Health care is expensive. In 2017, costs totaled $3.5 trillion in the U.S. alone, equal to 17.9 percent of the country’s gross domestic product. Driving the bulk of the receipts were chronic conditions like heart disease and diabetes — almost half of all Americans have at least one. And the sickest among the sufferers — about 5 percent of the population — consume 50 percent of total health care costs.

KenSci’s mission is to reduce those costs with artificial intelligence (AI). The Seattle-based startup, which has offices in Singapore and Hyderabad, was founded in 2014 by a team of researchers at the University of Washington Tacoma and incubated at the college’s Center for Data Science. (Two longtime friends — University of Washington Tacoma professor Ankur Teredesai and former Microsoft executive Samir Manjure — made up the inaugural executive team.) KenSci’s AI-driven prediction platform helps practitioners cut costs intelligently by identifying contributing clinical and financial factors and by analyzing data across sources like electronic medical records, public records, demographics, claims data, and devices.

KenSci today announced that it has secured $22 million in series B financing led by Polaris Partners, with participation from Ignition Partners, Osage University Partners, Mindset Ventures, and new strategic investor UL Ventures. This comes a little over a year after the startup’s $8.5 million series A and brings its total raised to $30.5 million.

The new capital will be used to “aggressively” explore new markets and accelerate KenSci’s product roadmap, said Manjure, who serves as CEO. “In the last two years, we’ve singularly invested ourselves in building a platform that simplifies the way health systems look at their data and gain actionable, predictive insights to save lives and costs,” he added. “[We’re] committed to … driv[ing] this transformation across the care continuum.”


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Above: KenSci’s prediction platform.

Image Credit: KenSci

KenSci provides a library of more than 150 prebuilt models that allow its clients to integrate the company’s platform into existing visualization and reporting workflows. To ensure a baseline-beating level of accuracy, the models are trained on two years of data from customers’ patient populations and used to make predictions for a third year. These predictions are validated against the actual outcomes for that year. The system takes into account hundreds of variables for each patient to forecast health risks stemming from conditions like sepsis, cancer, and heart attacks, with the goal of minimizing hospital readmission, over-use of emergency room services, and other pain points.

“KenSci has rapidly scaled to become one of the leading names in health care AI in a fast-growing market,” said Brian Chee, partner at Polaris Partners. “What KenSci has accomplished in the last three years is extremely exciting, and we’re thrilled to partner with them and work toward their mission to help health care organization truly realize the potential of AI.”

The company isn’t a fly-by-night operation. It has 25 peer-reviewed papers to its name — published over the course of seven years — and has attracted funding from Microsoft’s Azure4Research grant program. Moreover, last year KenSci was recognized as winner of Microsoft’s Health Innovation Awards for the best use of AI and machine learning.

To be fair, it faces stiff competition from the likes of Health Catalyst and others. But it’s gaining market traction — more than 11 health systems currently use its tools to predict risk for 27 million patients, including NHS Scotland and Health Promotion Board Singapore.

KenSci recently bolstered its executive ranks with hires from Oracle, Tableau, Amazon Web Services, and Cerner, and it says it has doubled in size in the past year.

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