Mount Sinai Deploys Clarium Computer Vision System Across 8 Surgical Sites

Mount Sinai Health System is deploying Clarium's computer vision-enabled supply management platform across eight hospitals and ambulatory surgery centers, expanding its use of artificial intelligence in operational workflows inside operating rooms.

The deployment will introduce Clarium Vision, a system that combines in-room cameras with AI models to automatically capture surgical supply usage during procedures. The platform is designed to improve documentation accuracy, reduce manual work for nursing staff, and provide more detailed supply utilization data for purchasing and inventory decisions.

The New York-based health system performs about 100,000 surgical procedures annually in its main operating rooms, according to the announcement. Clarium said the deployment supports Mount Sinai's efforts to reduce unwarranted clinical variation, improve operational performance, and modernize perioperative operations through workflow automation and better data collection.

Focus on Surgical Supply Data

Operating rooms are among the most resource-intensive areas of a hospital, requiring large volumes of supplies, implants, instruments, and disposable products. Manual documentation of those items remains common across many health systems.

According to Clarium, U.S. hospitals waste an estimated $25.7 billion annually on unnecessary supply chain spending driven by fragmented data, manual processes, and outdated governance practices. Supply chain spending is typically one of the largest expense categories for hospitals after labor.

Mount Sinai said the system will automatically record supply usage at the point of care and validate products against centralized supply databases. The platform can also identify expired or recalled products, according to the company.

"The goals are to improve safety, reduce work burden, better ensure supplies are available when needed, and to reduce waste," Dr. Amanda Rhee, System Vice President, Perioperative and Procedural Services at Mount Sinai Health System, said in a statement.

The deployment builds on Mount Sinai's broader efforts to apply AI and analytics to supply chain operations, including work focused on identifying hidden procurement costs and operational inefficiencies.

Part of a Broader Operational AI Push

The partnership centers on preference card optimization, a process hospitals use to standardize supplies and equipment associated with specific surgical procedures. Inaccurate or outdated preference cards can contribute to excess inventory, unnecessary purchasing, and workflow inefficiencies.

Clarium said Mount Sinai selected the platform because of its ability to support complex multi-hospital operations, automate workflow execution, and provide computer vision-based inventory management capabilities.

"Mount Sinai's approach reflects a deep alignment between mission, clinical leadership, and operational discipline," Steve Liou, CEO of Clarium Health, said in a statement.

The company said Mount Sinai will evaluate the deployment based on measures including waste reduction, preference card accuracy, staff engagement, reduced documentation time, and improved clinical supply revenue capture.

The announcement comes as healthcare organizations increasingly expand AI projects beyond clinical applications and into operational functions such as supply chain management, financial workflows, inventory control, and workforce efficiency. Similar efforts have emerged across the industry as providers seek measurable returns from AI investments while managing rising costs and staffing pressures.

Recent healthcare deployments have included AI systems for operational performance measurement, financial management, and workflow automation.

Founded in 2020, Clarium said it works with more than 20 health systems representing nearly 30% of U.S. healthcare supply chain spending. The company has raised more than $43 million from investors including General Catalyst, Northzone, AlleyCorp, Kaiser Permanente Ventures, and the Texas Medical Center Venture Fund.