Residents live freely.
Sensed, never seen.
Predicting patient deterioration and modeling sleep from behavioral data is the science underneath Ambient. As a University of Minnesota data scientist who has taken research to market and won federal funding, you have walked the exact path we are on. That is the guidance we are looking for.
It started with a problem everyone described the same way
The people closest to memory care kept saying it the same way. The staff caring for residents with dementia are chronically understaffed. The residents are continuously observed by no one. And the technology built to help has been either invasive, unreliable, or just another layer of paperwork.
The insight was simple. Memory care needs continuous, accurate, dignified observation. Not surveillance. Not gadgets. A system that watches the way a thoughtful caregiver would, knows what matters, and tells the right person at the right time.
Three areas we’d value your guidance
From pilot to a repeatable model
Sequence the path from a thirty-six unit pilot into a repeatable commercial contract. Your track record founding and running analytics companies is exactly the playbook we want to pressure-test.
A defensible portfolio
Shape the patent strategy around Ambient's sensing and prediction stack, and help navigate the University of Minnesota licensing path where the core IP already sits.
Non-dilutive capital
Position Ambient for NIH SBIR/STTR and translational grants, building on the clinical predictive-modeling research you have won funding for and led.
The next generation of technology for aging care
Contactless 24/7 monitoring
Ambient sensors detect movement without wearables and cameras. Residents move freely without privacy concerns. Dignity is preserved.
Ella AI Nurse Assistant
Ella AI synthesizes continuous sensor data into clinical insights, delivering instant notifications for events and storing longitudinal data for prediction.
Memory care and skilled nursing
Designed around the constraints memory care actually has. No cameras in rooms. No wearables on residents with dementia. No new burden on stretched staff.
A PCT international application is on file with the University of Minnesota, with additional patents in progress. Details of the expanding portfolio are shared under NDA.
Four core capabilities
Fall detection
Ella AI detects falls within seconds and alerts staff immediately, day or night, whether the resident is in bed, in a chair, or on their feet. No wearable required.
Sleep monitoring
Continuous overnight tracking of sleep quality, restlessness, and time in bed. Ella AI identifies deteriorating sleep patterns before they surface as behavioral symptoms.
Behavioral change detection
Ella AI tracks activity rhythms across days and weeks, flagging statistically significant changes that may indicate pain, infection, or cognitive decline.
Staff coordination
Alerts, daily summaries, and trend reports flow to the right staff at the right time, through the dashboard or mobile, with no extra documentation burden.
