Radically Advance Female Health by Building the Largest Record of Female Datasets

Hélène Guillaume Pabis is the founder and CEO of Wild.AI, (an app) redesigning the essence of female health by helping women train, fuel and recover based on their menstrual cycle. The company also provides that knowledge to third parties (Oura Ring, Apple Health, etc.) through an API.

Now based in Portugal and working between the UK and US, the entrepreneur grew up in Belgium, Hong Kong, Japan and Peru. She has a master’s in Finance and Financial Risk Management, was a quant in a hedge fund and a management consultant to Fortune 500 companies optimising internal risk models using AI. Just as important, Pabis is an ultra-marathon runner, triathlete, surfer, skier and ice-swimmer. Yet, for the longest time, she had little knowledge about her own physiology. “I was training and eating like a man,” she recalls. “Women understand cars more than their own bodies.”

So now, Pabis wants to get rid of the sex bias in neuroscience and biomedical research. She wants to radically advance female health by building the largest record of female datasets – across all ages, life stages and ethnicities – and help women truly understand their bodies. Through research and algorithms, Wild.AI can not only predict when a woman will experience bloating or menstrual pain, but also advise how to alleviate these symptoms.