The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
GlowAI — AI Skincare Scanner & Dermatologist Recommendation Platform
Project Overview:
Most people struggle to find the right skincare routine because cosmetic products are often chosen through trial and error. I built GlowAI to bridge this gap by combining computer vision-based skin analysis with a smart recommendation engine that suggests personalized routines and verified dermatologist-grade ingredients.
The Problem:
Users face information overload when dealing with skin concerns like acne, hyperpigmentation, or barrier damage. Off-the-shelf apps either act as basic affiliate link directories or lack transparent, ingredient-focused insights tailored to individual skin types.
Key Features & Implementation:
Smart Skin Assessment:
Designed an intuitive image-capture and multi-factor questionnaire flow that analyzes skin type, primary concerns, sensitivity levels, and lifestyle factors.
Ingredient-Centric Recommendation Engine:
Built dynamic matching logic that pairs identified skin issues with active ingredients (e.g., Niacinamide, Salicylic Acid, Ceramides) rather than just pushing generic brand names.
AM/PM Routine Builder:
Created an automated routine generator that organizes steps into morning and evening regimens with usage frequency and conflict warnings (e.g., not mixing Retinoids with direct Acids).
Progress Tracker:
Implemented a visual timeline feature allowing users to log weekly skin photos and track improvements over time.
Responsive UI/UX:
Crafted a clean, minimalist interface focused on accessibility, fast load times, and frictionless onboarding.
Tech Stack & Tools:
Frontend / Architecture: Modern Component-Driven UI, Responsive Layouts
Backend & Logic: RESTful API Architecture, Dynamic Recommendation Engine
Data Management: Relational Schema for User Profiles, Ingredients & Routine Logs
Integrations: AI/Vision Model API for skin analysis, Secure Media Storage
Key Takeaways & Impact:
This project allowed me to solve a real-world consumer problem by turning complex dermatological data into a simple, interactive, and personalized user experience.
Open to freelance and contract opportunities in Full-Stack Web Development, AI Integration, and Product Engineering. Let’s build something great together!
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Trending
retrofuturism
Share your favorite designs from the past exploring the distant future. Or your own take on the aesthetic 🚀
halftone
Dots. Texture. Grain. Let's see your designs using the halftone technique.
Midjourney
Creatives are showing off what they're making with Midjourney.
colorgrade
Video editors sound off: How do you enhance the mood of your video in color grading?
Related posts
When designing a music app, most teams start with the player screen.
We did too. It's the obvious center of gravity.
But when we worked on this concept, we noticed something. The player was the least interesting design challenge. Every music app has a player. Not every music app knows what you actually listen to.
So we built around the intelligence layer first Sound Intelligence. 18h 42m of listening time. 239 songs played. Peak listening 9 PM–12 AM. Genre distribution mapped across Lo-fi, Pop, R&B, and Others in a horizontal bar system that makes your taste visible at a glance.
The player came second. The library came third. And the AI Discovery panel 24 tracks, 96% match came last, because by the time a user reaches it, the app has already proven it understands them.
What we noticed was that designing analytics before aesthetics made the whole product feel smarter. The visuals followed the data, not the other way around.
Does your music app know you as well as this one does?
Love how intuitive this mobile app design is
Three years ago, we built a service provider booking app (plumbers, carpenters, electricians) from scratch, fully custom code. Took close to 4 months to get live.
Today, with AI tools like Claude and ChatGPT in the workflow, I think a comparable MVP could realistically ship in 4-6 weeks. The boilerplate and repetitive work compress fast, matching logic and payment edge cases still need real engineering judgment.
If you had to rebuild something similar today, what timeline would you expect?
Four to six weeks feels realistic for a focused MVP now. The acceleration is real, but matching rules and payment edge cases are still where the product needs careful engineering.
Day14/30 of creating with AI
I figure something isn't working about this UGC ad
Can you guess what that is?
Let me know your thought...
UGC CreationugccreatorugcproductsaivideocreationAI Content CreationGraphic DesignCapCutChatGPTGoogle Flow
Awesome Video