WELLab AI-Enabled Research & Impact Platform

Data Model (see references/data-model.md)

Core entities: Participants, Observations, Health, Lifespan, Cognitive, Interventions. Each entity has standard fields plus module-specific extensions.

AI Capabilities Layer (see references/ai-capabilities.md)

• IDELS AI Extension — emotion → life satisfaction coupling classification
• Temporal Dynamics Engine — variability, rate of change, volatility
• Bidirectional Modeling System — wellbeing ↔ health, health ↔ wellbeing

Dashboards (see references/dashboards.md)

• Participant Experience UI
• Researcher Dashboard
• Policy Dashboard

When to Read Reference Files

Technology Stack

• Frontend: React / Vite, TypeScript, Tailwind CSS, Recharts / D3
• Backend: Node.js / Express, TypeScript
• AI/ML: Python (scikit-learn, statsmodels, DoWhy, PyTorch), Anthropic Claude API
• Infrastructure: AWS (Lambda, DynamoDB, S3, API Gateway, SageMaker)
• Data Pipeline: AWS Glue / Step Functions, DynamoDB Streams
• Auth: AWS Cognito (researcher + participant pools)
• Secrets: AWS SSM Parameter Store (SecureString)

Key Constraints

• IRB compliance: All participant data must be de-identified or under approved protocol.
• HIPAA-adjacent: Health data requires encryption at rest + in transit, audit logging, minimum necessary access.
• Reproducibility: Every AI pipeline must be version-controlled with pinned dependencies and deterministic seeds.
• Cross-cultural fairness: Models must be audited for demographic bias before deployment.
• Individual vs population: Never surface individual risk scores to unauthorized viewers. Population dashboards must aggregate to k-anonymity thresholds.

Output Patterns

When building features for this platform, follow these patterns:

Spec documents

Include: Goals, Non-goals, User stories, Data model changes, API routes, Security considerations, Edge cases, Test plan, Rollout plan.

Code output

• TypeScript for all Node/React code
• Python for ML/analytics pipelines
• Include file tree + filename headers
• Secure by default (least-privilege IAM, no hardcoded secrets)
• Small modular utilities

Data artifacts

• JSON schemas with example payloads
• CSV templates with headers + example rows
• Always include participant_id, timestamp, source_module

Quick Start Commands

# Clone and install
git clone <repo-url> wellab-platform
cd wellab-platform
npm install          # frontend + backend
pip install -r requirements.txt  # ML pipelines

# Dev
npm run dev          # Vite dev server
npm run api:dev      # Express API (nodemon)

# Test
npm test             # Jest + React Testing Library
pytest tests/        # ML pipeline tests

# Deploy
npm run deploy:staging
npm run deploy:prod