Lily Vittayaruksku's personal experience with her aunt's terminal colon cancer diagnosis led her to pivot her studies from aerospace engineering to genetic and data science. This traumatic event sparked a mission to create a solution to help individuals and advisors navigate long-term care options and costs. The result is Waterlily, a four-year-old San Francisco startup that has just raised $7 million in seed funding to further develop its AI-powered platform.
Waterlily's platform uses artificial intelligence to predict a family's future long-term care needs and costs, guiding them in building a care plan and determining the right way to pay for it. The company's predictive AI can be used for any individual over 40, and it pulls from over 500 million data points and machine learning algorithms to make highly personalized care and cost predictions.
The startup's founder, Lily Vittayaruksku, initially started Waterlily as a solo founder until Evan Ehrenberg, a small angel investor, came on board. Ehrenberg, who had previously founded and sold Clara Health, was struck by the industry's response to Waterlily's platform and eventually became a co-founder. His own backstory is impressive, having graduated from UC Berkeley at 16 and becoming MIT's youngest neuroscience Ph.D.
Waterlily's platform stands out in a complicated space, offering a more personalized approach than existing tools. While other tools exist that help with long-term planning, they often rely on national averages or Monte Carlo simulations, whereas Waterlily blends deep predictive modeling with an easy-to-use platform.
The startup has seen significant growth since its public launch in March 2024, with its monthly recurring revenue (MRR) today being greater than 22x what it was after its first month in the market. Its average month-over-month MRR growth since its launch has been 58%. Waterlily currently has eight major enterprise customers, including Prudential and several other Fortune 100 insurance carriers, as well as hundreds of independent financial advisors and insurance agents who use its platform.
The company's revenue model is SaaS-based, charging $250 per advisor or agent seat per month. With its new capital, Waterlily plans to build out its engineering, data science, and enterprise management teams, as well as continue strengthening its AI models and data partnerships. It also plans to increase its sales and marketing efforts.
Looking ahead, Waterlily is exploring expansion into disability, critical illness, hospital indemnity, and Medicare planning, or any area where advanced predictive modeling would help families make better life and health coverage decisions. The company is also receiving interest from insurance carriers that want to use its data in underwriting, and it may expand internationally to Canada, the UK, and parts of Asia.
Investor John Kim, former president of New York Life, believes that Waterlily is "the first AI native guidance tool to assist in the single largest need as Americans age." He adds that Waterlily's guidance tool has no comparable offering, providing a customized and personalized recommendation for one's LTC needs. Kim believes that Waterlily will be a game changer for the LTC insurance marketplace.