KenSci lands $8.5M to boost its data platform, grow business

By Bernie Monegain
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Seattle-based KenSci has raised $8.5 million in its first round of funding. It plans to use the capital to further develop its data and machine learning platform and expand its operations.

The company, which was incubated at the University of Washington in Tacoma, boasts a rapidly growing customer base. KenSci spun out in 2015 after more than four years of research and industry-academic collaboration.

KenSci's healthcare data platform and machine learning-powered applications are built collaboratively with practicing physicians, data scientists, machine learning developers and computing and biomedical researchers.

"The challenge in healthcare analytics is not in the lack of data but in the ability to connect and combine data meaningfully to unearth patterns and predict risks, Samir Manjure, CEO and co-founder of KenSci, said in a statement.

As Manjure sees it, legacy systems have created "walled gardens," unwittingly causing poor health outcomes and increasing healthcare costs.

"We are engineering a system of insight, on top of these legacy systems, to help enable our customers to predict and intervene ahead of time rather than drive looking backward, Manjure added.

KenSci technology is engineered to predict clinical risk, financial risk and operational risk, enabling health systems to transition to value-based care.KenSci's platform is engineered to ingest, transform and integrate healthcare data across clinical, claims, and patient generated sources. A library of more than 150 prebuilt models and modular solutions for clinical and operational risk prediction enable customers to ask and answer harder questions faster, with average deployment taking 10 weeks and ROI visibility in 90 days, according to Manjure.

The company employs Microsoft's Azure and Cortana suite to power secure, cloud-scale machine learning.Ignition Partners led this first round of funding, with participation from Osage University Partners and Mindset Ventures.