Allez Health is a mobile app for continuous glucose monitoring. It connects to a sensor via Bluetooth, regularly receives measurements, processes them with a special algorithm, and shows the user the current glucose level, trends, and important changes in status.
We developed native apps for iOS and Android, the backend, API, cloud infrastructure, and a set of services for storing metrics, users, accounts, and device data.
Task
The task was to create a stable product for daily medical monitoring: connect to a Bluetooth sensor, ensure continuous data intake, correctly process measurements, provide clear visualization, and send timely alerts about critical changes in glucose levels.
A separate part of the task was the server platform: an API for mobile apps, microservices for working with accounts and metrics, reliable data storage, documentation, tests, and infrastructure ready for scaling.
Sensor connection
The app includes sensor search and connection, user onboarding, and informational screens that help configure monitoring correctly. After connection, the app receives data via Bluetooth and passes it to the internal glucose calculation algorithm.
Mobile apps
The native iOS and Android apps are built around daily monitoring scenarios. The Now section shows the current value, status over the recent period, and nearest trend so the user can quickly understand what is happening right now.
The trend chart displays data for 12 hours, 24 hours, and 3 days. This helps users see not only individual measurements, but also dynamics: how glucose levels changed throughout the day, after meals, physical exercise, or other events.
Events and context
The user can add events: meals, physical exercise, and other activities. These notes make charts more useful because measurements can be analyzed together with the context in which they appeared.
Analytics and reports
The app has a separate statistics section with metrics for 24 hours, 7 days, and 30 days. Data is compared with previous periods, so users see not only current numbers, but also how metrics change over time.
Report generation for the last 15 days was also implemented. The report includes statistics, charts, and summary data that can be used to analyze the condition and discuss results with a specialist.
Notifications
The app notifies users when glucose rises above or falls below configured limits. In the settings, users can change the target range, alert levels, and schedule so notifications match their individual needs.
Backend and infrastructure
A full server side deployed in Amazon Web Services was developed for the product. The backend consists of an API and a set of microservices that store information about users, accounts, devices, and collected metrics.
The infrastructure was designed with autoscaling, backups, stable operation under load, and industry-standard security and reliability practices in mind.
A separate large effort focused on autoscaling and handling peak load. Performance and high-load tests showed that the platform in its base configuration can handle 10,000 requests per second, which is estimated to cover the needs of 1 million concurrent users.
Infrastructure as Code
The cloud environment is deployed with Terraform. This makes the infrastructure reproducible, controlled, and convenient for supporting different development, testing, and production environments.
Quality
The mobile apps are fully covered by unit tests and end-to-end tests. The interface works in light and dark themes, supports localization into multiple languages, and passes checks for key user scenarios.
The backend also has 100% unit test coverage. API documentation was prepared according to standards so the mobile, backend, and QA teams could work with service contracts in sync.
Result
Allez Health received a complete technical foundation for continuous glucose monitoring: native mobile apps, algorithmic sensor data processing, personalized notifications, charts, statistics, reports, and a scalable server platform in AWS.
