KenSci provides health systems and payers with a machine learning risk-prediction platform that identifies clinical, financial and operational risk. Its platform is built on Azure ML and SQL and ingests EMR, claims, billing, pharmacy, wearable and psychosocial data to uncover cost-saving opportunities. A library of pre-built models and modular solutions allows the platform to integrate into existing workflows. The company emphasizes Explainable AI models to make risk-based prediction more efficient and accountable. KenSci was incubated at the University of Washington’s Center for Data Science at UW Tacoma and also has offices in Singapore and Hyderabad. The company raised a Series B that brought total funding to $30.5M and intends to use proceeds to accelerate its product roadmap and global expansion. KenSci provides a healthcare data platform and machine learning-powered applications developed collaboratively with practicing physicians, data scientists, machine learning developers and biomedical researchers. The platform predicts clinical risk, financial risk and operational risk and is powered at cloud scale using Microsoft’s Azure and Cortana suite. The company was incubated at the University of Washington Tacoma and spun out in 2015 after more than four years of research and industry-academic collaboration. KenSci was previously part of Microsoft Accelerators’ Data Science program and maintains offices in Seattle, Dallas, Singapore and Hyderabad. Led by CEO and co-founder Samir Manjure, the company plans to use new funding to accelerate innovation on its machine learning platform and to expand operations. The article does not disclose operating metrics such as revenue or user counts.

Total raised

$31M

Funding rounds

2

Latest round

Series B

Latest activity

Feb 2019