Lily Vittayarukskul (shown above) was pursuing her aerospace engineering degree when her aunt was diagnosed with terminal colon cancer. Growing up, her aunt had been a key figure in Vittayarukskul’s life, raising her while living under the same roof. “We committed fully to her care,” she reflected.
Following chemotherapy, Vittayarukskul’s aunt “became quite frail,” which led her family—originally from Cambodia—to manage her daily long-term care requirements for nearly two and a half years. “It took a heavy toll on us financially,” she recounted to TechCrunch.
The emotional and financial strain was so severe that it led Vittayarukskul to shift her academic focus toward genetic and data science.
In December 2021, she launched Waterlily, a startup based in San Francisco that aims to assist individuals and advisors in navigating long-term care options by modeling associated costs and funding strategies. Vittayarukskul stated that the goal is to simplify the process for financial advisors and insurance agents “to recommend the appropriate financial products based on a family’s anticipated long-term care requirements.”
Vittayarukskul further explained, “People typically start considering long-term care plans around ages 65 to 70, or only when they actually need them.” However, this delay can often be detrimental.
Waterlily utilizes artificial intelligence to forecast a family’s potential long-term care needs and expenses, guiding them “in developing a care plan and identifying the optimal funding method,” Vittayarukskul shared with TechCrunch. “This might involve purchasing life insurance with a long-term care rider, securing a dedicated LTC policy, leveraging annuities, or simply using personal funds.”
Waterlily’s predictive AI can cater to anyone aged 40 and above.
The startup draws from over 500 million data points and employs machine learning algorithms through its AI modeling software to provide “highly tailored care and cost predictions,” projecting the “when,” “how,” and “how much” of an individual’s future long-term care needs.
“We hold formal data-sharing agreements with long-term care providers, government databases, academic research projects, and individual users”—including the Centers for Medicare & Medicaid Services and the Federal Long Term Care Insurance Program—“and we are in the process of establishing similar deals with insurance providers to securely access their anonymized data,” Vittayarukskul revealed.
Initially, Vittayarukskul embarked on her journey with Waterlily as a solo founder until she was joined by Evan Ehrenberg, a small angel investor. Ehrenberg, who previously founded and sold Clara Health, aided in the preliminary research and was impressed by the industry’s response. Intrigued, he tested the platform and was taken aback by the predictions regarding his long-term care needs—enough to alter his diet, hire a personal trainer, and update his financial strategies.
This experience drew him into the project further. He noticed similarities between long-term care and challenges he had faced in clinical trials. Clara Health facilitated tens of thousands of patients to find trials, but he discovered that many patients sought these trials not for innovative treatments, but for generic alternatives to brand-name medications that insurance wouldn’t cover. Long-term care presented a similar challenge—most health insurance plans do not cover it, leaving many unprepared for the financial ramifications, noted Vittayarukskul.
“After six months of collaboration, we recognized it was a perfect match and appointed him as a co-founder,” she noted.
Ehrenberg’s background is quite remarkable: he graduated from UC Berkeley at just 16 years old and later became MIT’s youngest PhD in neuroscience. He currently holds the position of chief operating officer at Waterlily.
Distinguishing in a Complex Landscape
While other tools exist for long-term planning, Vittayarukskul asserts that they differ significantly from Waterlily’s customized approach. For instance, Genworth’s cost of care calculator provides ZIP-code averages. Other platforms like NaviPlan, eMoney, MoneyGuidePro, and RightCapital serve as broader financial-planning tools, featuring basic long-term care modules or cost calculators among their various functions.
According to her, “While these tools aid advisors in modeling retirement and insurance scenarios, their long-term care assumptions often rely on national averages or Monte Carlo simulations to stress-test financial planning by introducing randomness into a basic simulation.” In contrast, Waterlily “integrates advanced predictive modeling with an intuitive platform.”
Waterlily publicly launched its platform in March 2024 and has yet to gather year-over-year metrics, but Vittayarukskul disclosed to TechCrunch that the startup’s monthly recurring revenue (MRR) is now over 22 times what it was in its inaugural month. Moreover, its average month-over-month MRR growth since launch has been 58%.
The company currently boasts eight prominent enterprise clients, including Prudential and several other Fortune 100 insurance providers. Additionally, hundreds of independent financial advisors and insurance agents utilize Waterlily, as per Vittayarukskul. The company’s revenue model operates on a SaaS basis, charging $250 per advisor or agent seat monthly.
Recently, the startup secured $7 million in seed funding, led by John Kim, founding partner of Brewer Lane Ventures, with strategic investments coming from Genworth, Nationwide, and Edward Jones. Prior to this, Waterlily had raised a $2.2 million pre-seed round from various investors, including Scott Barclay, managing director of healthcare at Insight Partners.
The fresh capital raised through a SAFE will be allocated towards expanding their engineering data science and enterprise management teams, while also enhancing their AI models and data partnerships. Furthermore, they aim to bolster their sales and marketing strategies.
At present, the startup has nine full-time employees in addition to a roster of contractors.
Looking forward, Waterlily is exploring areas such as disability, critical illness, hospital indemnity, and Medicare planning—or “any domain where advanced predictive modeling can aid families in making informed life and health coverage decisions,” commented Vittayarukskul.
The company has also attracted attention from insurance providers interested in leveraging its data for underwriting purposes. There are possibilities for international expansion, potentially including Canada, the U.K., and certain parts of Asia.
Investor Kim, a former president of New York Life, shared with TechCrunch that he invested in Waterlily due to his belief that it represents “the first AI-driven guidance tool to address a crucial need as Americans age.”
He added, “Long-term care insurance is an expanding necessity, largely overlooked by trusted advisors. Waterlily’s guidance tool is unmatched, providing tailored and personalized recommendations for long-term care needs. I am confident it will revolutionize the long-term care insurance sector.”
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