Kepler Vision Technologies provides AI‑driven software that monitors patients in real time to detect falls and near‑fall situations, alerting caregivers within seconds.
Funding
$1.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Care facilities and hospitals often experience delayed response to patient falls or near‑fall situations due to limited staff availability, especially during night shifts, leading to increased injury risk and inefficient use of personnel.
Solution
Kepler Vision Technologies offers AI‑driven software that continuously monitors patients in real time and instantly identifies unsafe conditions such as a patient approaching the edge of a bed or an actual fall. The system processes video locally and anonymously, preserving privacy while eliminating the need for constant human observation. When a risk is detected, an alert is sent to caregivers within seconds, enabling rapid intervention. The software’s high precision reduces false alarms to roughly one per 92 days, minimizing unnecessary disruptions. By automating vigilance, the solution helps facilities maintain safety standards despite staffing shortages and supports more efficient allocation of caregiver time.
Target Audience
Primary customers are senior‑care facilities and hospitals that need reliable fall prevention and detection for residents and patients, particularly during overnight or understaffed periods.
Features
- Real‑time AI analysis of video streams to detect falls and near‑fall events with sub‑second latency
- Local, on‑device processing that ensures data never leaves the premises and remains anonymized
- Alert system that notifies nurses instantly via existing clinical communication channels
- Extremely low false‑alarm rate (≈1 false alarm per 92 days), reducing alarm fatigue
- Compatibility with standard camera hardware, requiring no specialized sensors
- Integration options for night‑shift workflows, allowing staff to intervene only when prompted