Medical Devices

Inference runs locally, so imaging, vitals, and recordings never leave the hardware. No cloud round-trip means no PHI in transit — a dramatically simpler HIPAA and GDPR posture.

Run segmentation, detection, and guidance models on endoscopy, ultrasound, and surgical video with deterministic, sub-frame latency on Jetson-class compute.

Fuse vitals, waveforms, and camera streams at the bedside to catch deterioration early — alerts fire in milliseconds, even if the hospital network goes down.

No shared cloud tenancy, no variable network latency. The device behaves the same in validation and in the field — exactly what regulators expect of a medical device.

Hardware-backed device identity, signed and verified OS images, and encrypted storage keep every device authenticated and tamper-resistant across its clinical life.

Tamper-evident, on-device logs capture inputs, model versions, and decisions with full context — evidence for design history files, audits, and post-market surveillance.

Push signed application and full-OS updates through controlled rollouts. Updates are atomic — a device is never left half-updated or bricked mid-shift.

Monitor every device across hospitals, clinics, and labs from one console: versions, health, and status in real time, without touching patient data.

Ambulances, rural clinics, and field hospitals rarely have reliable connectivity. Wendy devices run fully offline and sync state when a link returns.

Medical products live for a decade or more. First-class support for NVIDIA Jetson and Raspberry Pi class hardware keeps a validated stack stable for the long haul.