Data meets dermatology at Brooklyn-based skincare start-up Atolla, launched by an MIT engineer who has applied machine-learning algorithms to fix problem skin.
The Atolla Skin Health System works by giving users testing kits to measure the exact characteristics of their skin ? specifically, its hydration, oil, pH and absorption.
It then sends them a face serum calibrated precisely to their skin's needs, with the formula updated monthly.
Atolla creates skincare products personalised to an individual's skin
Atolla's co-founder Meghan Maupin ? who has previously worked on an AI-powered personal assistant and products for mass customisation in 3D printing ? was at the Massachusetts Institute of Technology when she decided to see if she could use her software expertise to improve her skin. "I have super sensitive skin, and when I got to MIT, I found myself dealing with a whole new set of skin issues," said Maupin. "I couldn't understand what was causing my skin freakouts or how to solve them."
"Challenged to figure it out, I realised that I was at the best place in the world to solve this complicated problem with machine learning."
The company sends users a kit to test their skin
She teamed up with data scientist Sid Salvi, who was doing his MBA at MIT Sloan at the time, and dermatologist Ranella Hirsch to co-found Atolla in 2017.
They went to develop the idea at the MIT Delta V summer accelerator in New York City and launch a successfully funded Ki...