A US-based HealthTech startup needed a complete digital platform — mobile, cloud, and AI — to move seizure monitoring from a reactive, hardware-only model to a personalised, predictive, and connected care system. Full delivery was handled through IT team outsourcing, with end-to-end ownership from architecture through to production.
Context & Challenge
Existing seizure management tools operate reactively: they detect a seizure after it begins through fall detection or convulsion monitoring. While useful for immediate safety, they offer no predictive capability, no personalisation, and no insight into what triggers seizures for a specific individual.
The client had a clear vision — a platform that continuously collects neurobiological data through wearable devices, analyses it with AI to identify personal seizure patterns, and alerts both the patient and their care network before an event occurs.
The challenge was building that platform from scratch: a real-time data pipeline, a HIPAA-compliant cloud infrastructure, a Flutter mobile application with native device integration, and an AI layer capable of delivering accurate, personalised predictions at scale.
Our Approach
We provided a fully dedicated outsourced engineering team, taking complete ownership of technical delivery while the client retained strategic and clinical direction.
The platform was architected around three principles: real-time data integrity, strict regulatory compliance, and a care model that extends beyond the individual patient to their family and support network.
Every architectural and development decision was made with HIPAA compliance as a non-negotiable baseline — from data encryption and access control to audit logging and secure transmission.
Technology & Architecture
The platform was built on a cloud-native, event-driven stack designed for reliability, real-time performance, and healthcare-grade security:
- Azure AKS for containerised orchestration and scalable deployment.
- Spring Boot for a robust, service-oriented backend.
- Flutter with native coding for a cross-platform mobile application with deep device integration for wearable data collection.
- Apache Kafka for real-time event streaming across the data pipeline.
- gRPC for high-performance communication between internal services.
- Redis for low-latency caching and session management.
- Elasticsearch for fast data indexing and search.
- Azure Cosmos DB & Microsoft SQL Server for flexible and relational data persistence.
- Azure AI for machine learning model execution and pattern recognition.
- Stripe for subscription and billing management.
- Full HIPAA compliance across all layers — data at rest and in transit, access management, audit trails, and Business Associate Agreement readiness.
Key Features Built
- Wearable Data Collection — Continuous neurobiological signal capture from discreet wearable devices, transmitted in real time to the mobile application and cloud platform.
- AI-Powered Personalised Prediction — Machine learning models trained on each individual’s neurobiological data to identify personal seizure triggers and generate early predictive alerts — moving beyond generic population-level thresholds.
- HIPAA-Compliant Mobile Application — A Flutter application with native device integrations for seamless wearable connectivity, real-time alert delivery, and secure patient data management.
- Family & Care Network Alerts — Real-time push notifications to designated family members and caregivers upon detection of a predictive signal, alongside integrated GPS tracking to enable rapid coordinated response.
- Cloud Data Pipeline — An event-driven Kafka pipeline processing continuous neurobiological data streams with low latency, feeding the AI prediction layer and persisting structured records for longitudinal analysis.
- Research Data Infrastructure — A secure data layer enabling anonymised aggregation of patient data to support clinical research and model improvement over time.
Compliance & Security
HIPAA compliance was implemented across the full platform — not as an afterthought, but as a foundational design requirement:
- End-to-end encryption for all patient data in transit and at rest
- Role-based access control across all platform components
- Complete audit logging for data access and system events
- Secure API design with authenticated service-to-service communication
- Infrastructure configuration aligned with HIPAA Technical Safeguard requirements
Impact
The platform shifts seizure care from a reactive, device-dependent model to a proactive, data-driven system — giving patients, families, and clinicians a level of personalised insight that was previously unavailable outside of clinical trial settings.
The result is improved patient safety and autonomy, reduced anxiety for caregivers, and a research-grade data infrastructure that grows more accurate as the platform scales.
Delivery Model
This project was delivered through full IT team outsourcing — we provided the complete engineering team covering backend, mobile (Flutter), DevOps, cloud architecture, and AI integration. The client focused on product vision and clinical partnerships while we owned technical execution from first line of code to production deployment.
Expertise Demonstrated
- HIPAA-compliant healthcare platform development
- Flutter mobile development with native wearable integration
- Real-time data streaming with Kafka and gRPC
- AI and machine learning integration on Azure
- Cloud-native architecture on Azure AKS
- HealthTech IT team outsourcing
- End-to-end product delivery for regulated environments
Vision
This project reflects a broader transformation in digital health: moving from isolated monitoring devices toward intelligent, connected platforms that learn from individual patients over time.
By combining AI, real-time data infrastructure, and a compliance-first architecture, the client is positioned to scale from early adopters to a clinical-grade platform — with the engineering foundation to support it.
