FemTech Longevity Companies Regional Distribution

Geographically, the vast majority of companies in FemTech Longevity subsector are based in North America, particularly in the United States, where 58% of companies are located, and Canada at 4%. Europe is the second-largest region, with a 20% share, led by United Kingdom. Israel leads the Middle East region in the number of companies. Asian countries and Australia are somewhat less represented by FemTech Longevity subsector.

FemTech Longevity Companies by Revenue Overview

The largest number of companies in the FemTech Longevity subsector comprising 46% out of total show revenue, estimated in the range of $1M-$10M. The revenue of about 37% of companies does not exceed $1M, while 17% of players have revenue as high as $10M or more.

Longevity in FemTech: Companies Funding

Funding of companies in the FemTech Longevity subsector totaled over $3B in 2021, with 75% falling to the top 10 market players. In fact, 40% of funding was made through M&A, 28% from IPO, and 21% from VC.

The Future of FemTech Longevity

The Future of FemTech Longevity

A great deal of future FemTech will take the form of AI-powered software as a service (SaaS), including courses of monitoring and advice particularly reliant on deep learning, such as that developed by Haut.AI.
Their product is a form of deep learning-powered SaaS for skincare. They help clients develop new skincare strategies, selecting for them skin care treatments for their individual skin type, climate, health status, geography, and other parameters, to personalize the treatments for each individual. The software tracks and updates these parameters over the years, to help aging skin retain a youthful look.
They also create an interaction between between business and customers, facilitating R&D by feeding back data from 100,000 skin images to the company for further deep learning and consequently more accurate and efficient skin care regimes. It is expected that information collected from individual users of such services will provide researchers with large databases of metrics, offering the potential for doctors to better understand a wide range of aspects of women’s health as they age.
However, for serious kinds of female age-related disease such as breast cancer, such kinds of data analytics would need huge amounts of authentic patient data from patients in
different countries and diverse racial and genetic backgrounds, for deep analysis and the creation of different patterns for successful detection.