Evvy, a five-year-old women’s health startup, announced an oversubscribed $40 million Series B on September 15, 2026, led by Catalio Capital Management, funding that CEO Priyanka Jain says will be used to validate a new generation of AI-driven diagnostic and care models across women’s health, beginning with fertility. The round, reported by TechCrunch, Fortune and Forbes, brings fresh new investors including Rethink Impact, Muse Capital and Alumni Ventures alongside returning backers LabCorp Venture Fund, General Catalyst, Left Lane Capital and BBG Ventures.
Building the Dataset Medicine Never Built
Founded in 2021 by Jain along with Laine Bruzek and Pita Navarro, Evvy has spent the past five years assembling what the company describes as the world’s largest proprietary, clinical-grade dataset on the vaginal microbiome and its connection to women’s health outcomes. The company’s at-home test, which is CLIA- and CLEP-certified, uses metagenomic next-generation sequencing to analyze vaginal microbes, and has now been used by more than 100,000 patients working alongside roughly 3,000 practitioners. Jain has framed the company’s mission in blunt terms: “You can’t build precision medicine for women on datasets that never adequately measured female biology in the first place.”
From Test Results to an AI Assistant
In May 2026, Evvy layered an AI assistant, EvvyAI, on top of its sequencing data, designed to translate raw microbiome results into real-time guidance for patients while directing more complex clinical questions to practitioners on the platform. The new funding is earmarked for expanding that machine-learning engine into diagnostic biomarkers spanning fertility, IVF outcomes, recurrent infections, chronic inflammation, endometriosis, perimenopause and HPV progression, according to the company’s funding announcement.
Why Fertility Is the First Target
Evvy’s decision to push into fertility first reflects both scientific opportunity and market demand. The vaginal microbiome has increasingly been linked in research literature to IVF success rates, risk of pregnancy loss, and preterm birth, yet fertility clinics have historically had few standardized, data-driven tools to assess microbiome-related risk factors before or during treatment. By connecting its existing patient dataset, now spanning 15 peer-reviewed publications and conference abstracts, to fertility outcomes specifically, Evvy is positioning itself to sell into a fertility industry where patients and clinics already spend heavily on diagnostics and are motivated to reduce failed IVF cycles.
A Broader Femtech Funding Wave, With Caveats
Evvy’s raise lands amid a broader resurgence in women’s health investment; the same week, the National Institutes of Health announced $21 million for a new Computational Modeling of Hormone Homeostasis Initiative aimed at building sex-specific models of how hormonal biology affects drug dosing and toxicity, a sign that both private capital and federal science agencies are treating women’s health data gaps as a priority in 2026. Still, researchers who track health-tech investment caution that the field has a history of hype outpacing validation: microbiome science broadly remains an active, sometimes contested research area, and correlations between specific bacterial populations and conditions like infertility or endometriosis do not always translate cleanly into reliable, individualized diagnostic predictions. The strongest current signal in the sector, according to analysts who track femtech, is demand for genuinely trustworthy infrastructure, tools that protect sensitive data and reduce friction in care without overselling what an algorithm can determine from a swab.
What Investors Are Betting On
Catalio Capital Management and the other new backers are effectively betting that Evvy’s combination of a large, longitudinal patient dataset and a functioning consumer product, people are already paying for the test and returning for repeat testing, gives it a defensible data advantage that competitors starting from scratch would take years to replicate. That bet mirrors a pattern across health tech, where companies with proprietary real-world datasets have increasingly been valued less like diagnostic labs and more like AI companies sitting on a moat of unique training data.
What’s Next
The near-term test for Evvy will be whether EvvyAI’s fertility-focused diagnostic models can produce results that hold up under independent clinical scrutiny and, eventually, regulatory review, rather than remaining a proprietary interpretation layer sold directly to consumers and practitioners. If the company can show that its microbiome-based predictions meaningfully improve IVF success rates or catch endometriosis and infections earlier than existing standard-of-care testing, it could become a template for how AI-driven diagnostics get built in other historically understudied areas of women’s health, from perimenopause to chronic pelvic pain.
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