🧰 Technologies Used
Synora was built using a carefully chosen stack that balances reliability, scalability, cost, and ease of deployment across home and clinical environments.
Programming Languages
- Python – AI model development, data processing, and backend logic
- C and C++ – Embedded firmware for low-power wearable devices
- JavaScript and TypeScript – Caregiver dashboard and mobile interface logic
Frameworks and Libraries
- TensorFlow Lite – Lightweight machine learning models optimized for edge devices
- PyTorch – Prototyping and training AI models
- React and React Native – Web and mobile caregiver applications
- Node.js with Express – Backend API services
- MQTT – Lightweight real-time device communication
Hardware and Embedded Platforms
- ESP32-class microcontrollers – Sensor integration, wireless communication, and power-efficient processing
- IMU and vital sensors – Motion, fall detection, and physiological signal capture
Cloud and Backend Services
- AWS – Scalable backend infrastructure and device management
- AWS IoT Core for device connectivity
- AWS Lambda for event-driven processing
- AWS S3 for encrypted data storage
- AWS IoT Core for device connectivity
Databases
- PostgreSQL – Structured user, device, and event data
- Redis – Real-time alert queues and low-latency state management
APIs and Integrations
- REST APIs – Secure communication between devices, cloud services, and caregiver apps
- Push notification APIs – Instant caregiver alerts on critical events
- Encryption libraries – End-to-end data protection and user-controlled access
DevOps and Tooling
- Docker – Consistent deployment across environments
- Git and GitHub – Version control and collaborative development
- CI and CD pipelines – Automated testing and deployment workflows
Security and Privacy
- TLS and AES encryption – Secure data transmission and storage
- Role-based access control – Ensuring data visibility only to authorized caregivers
This technology stack allowed Synora to remain affordable, scalable, and privacy-first while delivering real-time, AI-driven assistive care.
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