WILD.AI Gives Women a Way to Train With Their Menstrual Cycle

April 12, 2021 by
Credit: Courtesy of WILD.AI
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Signing up for WILD.AI starts the same as any other fitness app: you make an account, add your email, then input age and weight. But instead of the presumed follow-up tackling weight or fitness goals, the app’s next question asks about life stage. Are you menopausal? Pregnant? Prone to irregular cycles? 

The big picture: WILD.AI applies the science of female physiology to athletes. It’s designed to help women train, recover, and eat based on their menstrual cycle. 

How it works: Following the initial “life stage” question, preliminary inquiries from WILD.AI include the last day of your most recent period, the average time between cycles, and an estimation of emotional state in the days leading up to the first day of menstruation.

  • This creates base data for the app, which will then learn and adapt based on a mix of objective and subjective information input by the user. 
  • But even without the other data, when you open the app for the first time, WILD.AI gives advice for training, nutrition, recovery, supplement need, and mental state based on current cycle status. 

Objective data: WILD.AI integrates with trackers, like Strava and Garmin, to gain real-time workout data. 

  • Connecting a wearable gives the app information on sleep patterns, recovery, and activity, says founder and CEO of WILD.AI Hélène Guillaume, who has a background in data science.

Subjective data: Daily, users are asked to complete check-ins. This manual input includes, “how well you slept, how stressed you are, how you trained, your eagerness to train, your pains, where are your pains located, and things like that,” Guillaume says. 

  • These check-ins come in the morning, evening, after training sessions, during menstrual cycles, and more, measuring things like energy levels, exertion, quality of sleep, and hydration. 
Credit: Courtesy of WILD.AI

Recommendations: “Together, these objective and subjective data sets… you start seeing patterns in your symptoms and your behaviors, and then [WILD.AI] provides you with recommendations on how to mitigate those symptoms to occupy the positives,” Guillaume says. 

  • Recommendations vary from training intensity to optimizing nutrition to sex drive.
  • For example: if you’re in the follicular phase, immunity against pathogens is higher, meaning you’re better suited to handle exercise-induced strain. In this phase, the app – with a caveat saying “if your period does not negatively impact you” – advises adjusting to a higher intensity or volume of training. 
  • Training can be input manually or based on an integrated plan. Once added to the app, it will give recommendations on what to eat before and after, with science-based, cited information to back it up.  
  • “As a woman, it’s more… the timing of when you eat your proteins after your training, in particular, the… 45-minute window to replenish muscles. If you add your CrossFit training to your wearable – you put it on Strava – it goes automatically in the [WILD.AI] and we basically take that directly to recommendations of nutrition,” Guillaume explains. 

Once used long enough, WILD.AI can identify, predict, and reduce symptoms of the menstrual cycle. The app shows graphs to measure the potential for mood swings or anxiety, the need for certain vitamins, ways to ease the body out of pain, and more. 

The bottom line: Guillaume, a longtime athlete who now runs triathlons, says that in the sports world, there is lots of data on training. 

  • But, Guillaume continues, she “realized there was very little about the female body in particular.” 

WILD.AI is changing this. The app offers women access to data about their bodies, giving them ways to learn about and respond to their menstrual cycle. This provides female athletes with the knowledge to discover patterns and optimize body needs, leading to better training.  

  •  Women love it,” Guillaume says. “They’re seeing a massive improvement in their performance or the way that they feel.”

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