About Cutib
Skin science, owned by each person
Skincare rests on more science than most categories, yet people often choose from shelf placement, packaging, and influencer clips. Cutib closes that gap. Founded in Seoul in 2023, we put skin reading in the hands of consumers and the brands serving them.
The founding team shared one frustration: the science and models existed, but no consumer product made them usable. Cutib is that product.
Our Story
From Seoul, built for skin everywhere
Seoul is among skincare's most demanding markets. Consumers read labels closely and switch quickly when products fall short. Working in that setting shaped our focus on precision.
During our first year, we researched skin reading with formulation scientists and a computer vision research team. The aim was not another quiz or skin-type classifier, but a model that reads a person's actual skin and links it to specific product and ingredient outcomes.
In 2025, we began early access with three DTC beauty brands. Feedback showed product-level personalization reduced returns and lifted repeat purchase intent. The public platform launched in early 2026.
The Team
Three people, deep expertise
We are a small founding team, and each person has a specific reason to care about Cutib's work.
Donghyuk Choi
CEO and Co-Founder
Donghyuk built recommendation systems for consumer mobile platforms and saw one pattern recur: matching logic existed, but the consumer product to surface it did not. Skincare showed that gap most clearly, leading him to co-found Cutib.
Soyeon Kwon
CTO
Soyeon works across computer vision and ML for human skin analysis. She has built real-time image classification pipelines for consumer apps, bringing that production discipline to Cutib's skin-reading model. She leads its technical architecture and analysis pipeline.
Arjun Mehta
Head of AI
Arjun works on large-scale recommendation and search systems for consumer e-commerce, including cold-start personalization and sparse-signal matching for new users with little history. At Cutib, he applies this to the product-matching layer connecting a skin reading to a specific routine.
What We Believe
Three principles shape our work
Precision, not generalization
Skin types offer shorthand, not sound decisions. Combination skin in Seoul in winter differs from combination skin in Mumbai in July. Cutib works from the individual reading rather than a category bucket.
Make each AI reading clear
Every Cutib recommendation includes a reason: what the skin reading found and how it points to an ingredient or product. We do not ask you to trust a black box.
Small brands need these tools too
Large beauty corporations have formulation teams and skin science labs; a three-person indie brand does not. Cutib levels the field so brands of any size can offer personalized guidance of the same quality.
Begin Today
Read your skin. Find your fit.
Explorer is always free. Take your first skin reading in under two minutes.