Healthcare solutions.
Bedside and clinical monitoring products, built and operated by the same engineers who ship your production software.
Our products
tina.care®
A contactless bed-safety monitoring platform for hospitals and inpatient care facilities — Industry 4.0 IoT sensors above the bed, no cameras or wearables. Not a medical device and not intended for diagnosis; built for operational awareness and staff response time. Fully implemented and long-term operated by Bonitoo, including continuous development of new versions.
Use cases
- Bed-exit detection and alerts, timed to each person's mobility profile
- Central dashboard across many beds, with color-coded status cards and a dedicated urgent-events row
- Night mode, passive monitoring, and unoccupied-bed modes for different care contexts
- Multi-device access — phones, tablets, TVs, monitors — with real-time sync across an organization
- Event history and PDF/Excel reporting for clinical and managerial review
Tech challenges & stack
Near real-time event propagation from sensor to application, with delayed/confirmed state transitions to reduce false positives rather than reacting to every raw sensor blip. No local buffering during outages — sensors resume live transmission the moment connectivity returns. Communication between sensors, backend and applications is encrypted end to end, sensors talk only to predefined backend endpoints, and the whole system is designed to minimize personal data exposure — operational awareness, not medical diagnostics.
Andromeda
A healthcare data analytics platform for collecting, integrating and analyzing heterogeneous biological and physiological time-series data from non-invasive sensors, in support of personalized care. Not a medical device, and does not provide automated diagnosis or treatment decisions — outputs are meant for expert interpretation. Currently in the prototype phase.
Use cases
- Continuous ingestion of time-series data from multiple non-invasive sensor types
- Identification of individual behavioral patterns and baselines
- Anomaly detection and individual-level risk stratification
- Structured, exportable outputs for visualization and clinical-research reporting
Tech challenges & stack
Deterministic, pipeline-based processing that handles missing data, variable sampling rates and ingestion delays without manual intervention. Clear separation between training, validation and inference workflows for the machine-learning components, and between analytical data and anything directly identifiable — with anonymization/pseudonymization support built in. Modular, horizontally scalable pipeline architecture designed for iterative experimentation as the product moves beyond prototype.