Femtech
Apparently, putting a man on the Moon was easier than properly understanding the female body. Okay, maybe that’s an exaggeration. But when women’s health has been unfunded for years, it’s worth asking why.
In the past, women have never been adequately represented in healthcare, leading to significant gaps in medical industry. Why are women being treated on a certain medication experimented on men? A survey of U.S. medical schools found that only 14% had implemented a women’s health curriculum, and just 10% had a program responsible for integrating sex-specific information across the curriculum. Shocking fact: Did you know that only 1% of global R&D went towards women’s health in 2020! Furthermore, the term FemTech was coined in 2016 Ida Tin, who is the founder of the period-tracking app Clue. Is FemTech simply making healthcare more convenient, or is it beginning to change the way we understand women’s bodies?
Hot take: Why talking about women’s health a taboo? Why the whispering behind closed doors? Surprisingly, half of earth’s populations health is a taboo!
Historically, women were often excluded or underrepresented in medical research. In the United States, the FDA only lifted its restriction on including women of childbearing potential in early clinical trials in 1993. Before this change, researchers often assumed that results from studies on men could simply be applied to women.
Simple definition of FemTech: technology designed specifically to address women’s health needs.
What actually counts as FemTech?
Now that we know vaguely what FemTech is, lets dive deeper. What does FemTech cover? FemTech covers many things, including but not limited to:
- Menstruation
- Fertility
- Pregnancy
- Menopause
- Contraception
- Sexual health
- Pelvic health
- Breast health
- Diagnostics
(the picture above aims to mention the different aspects of FemTech) (the image is from the following source: Your Ultimate Guide to FemTech: What is femtech & so much more!)
As of 2026, things are slowly changing as more people are finally learning about women bodies, and there are multiple companies that focus on different aspects, such as Flo ( menstrual/reproductive health), Clue (cycle tracking), and Elvie ( pelvic floor technology and breast pumps).
Cool fact! (and kind of obvious!): Around 70% of FemTech companies are founded or co-founded by women.
But FemTech is not just about creating an app that reminds someone when their period is coming. It can involve medical devices, wearables, software, diagnostics and technology that collects biological data. This is important because it means FemTech can potentially turn information about women’s bodies into something that can actually be studied and understood.
How is ai changing FemTech?
Now, lets understand how AI is used in apps to track things like menstrual cycle, reproductive and sexual health!
To be specific, we will focus on the app Flo!
Flo collects general data, like cycle duration, symptoms, lifestyle factors, fertility related logs, and general health.
Flo’s AI identifies patterns such as: “You usually experience headaches 2 days before your period.” Or “Your energy levels tend to be highest during the follicular phase.” Flo’s Health 360 module uses evidence-based algorithms to flag patterns associated with conditions like PCOS (e.g., irregular cycles + high BMI) So, what Flo’s AI can predict is Menstrual cycle length and next period, fertility, and health risk indicators.
However, AI can only predict, and Flo clearly says to always see a doctor for any concerns. The AI can’t diagnose!
But how does the technology actually work?
This is where FemTech becomes more interesting. An algorithm does not magically “know” when someone is going to ovulate. It needs biological information and patterns from that person’s data.
( the picture above represent the increase in body temperature during the ovulation phase-UNDERSTANDING THE INFLUENCE OF BMI AND POLYCYSTIC OVARY SYNDROME (PCOS) ON MENSTRUAL CYCLE AND OVULATION TRENDS — Fertility and Sterility)
This is significant because the technology is not simply counting 28 days and assuming everyone has the same cycle. It is using biological data to create an individualized prediction. Natural Cycles became FDA-cleared as a digital birth-control method in the United States in 2018. The company says its clinical evidence involved more than 15,000 women and 180,000 cycles. (Natural Cycles’ numbers come from the company itself.)
However, “FDA-cleared” does not mean 100 percent correct. Natural Cycles reports 93 percent effectiveness with typical use and 98% with perfect use. This difference is important because technology can work differently depending on how consistently and correctly it is used.
So, the important thing to understand is that AI in FemTech is not just about making guesses. It is about taking large amounts of biological information, finding patterns that may be difficult for a person to see themselves, and turning those patterns into useful information.
Why is this different from using a normal calendar?
A normal calendar isn’t personalized to your habits, lifestlye and environment, so even though a average cycle is 28 days, the AI can predict, for example, a cycle of 31 days!
If AI can recognize patterns in someone’s health that they might not notice themselves, could it eventually help detect health problems earlier?
That possibility is one of the most exciting parts of FemTech. Instead of waiting until someone becomes seriously ill before they seek help, technology can potentially notice unusual patterns and encourage women to speak to a healthcare professional earlier. However, there is an important difference between noticing a pattern and diagnosing a medical condition. An algorithm can say that something looks unusual, but a doctor still needs to investigate what that pattern actually means.
This also shows why the quality of the data matters. If an algorithm is trained on incomplete or biased information, its predictions can also be incomplete or biased. This is one of the biggest challenges facing AI in healthcare: technology can only be as good as the information it is trained on and the way that information is interpreted.
Is FemTech actually fixing healthcare for women?
There are the positives…. Then the negatives!
Positives:
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Women can learn more about their bodies
FemTech gives women access to information that they may not have learned about in school or even from healthcare professionals. Cycle-tracking apps, for example, can allow users to notice patterns in symptoms, cycle length and changes over time. Instead of seeing each symptom as a separate event, someone can look at their information over several months and find a pattern.
Health data can be collected continuously
Traditional healthcare usually gives doctors a general overview of someone’s health. A patient might visit a doctor once every few months, while an app or wearable can collect information more frequently. This could give healthcare professionals more information to work with, especially when symptoms change throughout a menstrual cycle.
Technology can predict certain results or outcomes
FemTech can use algorithms to make predictions about fertility, menstrual cycles and other health patterns. Natural Cycles is an example of technology that uses temperature data and an algorithm to estimate fertility status rather than relying only on a standard calendar.
Negatives:
Can an app replace a doctor-no
An app can provide information, but it cannot completely understand someone’s medical history, physically examine them or consider every possible explanation for a symptom. This is particularly important when an app identifies a possible health problem. A prediction should be treated as information to discuss with a healthcare professional, not as a diagnosis.
Can algorithms make mistakes-yes
Even advanced algorithms can produce incorrect predictions. For example, a fertility algorithm depends on the data it receives. If data is missing, unusual or entered incorrectly, the prediction may not be as useful. This is why effectiveness statistics often distinguish between “typical use” and “perfect use.” Natural Cycles, for example, reports different effectiveness rates for typical and perfect use.
Can health data be biased-yes
Another problem is that healthcare data has historically not always represented women equally. If certain groups of women are missing from datasets, an algorithm might work better for some users than others. This is not only a technology problem; it reflects the wider problem of gaps in women’s medical research.
What can happen to extremely sensitive reproductive data? Is an app selling our information.
This is where FemTech becomes much more complicated.
In 2021, the U.S. Federal Trade Commission (FTC) finalized a settlement with Flo Health after alleging that Flo had shared sensitive health information from millions of users with outside companies, including Facebook and Google, despite promising users that their health information would remain private. The FTC said that the information shared could include sensitive information such as a user’s pregnancy status.
This raises a serious question: Who actually owns your health data?
When someone enters information about their period, fertility, pregnancy or symptoms into an app, that information is much more personal than an ordinary search history. It can reveal extremely sensitive details about someone’s body and life.
The Flo case shows why privacy should not just be a small section hidden inside an app’s terms and conditions. Users should know exactly what information is collected, why it is collected, who can access it, and whether it is ever shared with another company.
In my opinion, FemTech companies should make privacy one of their main features, not an afterthought. Users should have clear choices about what data they provide and should not have to read pages of complicated legal language to understand what happens to their information. If FemTech is supposed to give women more control over their health, women should also have control over their health data.
Hot take(AGAIN!)- FemTech is revolutionary, but the fact that we need FemTech in the first place proves how much traditional healthcare has failed to understand women’s health. Because there certainly isn’t a term called Mentech!
Where could FemTech go next? What does the future look like?
AI and wearable technology are becoming more advanced. Women’s healthcare could shift from tracking symptoms to spotting patterns and possibly detecting problems earlier. Researchers are already looking at AI-integrated wearables that can gather data all the time and give more personalized health information.
Imagine a future where a wearable could continuously collect information such as temperature and other biological signals, while an algorithm looks for changes over time. Instead of a person having to manually remember every symptom, technology could create a much larger picture of their health.
However, this future also creates another problem: more data does not automatically mean better healthcare. If women are constantly collecting health information but doctors do not have the time, training or systems to interpret it, the technology may not actually close the health gap.
That means FemTech is not about smarter period trackers or better wearables. FemTech could become part of a larger shift, toward healthcare that understands women’s bodies more accurately.
But for that to happen, innovation cannot be the only goal. Researchers need better data, companies need stronger privacy protections, and healthcare professionals need to understand how to use the information these technologies produce. Otherwise, FemTech could simply create more data without actually creating better healthcare.
image
Finally, where does FemTech leave us?
FemTech is much more than period tracking, it is changing the way women receive care. This technology can help address gaps that has existed in women healthcare and medicine for years. FemTech isn’t proof that we’ve solved the women’s health gap. It’s proof that we’re finally admitting there was one.
Bibliopgraphy:
Unlocking opportunities in women’s healthcare | McKinsey
The Science Behind the Birth Control App | Natural Cycles
Flo Health, Inc. | Federal Trade Commission
Closing the women’s health gap | McKinsey
About Me
Hi! I’m Pragya Panchanathan, a student in Grade nine who loves learning about things that go beyond what we learn in school. I’m interested in psychology, business, technology, healthcare, and pretty much anything that makes me stop and think.
I especially enjoy researching random topics and discovering issues that people don’t always talk about. That curiosity is what led me to learn more about FemTech and the gaps that still exist in women’s healthcare.
I’m passionate about using writing and research to explore important topics and share what I learn with others. I believe that sometimes, starting a conversation about an overlooked issue can be the first step towards creating change.
