WHY THIS WORK MATTERS
Health products that ignore gender, context, and lived experience do not get used.
The communities most affected by health challenges hold knowledge that no dataset can capture.
Ethical innovation means making space for that knowledge and letting it shape what gets built.
We help you build HEALTH PRODUCTS that work in real life.
“Integrating gender dynamics and user perspectives early in the development of a health product, while addressing misconceptions that shape perceptions, drives higher engagement, better outcomes, sustained use, and more equitable impact.”
Amanda Cordova-Gomez., PhD | Founder.
“There is power, equity, and righteousness in asking the people you are trying to affect what they want.””
Moushira El-Sahn | Expert
The numbers tell the story.
5% of global health research addresses conditions specific to women54% of health AI tools perform worse for women and minorities due to biased training data7–10 years the average diagnostic delay for endometriosis, a condition affecting 190 million women globallyWhen gender, COMMUNITY VOICES and context are ignored, the consequences are real.
The science works. The product doesn't.
A contraceptive implant with 99% efficacy becomes inaccessible when a woman cannot get it removed on request.Partner opposition. Provider bias. Community stigma. None of these were part of the design from the start.AI scales the bias it was meant to solve.
When health AI tools are trained on data that does not represent women, they perform well for some and invisibly fail others. Unaddressed bias does not disappear, they are scaled.Products reach facilities. Not women
Long-acting contraceptives are available in urban clinics. But for rural women, where the need is highest, trained providers, cold chain infrastructure, and removal services were absent. The delivery model was never designed for the women who needed it most from the start.Evidence sits in reports. Not in practice.
Without real world implementation evidence, gender analysis, and community ownership, innovations generate findings but not change. The people who need them most never benefit.In every case, the failure was not scientific. It was a failure to ask from the very beginning who this is for, what their lives look like, and what it will actually take for this product to reach them.