A comprehensive enterprise-grade AI platform for employee wellness, organizational health monitoring, and workforce resilience. Built with agentic AI architecture, privacy-first design, and seamless enterprise integrations.

Experience the intuitive UI/UX of our wellness platform - from personalized dashboards to AI-powered conversations and comprehensive analytics.

• HR & Leadership: Privacy-safe analytics on organizational stressors and burnout risks
• Employees: Personalized AI wellness companion with real-time support
• Enterprise: Seamless integration with Slack, Teams, Outlook, and HRIS systems

The platform operates through five specialized AI agents working in orchestration:

1. Wellness Companion Agent - Direct employee interaction, mood tracking, stress check-ins
2. Resource Recommendation Agent - EAP matching, wellness resource curation
3. Sentiment & Risk Detection Agent - Burnout prediction, stress pattern analysis
4. Analytics & Reporting Agent - HR dashboards, organizational health insights
5. Policy & Privacy Agent - Data anonymization, compliance enforcement

Backend

• FastAPI (APIs & microservices)
• LangChain/Guardrails (agent orchestration)
• PostgreSQL + Redis (data persistence)
• ChromaDB/Pinecone (vector embeddings)

Frontend

• React (employee dashboard, HR analytics)
• TypeScript (type safety)
• Material-UI (enterprise design system)

Integrations

• Slack/Teams bots
• HRIS connectors (Workday, BambooHR, etc.)
• Email integration (Outlook, Gmail)

Observability & Security

• Prometheus + Grafana (monitoring)
• Open Policy Agent (OPA) for policy enforcement
• Differential privacy for analytics
• HIPAA/GDPR/SOC2 compliance

• Docker & Docker Compose
• Kubernetes cluster (for production)
• PostgreSQL 14+
• Redis 6+

# Clone and setup
git clone <repository>
cd enterprise-wellness-ai

# Environment configuration
cp .env.example .env
# Edit .env with your configuration

# Start development environment
docker-compose up -d

# Initialize database
docker-compose exec backend python -m scripts.init_db

# Access the application
# Frontend: http://localhost:3000
# Backend API: http://localhost:8000
# Grafana: http://localhost:3001

# Kubernetes deployment
kubectl apply -f k8s/

# Or using Helm
helm install wellness-ai ./helm/

• AI Wellness Companion: 24/7 chat support in Slack/Teams
• Mood Journaling: Secure, private emotional tracking
• Personalized Resources: Tailored wellness content and exercises
• Stress Check-ins: Proactive wellness monitoring

• Organizational Health Dashboard: Aggregated, anonymized insights
• Burnout Risk Analytics: Predictive modeling for high-risk teams
• Engagement Metrics: Workforce sentiment and wellness trends
• Intervention Recommendations: Data-driven wellness program suggestions

• Privacy-First Design: End-to-end data anonymization
• Enterprise Security: SOC2, HIPAA, GDPR compliance
• Audit Trails: Complete data governance and access logs
• Policy Enforcement: Automated compliance checking

# Database
DATABASE_URL=postgresql://user:pass@localhost/wellness_db
REDIS_URL=redis://localhost:6379

# AI Services
OPENAI_API_KEY=your_openai_key
ANTHROPIC_API_KEY=your_anthropic_key

# Enterprise Integrations
SLACK_BOT_TOKEN=your_slack_token
TEAMS_APP_ID=your_teams_app_id
WORKDAY_CLIENT_ID=your_workday_client_id

# Security & Privacy
ENCRYPTION_KEY=your_encryption_key
OPA_POLICY_URL=http://opa:8181/v1/data

# Observability
PROMETHEUS_ENDPOINT=http://prometheus:9090
GRAFANA_URL=http://grafana:3000

Each agent can be configured independently:

# config/agents.yaml
wellness_companion:
  model: gpt-4
  memory_type: episodic
  response_style: empathetic
  risk_threshold: 0.7

resource_recommendation:
  vector_db: chromadb
  embedding_model: text-embedding-ada-002
  recommendation_engine: collaborative_filtering

sentiment_analysis:
  models:
    - vader
    - roberta
  risk_indicators:
    - burnout
    - stress_spike
    - toxic_patterns

• Agent performance and response times
• User engagement and satisfaction
• Risk detection accuracy
• Privacy compliance metrics
• System health and availability

• Executive Dashboard: High-level organizational health
• HR Analytics: Detailed workforce insights
• Technical Operations: System performance and health
• Compliance Dashboard: Privacy and security metrics

• End-to-end encryption: All data encrypted at rest and in transit
• Differential privacy: Analytics with mathematical privacy guarantees
• Data anonymization: Automatic PII removal before processing
• Consent management: Granular user consent controls

• HIPAA: Healthcare data protection
• GDPR: European data privacy
• SOC2: Security and availability controls
• Enterprise policies: Custom organizational compliance

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

This project is licensed under the MIT License - see the LICENSE file for details.

• Documentation: docs.enterprise-wellness.ai
• Support Portal: support.enterprise-wellness.ai
• Email: support@enterprise-wellness.ai

Built with ❤️ for better workplace wellness