Project at a Glance
HairSnap was conceptualized as an intelligent beauty and lifestyle platform designed to help users better understand their hair condition through AI-driven visual analysis. The objective was to create a mobile-first solution capable of transforming simple user photos into meaningful hair insights, personalized health ratings, and tailored product recommendations.
We developed a cross-platform mobile application enabling users to capture or upload images of their hair for instant evaluation. The platform analyzes various attributes such as texture, density, thickness, volume, and overall health condition, translating complex analysis into clear, easy-to-understand feedback for everyday users.
The system was designed to bridge the gap between professional hair assessments and consumer accessibility by providing data-driven recommendations aligned with individual goals — whether improving hair health, enhancing styling outcomes, or selecting the right products. The result was a scalable AI-driven beauty assistant capable of delivering personalized care insights directly through mobile devices.
Solution & Implementation
We engineered HairSnap as a mobile-first AI analysis platform combining intelligent image processing with a streamlined user experience to simplify personalized hair assessment.
Key implementation components included:
- AI Hair Analysis Engine: Developed an intelligent visual analysis system capable of detecting and evaluating hair attributes such as density, thickness, texture patterns, volume, and overall condition from uploaded images.
- Personalized Hair Health Scoring: Introduced a dynamic rating system translating analysis results into understandable health scores and insights, enabling users to track improvements and understand their hair profile.
- Smart Recommendation System: Implemented a recommendation framework that maps analysis results to suggested hair care routines and product categories tailored to individual user goals.
- Mobile-First User Experience: Designed an intuitive interface allowing users to capture images, review analysis reports, and explore personalized recommendations through a seamless and modern mobile workflow.
- Profile-Based Progress Tracking: Users can maintain personal profiles, track historical assessments, and monitor changes in hair condition over time to encourage long-term engagement and improvement.
- Scalable Recommendation Architecture: Structured the platform to support future enhancements such as advanced beauty analytics, skincare integrations, and AI-driven styling simulations.
Technology Stack
Python
AWS
Firebase
NodeJs
Flutter
Android
iOS
AI
Figma
Project Outcomes
- Delivered an AI-driven mobile beauty assistant capable of analyzing hair attributes through image recognition.
- Simplified complex hair assessments into clear ratings and actionable insights for everyday users.
- Enabled personalized product and care recommendations aligned with individual hair goals.
- Improved accessibility to professional-style hair analysis through a user-friendly mobile experience.
- Established a scalable AI foundation for future expansion into broader beauty and lifestyle personalization features.
- Enhanced user engagement through profile tracking and ongoing hair health monitoring.