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GetWella

AI health app for women 40+

Health & Fitness
Artificial Intelligence
FemTech

Hunted byKhaled AliKhaled Ali

Most health apps were built for a 28-year-old. GetWella was built for the woman doing everything right and gaining weight anyway. We track sleep, stress, energy, and weight, then our AI explains the connections your body has been making for months. Why energy crashes. Why weight stalls. Why stress undoes a week of effort. No calorie counting. No judgment. No streaks. Free 14-day trial. No credit card required.

Top comment

Hi Product Hunt 👋 I'm the founder of GetWella. I built this after a close friend gained weight during perimenopause despite doing everything right. Every app made her feel like a failure. She didn't need another tracker; she needed someone to explain what was happening. So I assembled a team and spent months consulting doctors and professors at German universities to understand the hormonal science behind what women 40+ actually experience. The result is an AI that explains the WHY, not generic advice, but real pattern recognition built on real science. She lost 30kg. More importantly, she stopped feeling broken. Happy to answer any questions!

Comment highlights

How does the AI differentiate between weight changes caused by hormonal shifts versus diet and exercise patterns? Building specifically for women 40 plus is a thoughtful focus, congrats!

This resonates a lot. "Most health apps were built for a 28-year-old" spot on, and it goes way beyond fitness.

I'm building Olkano, a daily check-in for people living alone (many of them elderly). Same realization: the generic solutions just don't work for specific demographics. They're either overengineered or too broad to actually help.

I think apps like yours that go deep on a specific group instead of wide for everyone are where things are headed. Congrats on the launch

this is so smart - connecting stress to weight stalls is something most apps completely miss. curious how the AI actually identifies these patterns? are you looking at sleep quality metrics alongside the other data points, or is it more about timing correlations?