Kintsugi Voice is an API-first platform, we are developing novel voice biomarker infrastructure to detect signs of clinical depression and anxiety from short clips of free form speech. We help healthcare organizations scale access to mental healthcare with smarter, more accurate triage. Our technology supports multiple use-cases to help more people get the right care at the right time.  We focus on early detection that allows you to lower cost and improve patient outcomes. We have created the first clinical-grade voice biomarker diagnostic (U.S. Patent-Pending and FDA De Novo pending) to measure the severity of depression and anxiety in real-time.

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.

1. Kintsugi Voice only needs 20 seconds of free from speech vs. a manual screen that takes roughly 10 minutes.
2. Kintsugi Voice is language agnostic and does not listen to what a patient is saying, but how they are saying it.
3. Kintsugi has the largest annotated patient data model, validated by a psychiatrist team with more than 7 years experience. This allows us to predict depression and anxiety with high specificity and severity, based off of PHQ-9 standards.
4. Kintsugi Voice’s flexible API enables hundreds of workflows from retrospective to live in-call scoring. Typical depression screenings are typically delivered 1 time and not longitudinal. We provide the ability to longitudinally track patients across a period of time.

1. We are not a NLP tool, we do not need any canned speech and or paragraph read to detect depression and or anxiety.
2. We have the largest annotated data model in the world with over 35k patients.
3. We are supporting over 1M at risk lives.
4. 2X accuracy rating compared to the standard of care.

• 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