SkinSense AI

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  landing-page

Inspiration

Skincare is overwhelming. With thousands of products, conflicting online advice, and ingredient lists that feel like chemistry exams, most people don’t know where to start. Nearly everyone we spoke to, friends, classmates, even strangers admitted they were confused about what their skin actually needs. We realized skincare shouldn’t be exclusive, complicated, or gender-targeted. It should be simple, personalized, and inclusive. Our inspiration came from wanting to create something that helps anyone, regardless of gender, background, or skincare knowledge, to understand their skin and build a routine that truly works for them.

What it does

SkinSense AI transforms a single selfie into a complete, personalized skincare experience.

How we built it

Frontend React + Vite Custom UI components for the routine builder, skin report, and location layer Clean, aesthetic theme inspired by modern skincare brands

Backend Cloudflare Workers Gemini Vision + Text APIs for skin analysis and routine generation Walmart API + Amazon RapidAPI Custom Sephora & Shoppers scrapers Geoapify Places API for store locator Static JSON datasets for ingredients, product types, and cycle patterns

Challenges we ran into

Getting AI output to remain structured despite variations in selfie quality Handling scrapers + APIs under time pressure Debugging Vite hot reload loops during development Making the UI gender-inclusive and beginner-friendly

Accomplishments that we're proud of

Built a full AI-powered skincare engine in under 36 hours Clean, modern, inclusive UX Integrated multiple APIs + scrapers + AI models seamlessly Delivered personalized routines that feel professional and dermatologist-inspired Made skincare accessible to everyone most importantly we created something that can genuinely help people feel more confident in their skin.

What we learned

How to structure AI prompts for reliability How to build scalable Cloudflare Worker backends How to blend AI + product data + geolocation into one system How to design user-friendly, non-intimidating skincare flows The importance of inclusive design in wellness tech How to coordinate multiple APIs under tight time pressure

What's next for SkinSense AI

We're excited to keep expanding SkinSense AI beyond the hackathon:

Skin progress tracking using weekly photo comparisons Multi-language support for global accessibility Sleep + stress integration with skin cycle patterns Dermatologist-mode for more clinical recommendations Mobile app with camera scanning and offline mode

Built With

• cloudflare
• gemini
• rapidkeyapi
• react
• typescript
• vite