SkinWise AI

Inspiration

Skincare shouldn't feel like solving a puzzle with 20 products and 50 different opinions. Most people don't need another shelf full of products—they need to understand their skin, know what suits them, and build a routine they can actually afford and follow. We built SkinWise AI to make skincare feel less confusing, more personal, and easier to stick with.

What it does

SkinWise AI takes you beyond a skin scan. It helps turn skin insights into a practical skincare plan, with:

• Your AM/PM routine: A simple morning and evening plan built around your skin concerns.
• Budget-friendly product choices: Recommendations that consider what you can spend, not just what's trending.
• Sensitivity-aware suggestions: Filters to help avoid ingredients that don't suit you.
• Climate-conscious skincare: Guidance that considers how your local weather can affect your routine.
• Progress tracking: A way to follow your skincare journey instead of constantly starting over.
• Photo-quality coaching: Tips to help you take more consistent skin photos.
• Your skin report: A shareable summary of your results and recommendations.
• Virtual try-on: Explore beauty looks before deciding which one feels right for you.

How we built it

We built SkinWise AI using Python and Streamlit, with a modular structure that separates skin-analysis requests, virtual try-on, skincare routines, and product recommendations. YouCam API integration supports the beauty-analysis experience, while our own recommendation logic connects skin concerns with practical routines and product choices. We also built the interface around a simple idea: users should understand what to do next without needing to decode complicated skincare terminology.

Challenges we ran into

The hardest part wasn't putting features on a screen. It was making them work together as one useful experience. A skin scan alone doesn't tell someone which products fit their budget, which ingredients they want to avoid, or how to stay consistent. Connecting analysis, recommendations, routines, and progress into a clear flow required careful decisions about how each part should work. We also had to separate features that were ready to demonstrate from external API functionality that still needed verification.

Accomplishments that we're proud of

We're proud that SkinWise AI aims to solve the after the scan problem. Instead of leaving users with information and no clear next step, it brings together routines, budget-conscious choices, sensitivity filters, climate guidance, progress tracking, and photo coaching. We're especially proud of designing it around real-life constraints—because a good skincare routine is one that works for the person using it, not just one that looks impressive on a product page.

What we learned

We learned that useful skincare guidance is about more than identifying skin concerns. Affordability, sensitivity, consistency, and everyday habits matter just as much. We also learned to treat external API integrations carefully, test individual components, and distinguish between a promising feature and one that has been verified end to end. Most importantly, we learned to design around the user's next decision, not just the technology behind the screen.

What's next for SkinWise AI

We want to make SkinWise AI a companion users can return to—not just a tool they open once. Next, we plan to strengthen longitudinal progress comparisons, improve routine adjustments as skin needs change, expand the product catalogue, and validate more of the external API workflows. Our goal is simple: help people make fewer random skincare purchases, understand their routines better, and feel more confident about the choices they make for their skin.

Built With

• api
• artificial
• computer
• intelligence
• learning
• machine
• python
• recommendation
• rest
• skincare
• streamlit
• system
• vision
• youcam