Gesund.ai provides CRO services for medical AI models, streamlining their clinical validation. Gesund.ai orchestrates the AI as-a-Medical Device lifecycle, bringing the AI algorithms to the diverse yet standardized medical data sources in a privacy-centered fashion. The unique analytical toolbox generates real-world evidence and fosters clinical validation, regulatory clearance and post-market surveillance.

Health systems use eCART to quickly and efficiently direct clinical resources toward their most critical patients and ensure timely and consistent care. Our sophisticated reporting and benchmarking further empower clinical leadership to understand and drive practice patterns. eCART draws upon readily available patient data from the EHR, rapidly quantifies disease severity, and predicts likelihood of critical illness onset, hours before it happens. Built upon more than a decade of ongoing scientific research, eCART was developed at the University of Chicago by Dr. Dana Edelson, MD, MS and Dr. Matthew Churpek, MD, PhD and is well chronicled in published literature. The analytic and workflow have been in use in clinical practice since 2016.

At AgileMD, we are building the most advanced real-time predictive analytics and clinical pathways platform for hospitals.

To date, AgileMD tools have been used on nearly 2.5 million patients by more than 80,000 providers in over 150 hospitals, including some of the nation's leading academic medical centers. AgileMD is backed by premier accelerators MATTER, YCombinator, and Rock Health, and our cutting-edge analytics are built on a decade of ongoing research at the University of Chicago. In 2021, AgileMD garnered nearly $3 million in combined federal research and development funding from the National Institutes of Health (NIH) and Health and Human Services (HHS) to further advance our platform.

• 10+ years of published academic literature on value over other early warning scores
• Analytics derived and validated in robust patient datasets 
• Built by clinicians for clinicians, with full cross-team workflow to ensure risk scores are understood and acted upon

• 8+ years in clinical use
• High sensitiviy and specificity, meaning fewer false alarms and more efficient focus on the highest risk patients
• Integrated workflow to ensure that risk scores are not ignored and action is taken
• Robust reporting and benchmarking to drive quality improvement
• Deep EHR-integration