By Evelyn Nguyen, January 2024.
Despite post-pandemic inactivity, the healthcare startup world is heating up—with a smaller yet more quality pool of innovative early-stage companies. Whether that is Aiolos Bio’s asthma drug or Hippocratic AI’s LLM aimed at explaining healthcare use cases like dietary advice and medication reminders, healthcare technology is the future.
This has compelled me to seek out and screen HealthTechs for our venture partner, focusing on software & AI data labeling last December. Our Moso Deal Team led by Nae Nae Chairatchaneeboon (MD) is proud to share that we have sourced and conducted diligence on Elythea, resulting in an investment by our venture partner in the startup’s $1.5M seed round.
Backed by Y-Accelerator, Kleiner Perkins Fairchild Fund, Johnson and Johnson Impact Ventures, MIT Solve. An impressive strategic investor roster. However, Elythea’s value was beyond these backers: I knew that Elythea was special as I hopped on my first call with Reetam Ganguli, Elythea’s founder. Passionate, talented, and cautious: three words to describe him. Reetam was accepted into Brown’s accelerated medical school program at 17. His research emphasized developing ML/DL models to detect hard-to-predict outcomes in women's health—from recurrent cancer to postoperative mortality. Prior to Elythea, he founded a global biology education company with 10,000+ students in 30+ countries and consultative status with the UN.
But it’s not just the talent that drew us to Elythea. Like our partnering investor, we believed that Reetam was truly building a generational company.
In 2021, pregnancy complications occurred in over 40% of pregnancies. According to the CDC, 80% of related deaths were preventable, and 2 in 3 complications could’ve been avoided with earlier identification and intervention. From my OBGYN shadowing in Vietnam, I knew that traditional diagnostic solutions are limited—clinician judgement varies, scoring systems are outdated, and diagnostic tests are often only usable after the second trimester.
With Elythea’s ML technology, doctors can predict complications like postpartum hemorrhage, eclampsia, and preterm labor from the very first visit—using just basic demographic and socioeconomic data. Their model is trained on over 14 million patient records.
Beyond the $1.3B pregnancy complications market, Elythea is targeting the $110B global chronic disease space—including cardiology, oncology, and diabetes. Their predictive models are already being piloted outside the U.S., including in Nigeria and Cameroon—demonstrating that the tech isn’t overfit to U.S. data and can generalize globally.
We’re excited to have facilitated this investment between our partnering angel and this generational startup. Can’t wait to see what the future holds for Elythea and Reetam!