Project overview
Client: Nomo International, Inc 🇺🇸
Platform: iOS, Android, Backend, Frontend, Machine Learning
Industry: Healthtech / Elder Care
Services: Native Mobile App Development, Backend Architecture, Audio AI & Machine Learning, IoT Integration
Nomo uses advanced motion-sensing and AI-powered audio technology to discreetly monitor daily routines and detect potential emergencies—without the need for intrusive cameras or wearables. Its built-in fall detection, intelligent sound recognition, and direct integration with 911 Emergency Services help caregivers stay connected and responsive at all times. Whether it’s a fall, a smoke alarm, or a cry for help, Nomo ensures that the right people are notified—fast, privately, and reliably.
The challenge
Many elder care solutions rely on wearables or cameras—devices that are either forgotten, intrusive, or rejected altogether. Nomo wanted to build a system that was:
- Completely non-intrusive
- Capable of understanding behaviour and audio patterns
- Instantly responsive to emergencies
- Easy to install, use, and trust
They needed a full-stack product partner to help them build a mobile-first, real-time care platform that integrated AI, hardware, and cloud infrastructure—without overwhelming the end user.
Our approach
We partnered with Nomo as a full-cycle development team—delivering a seamless, connected experience across mobile, backend, and AI systems. Our work focused on three pillars:
- Native mobile apps: Built with Swift and Kotlin, designed for real-time updates, emergency response, and ease of use for caregivers.
- Scalable infrastructure: Powered by AWS, RESTful APIs, MQTT messaging, and Firebase integrations to support secure, real-time communication between devices and users.
- Edge-based audio AI: Custom TensorFlow Lite models detect critical sounds like smoke alarms or cries for help—processed locally for privacy and speed.
The result
Nomo Smart Care is now actively helping families monitor and protect their loved ones—privately and respectfully.
- Full production rollout across iOS and Android
- Thousands of devices monitored in real time
- Real-time alerts with under 1s latency
- Emergency response capabilities integrated natively
- Caregivers reporting higher confidence and peace of mind
Tech stack
Mobile: Swift, Kotlin
Backend: Node.js, TypeScript, REST APIs, MQTT
Cloud: AWS, Firebase, Google APIs
AI/ML: Python, TensorFlow Lite
Frontend: React.js, Next.js
Other: Lottie, RapidSOS, ESP32, AWS Cognito