Inspiration

Choosing skincare can be overwhelming. Consumers face hundreds of products, conflicting recommendations, confusing ingredient lists, and uncertainty about which products actually suit their needs. Even after discovering suitable products, building a practical, compatible and affordable routine can be difficult.

We wanted to bridge the gap between understanding your skin and knowing what to do next.

What it does

SkinMate is an AI-powered skincare discovery and routine-building platform that brings skin analysis, product recommendations and personalised routine planning into one experience.

Users can upload a photograph and receive AI-powered skin insights through Perfect Corp's YouCam AI Skin Analysis API. SkinMate presents the returned findings in an accessible interface and connects relevant concerns with products from its catalogue.

Its central feature is the Routine Curator, which allows users to build skincare routines using available products, explore alternatives, review compatibility information and consider the total cost of their routine.

Users can also save products and routines through My Lists, making it easier to revisit their selections.

How we built it

We built SkinMate as a full-stack web application, combining a React-based frontend with a Python backend and Perfect Corp's YouCam API.

The YouCam integration handles image submission and AI skin analysis. The backend processes provider responses and makes the resulting information available to the frontend.

We developed a shared product catalogue and recommendation experience, followed by the Routine Curator, which brings product selection, compatibility information, alternatives and budget awareness together.

We also designed SkinMate as a guest-first experience, allowing users to explore and save their selections locally without requiring account registration.

Challenges we faced

One of our biggest challenges was turning AI analysis results into something genuinely useful for consumers. Displaying skin metrics alone does not help someone decide what to do next.

We focused on connecting analysis findings to product discovery and then translating those discoveries into a practical routine.

Another challenge was product catalogue integrity. We implemented image-source attribution, product identity checks and intentional text-based product cards for listings without verified images, rather than displaying misleading product imagery.

We also worked to make the experience transparent, accessible and useful without overwhelming users with technical information.

What we learned

We learned that the value of AI in consumer skincare is not simply in generating an analysis. It lies in helping people understand the results and make more informed decisions.

SkinMate represents our attempt to connect those steps in one coherent experience: analyse, discover, configure and save.