Cloudphysician provides AI‑powered computer vision and ambient intelligence platforms that continuously monitor patients in inpatient settings using existing video infrastructure. The system detects falls, pressure ulcers, infection risks, and readmission indicators in real time, sending instant alerts to staff to enable proactive care while reducing workload and complying with HIPAA standards.
Funding
$10.5M 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.
1OFounders
Product
Problem
Inpatient units often rely on manual observation to detect falls, pressure ulcers, infections, and other adverse events, leading to delayed interventions, increased patient harm, and higher healthcare costs.
Solution
Cloudphysician delivers AI-powered computer vision and ambient intelligence platforms that continuously monitor patients in real time using existing video infrastructure. The system analyzes multimodal video data to identify early signs of falls, pressure injuries, central line infections, catheter-associated urinary tract infections, and risk of readmission. Detected events trigger instant alerts to clinical staff, enabling proactive care and reducing workload. All data processing complies with HIPAA standards and can be deployed on-premise or in the cloud, integrating with hospital workflows without requiring new hardware.
Target Audience
Primary customers are hospitals and health systems operating inpatient wards, intensive care units, and long‑term care facilities that need automated patient safety monitoring.
Features
- AI-driven video analytics that detect patient falls, pressure ulcer formation, and infection risk in real time
- HIPAA‑compliant, scalable data pipelines for secure multimodal video processing
- Hardware‑agnostic deployment that works with existing hospital camera systems, on‑premise or cloud‑based
- Integration tools to embed alerts into existing clinical workflows and EHR systems
- Proprietary, clinically annotated inpatient video dataset that enhances model accuracy across diverse patient populations