The startup has developed an in-cabin AI detection system that monitors driver health by identifying critical conditions such as seizures, strokes, and fatigue. This technology enhances road safety and fleet operations by reducing vehicle accidents among vulnerable populations.
Funding
$3.3M 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
Accurate and timely detection of health events like seizures, strokes, cardiac arrest, and fatigue is challenging, especially in environments like vehicles or healthcare facilities where continuous monitoring is not readily available. Delayed detection can lead to severe consequences, including accidents, injuries, and increased mortality rates.
Solution
Moment AI develops visual intelligence models that analyze human behavior to detect health events and abnormal conditions in real-time. Using computer vision and generative AI, the company's technology identifies subtle indicators of distress or medical emergencies through video feeds. The system can be integrated into existing camera systems in vehicles, homes, and healthcare settings to provide continuous monitoring. When an abnormal event is detected, the system can trigger alerts, initiate automated assistance, or notify caregivers, enabling rapid response and potentially preventing adverse outcomes. The platform aims to improve safety and well-being by providing a proactive approach to health monitoring.
Target Audience
The primary target audience includes automotive manufacturers, fleet operators, healthcare providers, and home healthcare services seeking to enhance safety and monitoring capabilities.
Features
- Real-time analysis of video feeds using proprietary visual intelligence models
- Detection of various health events, including seizures, strokes, cardiac arrest, and fatigue
- Integration with existing camera systems in vehicles, homes, and healthcare facilities
- Customizable alert thresholds and notification protocols
- Automated assistance features, such as initiating ADAS in vehicles
- Generative AI training to improve detection accuracy and expand the range of detectable events
- Human factors lab for clinical trials and data gathering to train its Large Vision Model (LVM)