Services · Pillar D
On-device perception for homes, clinics, and wellness programs—attention, posture, gait, and safety signals processed at the edge so video never needs to leave the room.
Quantized pose, depth, and activity models on NPU/GPU-class edge hardware—local inference loops with optional encrypted telemetry summaries instead of raw frame upload. Designed for privacy-sensitive elder care, pediatrics, and telehealth follow-up.
Webcam-driven attention and posture tracking for structured learning sessions—gentle nudges when focus drifts or ergonomics slip, with session-level analytics for caregivers and clinicians without storing continuous video in the cloud.
Edge-AI fall detection and gait analysis in living spaces—event-triggered alerts, stride variability trends, and recovery posture checks with on-device processing so resident footage stays local by default.
Real-time joint angle monitoring via MediaPipe-class landmark pipelines—form correction, hold timers, and ROM progressions for preventive musculoskeletal programs in clinic or at-home wellness.
Diagnostic System
Step 1 — Select the constraint blocking your OR or R&D pipeline.