Lily Vittayarukskul (pictured above) was studying aerospace engineering when her aunt was diagnosed with terminal colon cancer. Her aunt had lived under the same roof as Vittayarukskul while she was growing up and helped raise her. “We went all in on her care,” she recalled.
Post-chemotherapy, Vittayarukskul’s aunt “became very frail,” so her family — originally from Cambodia — navigated about two and half years of her daily long-term care needs. “It wiped us out financially,” she told TechCrunch.
The emotional and financial impact was so traumatic that it prompted Vittayarukskul to pivot her studies to genetic and data science.
Ultimately, she founded Waterlily, a now four-year-old, San Francisco startup aimed at helping individuals and advisors navigate long-term care options by modeling costs and funding strategies. Its goal, according to Vittayarukskul, is to make it easier for financial advisors and insurance agents “to recommend the right financial products based on a family’s predicted long-term care needs.”
Explained Vittayarukskul, “Usually individuals start to think about long-term care when they’re between the ages of 65 and 70, or just when they need it.” But in many cases, that can be too late.
Waterlily uses artificial intelligence to predict a family’s future long-term care needs and costs and then guides them “in building a care plan and figuring out the right way to pay for it,” Vittayarukskul told TechCrunch. “That might mean buying life insurance with a long-term care rider, purchasing a dedicated LTC policy, using annuities, or simply self-funding.”
Waterlily’s predictive AI can be used for any individual over 40.
The company pulls from more than 500 million data points and machine learning algorithms using its AI modeling software in an effort “to make highly personalized care and cost predictions” and forecast the “when,” “how,” and “how much” of someone’s potential long-term care needs.
“We have formal data-sharing agreements with long-term care providers, government databases, academic research studies, and individual users” — these include the Centers for Medicare & Medicaid Services and the Federal Long Term Care Insurance Program — and we’re finalizing similar contracts with insurance carriers to securely ingest their anonymized data,” Vittayarukskul said.
Vittayarukskul initially started Waterlily as a solo founder until Evan Ehrenberg, a small angel investor, came along. Ehrenberg — who had previously founded and sold Clara Health — helped with early research, and was struck by the industry’s response. Curious, he tested the platform himself and was shocked by his long-term care predictions — so much so that he changed his diet, hired a personal trainer, and updated his financial plans.
That experience pulled him in deeper. He saw parallels between long-term care and issues he’d encountered in clinical trials. Clara Health had helped tens of thousands of patients find trials, but he also saw how many turned to them not for cutting-edge treatments, but for generic copycats of existing drugs because insurance wouldn’t cover the name-brand drugs they needed. Long-term care brought a similar realization — health insurance doesn’t cover it, and many are unprepared for the financial burden, noted Vittayarukskul.
“After six months of working together, we knew it was a great fit and made him a co-founder,” she said.
Ehrenberg’s own backstory is interesting: After graduating from UC Berkeley at 16, he became MIT’s youngest neuroscience PhD. Today, he also serves as Waterlily’s chief operating officer.
Standing out in a complicated space
Other tools exist that help with long-term planning, but Vittayarukskul believes they differ from Waterlily’s more personalized offering. Genworth’s cost of care calculator, for example, shows ZIP-code averages. NaviPlan, eMoney, MoneyGuidePro, and RightCapital are broader financial-planning platforms that include basic long-term care modules or cost calculators as one of their multiple functions.
According to her, “While these tools help advisors model retirement and insurance scenarios, their LTC assumptions are typically driven by national averages or Monte Carlo simulations in order to stress-test financial planning by introducing noise into a basic default simulation.” Waterlily, by contrast, “blends deep predictive modeling with an easy-to-use platform.”
Waterlily only launched its platform publicly in March of 2024 so it doesn’t have year-over-year metrics yet, but Vittayarukskul told TechCrunch the startup’s monthly recurring revenue (MRR) today is greater than 22x what it was after its first month in the market. And, she said, its average month-over-month MRR growth since its launch has been 58%.
The company currently has eight “major” enterprise customers, including Prudential and “several other Fortune 100 insurance carriers.” There are also hundreds of independent financial advisors and insurance agents who use Waterlily, according to Vittayarukskul. Its revenue model is SaaS-based, with the company charging $250 per advisor or agent seat per month.
And now the startup has raised $7 million in seed funding led by John Kim, founding partner of Brewer Lane Ventures, with strategic investments from Genworth, Nationwide, and Edward Jones. The startup previously raised a $2.2 million pre-seed round from investors including Scott Barclay, managing director of healthcare at Insight Partners.
Waterlily plans to use its new capital, which was raised via a SAFE, to build out its engineering data science and enterprise management teams, as well as to continue strengthening its AI models and data partnerships. It also plans to increase its sales and marketing efforts.
Presently, the startup has nine full-time employees in addition to contractors.
Looking ahead, Waterlily is looking at disability, critical illness, hospital indemnity and Medicare planning, or “really any area where advanced predictive modeling would help families make better life and health coverage decisions,” Vittayarukskul said.
The company says it is also receiving interest from insurance carriers that want to use its data in underwriting. It potentially might expand internationally as well to Canada, the U.K., and parts of Asia.
Investor Kim, who is also former president of New York Life, told TechCrunch that he put money into Waterlily because he believes it is “the first AI-native guidance tool to assist in the single largest need as Americans age.”
He added: “LTC insurance is a large and growing need, and largely underserved by trusted advisors today. Waterlily’s guidance tool has no comparable offering. It provides a customized and personalized recommendation for one’s LTC needs. I believe it will be a game changer for the LTC insurance marketplace.”
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