"The Algorithm Will See You Now": AI's Role in the Next Era of FemTech

A Market Long Overlooked

For decades, women's health has drawn far less attention than its scale of need suggests. In the U.S., women were only required to be included in clinical trials beginning in 1993, leaving large gaps in how diagnostics, dosage guidelines, and treatments have been designed. The investment landscape mirrors that disparity: in 2024, women's health startups raised approximately $2.6 billion in venture capital. (Silicon Valley Bank) Yet that represents a modest share of overall health-tech investment. Meanwhile, investment in women's health surged by 55% that same year. (Silicon Valley Bank)

Beyond finance, analysts suggest that closing the women's health gap could unlock massive social and economic value. Addressing persistent gender-based health inequities is estimated to add at least $1 trillion annually to the global economy by 2040. (McKinsey & Company)

Making Sense of Hormone Data

Dr Amy Beckley, founder of Proov, arrived in FemTech after her own struggle with infertility and recurrent miscarriage. "I thought being a scientist would make it easy for me to understand my body," she said. "Instead I discovered how broken the system was." Her product uses urine-based hormone testing across the menstrual cycle instead of a single snapshot. AI models absorb millions of data points, detect trends or deviations, and translate them into insight. "We're building something that's never existed before," she explained. "We need AI to uncover patterns and make them clinically relevant."

By converting raw fluctuations into interpretable trajectories, Proov shifts the diagnostic frame: women and clinicians can chart hormone health over time rather than interpret isolated drops or spikes.

Imaging at Finer Resolution

Endometriosis affects an estimated one in ten women, yet many women wait years for a diagnosis. Traditional imaging often misses the lesions responsible.

Dr Hadas Ziso's startup, EndoCure, integrates robotics and AI to push ultrasound into new territory. "We want to detect lesions as small as one millimetre," she said. "If I asked a radiologist to look for that across thousands of images, they'd walk out of the room." Her system refines imaging parameters, captures volumetric scans, and highlights suspect tissues via machine learning before radiologist review. While her immediate focus is gynaecology, Ziso envisions the same method applying to other domains—including prostate, kidney, or bladder imaging.

Biosensors, Pleasure, and Taboo

Innovation in women's health is emerging in less obvious domains. Isabella Sanda-Lewin, a biomedical engineer based in the NHS, is building Splash, a diagnostic tool for vaginal infections such as UTIs, thrush, and bacterial vaginosis. She also experiments with a biosensor-enabled vibrator. "We're measuring things like heart rate, muscle tension, and blood flow," she said. "AI then looks for patterns that might connect to pleasure responses. It's still early work, but it's a way to help women understand their own bodies."

Sanda-Lewin's investor conversations reflect deeper biases. "They love the technology," she said, "but they often ask me to frame it differently. It shows how much stigma still shapes women's health innovation."

Privacy, Regulation, and Trust

As technology continues to deepen its reach into intimate health, data practices and governance become increasingly consequential. Period- and fertility-tracking apps have already come under scrutiny for weak privacy policies and unintentional exposure of personal data.

Beckley tries to shift the paradigm: "It's her data," she said. "She can delete it, she can keep it, or she can choose to share it. If we ask to use it for research, we pay her." From an engineering perspective, trust is not a cosmetic aspect. Nick Solly, CTO of MOHARA, emphasized that "transparency, explainability, and consent need to be built into the product from the start." Many FemTech systems will fall under regulations like the EU AI Act, which demand disclosure of AI use, risk assessments, and user safeguards—even when operating outside Europe. (European Union)

Funding and the Road to Scale

Although women's health is drawing more capital, founders still verify through grants and non-dilutive support. Ziso credited early-stage grants from Israel's Innovation Authority for allowing EndoCure to fund preclinical proof-of-concept work. "Without that support, we would not have been able to start," she noted. Beckley likewise praised state-level commercialization grants she accessed in Colorado.

Larger players have taken note: companies like CVS and Amazon have entered or acquired in this space. Analysts forecast continued demand for women's health products. Yet until venture capital consistently recognizes their potential, many deep-tech founders will depend on mixed financing paths and carefully staged roadmaps.

Where AI May Take FemTech

Hormone testing that once required specialist clinics can now be done at home and interpreted in real time. Imaging tools may soon detect conditions that previously escaped diagnosis. Biosensors are starting to convert formerly invisible physiological signals into data women—and clinicians—can act on.

But success depends on more than technology. These innovations must deliver clinically verified results, guard deeply personal data, and win the trust of users historically been underserved. As Beckley cautioned, "The best technology won't matter if people don't understand the problem."

AI offers a method to make the invisible visible—to surface rhythm in noise, anomalies in complexity, and meaning in what was once overlooked. If that method is wielded thoughtfully, FemTech may at last graduate from the margins and become a cornerstone of tomorrow's healthcare.

4 Emerging Signals to Watch

1. AI-Assisted Diagnostics at Home
   Fertility and hormonal testing is moving out of labs and into bathrooms. Products like Proov are showing how AI can transform at-home data into clinical-grade insights, reducing time to diagnosis and easing the burden on healthcare systems.
2. Robotic Imaging Platforms
   Next-generation ultrasound systems like EndoCure's suggest a future where AI handles the "needle in the haystack" problem of interpreting thousands of images. Expect robotic + AI imaging to expand beyond endometriosis into oncology and urology.
3. Biosensors in Sexual Health
   AI-enhanced devices are beginning to treat sexual wellness as a legitimate field of data. From vaginal microbiome tracking to biofeedback vibrators, startups are turning previously taboo areas into measurable, research-ready domains.
4. Privacy as a Product Feature
   With the EU AI Act (European Union) now in force, transparency and user consent are no longer optional. The companies that thrive will be those that embed privacy by design, compensate users fairly for their data, and make governance visible at every stage.