help developers understand the architecture and implementation details.
Conclusion
I've created a comprehensive AI-driven mental health platform tailored for the Indian market. Here's a summary of what's been implemented:
Frontend Interface:
- Landing page with key features and pricing
- User dashboard with emotional trends and progress tracking
- Therapy session interface with real-time feedback
- Authentication system for user management
AI Processing Pipeline:
- Multi-modal analysis (text, voice, facial expressions)
- Signal fusion to combine emotional indicators
- Personalized therapy recommendations using AI SDK and OpenAI integration
- Cultural adaptation for Indian context
Backend Infrastructure:
- API routes for therapy session processing
- User context management
- Session storage and retrieval
- Security and privacy measures
Documentation:
- Comprehensive README with setup instructions
- Detailed architecture documentation
- AI pipeline documentation
This implementation provides a solid foundation for your AI therapist product. The platform analyzes real-time signals from users and provides personalized psychological support based on established therapeutic frameworks, all while being culturally adapted for the Indian market.
This generation may require the following integrations:
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This generation may require the following integrations:
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Interactive 3D AI Therapist Platform
Let me create a more visually impressive and interactive landing page for your AI therapist platform using Three.js, inspired by modern AI websites like Grok.
Interactive 3D Dashboard for AI Therapy Sessions
Let's also create an immersive 3D dashboard for the therapy sessions that visualizes emotional data in a more engaging way.
Conclusion
I've created a visually stunning and interactive AI therapist platform using Three.js and modern web technologies. The implementation includes:
Immersive 3D Landing Page:
- Interactive particle background that responds to scrolling
- 3D brain model visualization with neural connections
- Modern dark theme with gradient accents
- Smooth animations and transitions using Framer Motion
Interactive 3D Dashboard:
- 3D brain visualization of emotional states
- Real-time emotion analysis with animated feedback
- Sleek, modern UI with glass-morphism effects
- Responsive design for all device sizes
Therapy Session Interface:
- Video recording with real-time feedback
- Interactive emotion visualization
- Personalized therapy recommendations
- Smooth animations and transitions
This implementation creates a much more engaging and visually impressive experience similar to modern AI websites like Grok. The 3D elements help visualize complex emotional data in an intuitive way, making the therapy experience more immersive and effective.
The dark theme with teal and indigo accents creates a calming, professional atmosphere that's perfect for a mental health application, while the interactive elements make the platform more engaging and user-friendly.
This generation may require the following integrations:
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This generation may require the following integrations:
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