For most people considering in vitro fertilization, the hardest number to find is the one that matters most: what are my chances? Clinics have long answered with age - a woman's birth year standing in for her biology. Univfy, a health-AI company based in Los Altos, California, was built on the finding that age alone explains only about half of the variation in whether IVF ends in a live birth. The rest, the company argues, is hiding in data that machine learning can read.
Founded in 2009 by Dr. Mylene Yao, a board-certified OB/GYN and reproductive endocrinologist, and Prof. Wing H. Wong, a Stanford statistician elected to the US National Academy of Sciences, Univfy analyzes an individual's full fertility profile - age, BMI, Day 3 FSH, AMH, semen analysis, and reproductive history - against thousands of real IVF cycles. The output is a personalized probability of having a baby, delivered before a patient decides whether to begin treatment.
The company's core claim is not that it predicts better in the abstract, but that it predicts better for a given clinic. Univfy builds center-specific models, on the logic that a fertility center's patient population rarely matches the national average.
"Univfy makes IVF success and costs more predictable so you can make confident decisions about your treatment."
- Univfy, company mission
