Sensi AI

Audio event detection and classification is the product. The pods are microphones; everything of value is the model interpreting verbal and non verbal sound into more than 100 reported care insights. Without the model there is a speaker in a room.

The system detects and alerts a human care team for review rather than acting, which is the appropriate ceiling for in home monitoring. Held back from A because the Growth and Ops Agents operate on a different footing, handling inbound demand and caregiver scheduling with no disclosed escalation criteria, and because alert thresholds and false positive rates for clinical detections are unpublished. Alert fatigue is the primary failure mode for continuous monitoring, and the broader the detection set the more that matters.

Adoption is the strongest signal: the company reports serving 80 percent of the largest home care networks in North America and revenue tripling year over year for three consecutive years, which for a subscription product implies genuine renewal rather than pilot churn. Agency reported operational results include client base and billable hour growth. Held back from A because no clinical validation study was retrieved, and detection claims for conditions like urinary tract infection and pneumonia from audio signal are exactly the sort that warrant published sensitivity and specificity rather than testimonial.

The sensing choice was made on privacy grounds and the founder says so directly: audio rather than cameras, because cameras feel intrusive in a private home. That places it between the two other approaches in this lane, less invasive than SafelyYou video capture and arguably more so than Inspiren skeletal imaging, since always on audio in a residence captures conversation including visitors and family who never consented. Held back from A because retention terms, on device versus cloud processing, consent handling for third parties present in the home, and whether recordings are stored or only inferences were not disclosed in retrieved materials. For continuous in home audio those are the decisive questions.

No rate card, but the model is disclosed: subscription pricing to home care agencies covering audio hardware and the software together. Agencies are the buyer rather than families, which is the relevant scoping fact. A buyer can understand the structure without a sales call, though not the amount.

Detection scope is materially broader than the fall detection that defines this category, and specifically enumerated: alongside falls, the system reports flagging possible urinary tract infections, pneumonia, early signs of cognitive decline, and softer signals including changes in activity level, sentiment, and lack of companionship. A clinical team spanning social work, occupational therapy, nursing, and geriatrics develops new data points on an ongoing basis, which is how the insight set stays clinically grounded rather than drifting toward whatever audio happens to be classifiable.