An enterprise-grade system, BioT PaaS is built on the following 3 pillars: Connect, Collaborate, and Care.


Securely connect devices to the cloud in order to bring the power of cloud to device manufacturers.

  • Secure data transfer and storage, optimized per data type (numeric biomarkers, waveforms, images, raw data files, and more).

  • Cloudify - Go beyond device power and implement advanced data-driven AI algorithms on the cloud.

  • Remote device management – Configuration, status, alerts.

  • Constant updates – Seamless update of capabilities.

    • Centralized, zero-touch firmware updates.
    • Cloud software updates - Update once, affecting all deployments at zero time.
  • Open platform - Gain access to the collected big data to improve service for caregivers, expedite clinical trial analysis, gain visibility into Post-Market Clinical Follow-up (PMCF) studies, and correctly identify possible risks and real-world behavior in a timely manner.


  • Share information with doctors, patients and the ecosystem (subject to configurable fine-grained attribute-based access control policies).

  • Improve patient engagement and gain better data for your clinical trial and PMCF by personalizing the patient experience:

    • Engage when the patient is most likely to cooperate and when the data is still fresh (for example, sending a questionnaire after you’ve detected a medical event).
    • Send notifications via the medium convenient to your patient.
    • Tailor questionnaires based on experience with the individual patient, and improve feedback.
  • Integrate with the ecosystem (EHR, RPM, EDC, QMS, etc.), share and receive information to improve your data, as well as improving clinician experience by integrating into their existing workflows.

  • Analyze adherence patterns, per patient group, across your entire deployment, to gain a better understanding of how best to get patients to use the device or follow exercise protocols.


Improve patient outcome by:

  • Understanding adherence patterns and creating personal engagement in order to effectively prevent non-adherence.

  • Identifying critical events and creating automatic actions (alert physician, patients, etc.).

  • Providing real-world, accurate information for physicians, allowing better treatment decisions to be made by strong visualization modules. It combines observations with clinical events helping to develop intuition for cause and effect.

  • Providing self-management tools to patients allowing them to become an active factor in their own treatment.

    • Visualization of the patient's current status and adherence, allowing the patient to understand how they are affecting the outcome.
    • Self-reporting of feedback on their condition and treatment.
    • Adherence management tools allow the patient to take an active part in managing their adherence, by setting targets and keeping up with them.