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I've never really understood how people decide on a new hairstyle.
Most of the time, we save photos from Instagram, Pinterest, or a celebrity we admire and hope it looks good on us too.
But what if it doesn't suit our face shape?
That thought led me down a rabbit hole and eventually became a design concept I'm currently exploring: StyleScan.
The idea is simple.
You scan your face, get a breakdown of your facial features, and receive hairstyle recommendations that actually suit you. You can even try them on virtually, save your favorites, and share them with friends before making a decision.
One thing I kept asking myself while designing was:
"How can I help people feel more confident before they sit in a barber's or salon chair?"
Instead of making users guess, StyleScan is designed to guide them toward styles that fit their unique features.
Would you trust an app to help choose your next hairstyle? 👇
#UIUX #ProductDesign #MobileAppDesign #UXDesign #Figma #DesignThinking #AppDesign #StartupIdea
I loke those radial effect around the photo! Smart move!
Glad you like it 😁
Thank you! This started as a random idea and quickly turned into a full product concept. Glad you enjoyed it.
Clean and effective.
Thank you! Glad you like it. I enjoyed exploring the problem and thinking through how the experience could make hairstyle decisions a bit easier.
The face scan flow is a smart way to frame the core feature. Using the camera as the hero interaction makes the value prop immediately tangible. What's the plan for matching accuracy, ML model or curated database?
Great question. For the MVP, I'd start with a curated database approach rather than training a custom ML model from day one.
The initial version would use face-shape detection and predefined matching rules to recommend hairstyles based on facial structure, proportions, and hair...
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New design update: Reviews & Ratings for a Marketplace Buyer Profile🌟
Reviews are more than just stars - they help people decide who and what they can trust.
While designing this feature, I focused on making reviews clear, transparent, and useful for buyers.
Key improvements:
• Separate reviews about products and sellers for better context.
• Highlight verified purchases to increase credibility.
• Structure feedback so users can quickly find relevant information.
• Create a clean and intuitive experience that supports confident decision-making.
The goal was to turn reviews into a trust-building tool rather than just a collection of ratings.
Part of my ongoing Marketplace App concept. More screens coming soon 👀
Love this approach! Reviews play such a big role in decision-making, and I like how you've focused on making them more useful and transparent instead of just displaying ratings. Excited to see the next screens ✨
Amazing!
Meet ScribblePrompt.
It started with a moment at work. I was whiteboarding with one of our engineers, and the conversation felt faster, clearer, and more productive. That made me realize I wanted the same kind of experience with my coding agents, without sending screenshots, typing long explanations, and still not quite getting what I meant.
So me and @Carlneil Domkam built ScribblePrompt in Figma Make: a tool that lets you whiteboard with an agent, so ideas start as sketches, not walls of text.
If you like design tools that make ideation feel more natural, we’d love for you to check it out.
Features:
- Whiteboarding tools
- Sketch Context for Figma Make
- MCP for Claude and Cursor
- Sketch Assistant — generate sketches
- Responsive across desktop and iPad
Tools used:
- FigJam for ideation and brainstorming
- Figma Make for prototyping and implementation of the sketching tool, sketch context, and audio transcription
- Figma Design for UI design tweaks
- Figma Weave for logo generation and storyboard references
- Anthropic API for Sketch Context and MCP
- Gemini API for the sketching assistant:
It's been a fun 2 weeks participating in this hackathon! See you at Figma Config! 🚀
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