I know people don’t like to read long case studies, so I’m adding my work first below. But if you’d still like to read the full case study, you’ll find it after the project images. The project lasted around 1 month and is now under development.

Lustra AI is an AI-powered skincare platform designed to make personalized skincare more accessible, informed, and easy to manage.

The platform uses AI-powered facial scanning to analyze skin and provide detailed insights across key metrics such as hydration, acne, pigmentation, tone, texture, oil control, and sun protection.

Based on these insights, Lustra recommends suitable skincare products and helps users build personalized morning and evening routines. Users can also track their progress over time, compare previous scans, save products, and stay consistent with their routines.

The platform also introduces a social layer where users can share reviews, routines, achievements, and skincare journeys, creating a more engaging experience around personal care.

The goal was to create a personalized skincare experience where complex AI insights feel simple, actionable, and easy to understand.

Deliverables: UI/UX Design, Design System, User Flow Architecture, Prototyping

Skincare can feel overwhelming, especially when users are presented with complex skin metrics, product choices, and routines without clear guidance.

The main challenge was to make AI-powered personalization feel useful and understandable rather than technical or intimidating.

Our challenge was to:

Transform complex AI skin analysis into clear and actionable insights.

Create a personalized experience that adapts to each user's skin concerns and needs.

Make skincare recommendations feel relevant and trustworthy.

Design an easy-to-follow routine experience for morning and evening skincare.

Connect scanning, recommendations, progress tracking, and social features into one cohesive ecosystem.

I worked on the end-to-end product design for Lustra AI, taking the experience from user flows and information architecture through to the final interface and prototype.

Key responsibilities included:

Defining core user journeys across skin scanning, analysis, recommendations, routines, and progress tracking.

Designing high-fidelity interfaces that make AI-generated insights easy to understand.

Creating personalized flows around different skin concerns and user needs.

Designing product discovery, saving, and recommendation experiences.

Building a modular design system with reusable components for a consistent experience.

Prototyping key interactions to validate the overall product experience.

Designing the social layer around reviews, routines, achievements, and skincare journeys.

We explored existing skincare and AI-powered beauty experiences to understand how users interpret skin analysis, product recommendations, and routine-based guidance.

A key focus was understanding how to present multiple AI-generated metrics without overwhelming users.

Key insight: users needed more than a skin score. They needed clear explanations of what each metric meant, why it mattered, and what action they could take next.

I structured the experience around a continuous skincare journey rather than treating skin analysis as a one-time feature.

Core Flow: Scan Skin → Analyze Results → Understand Concerns → Get Recommendations → Build Routine → Track Progress

The architecture also connected supporting experiences such as saved products, previous scans, achievements, reviews, and social content, allowing users to move naturally between discovery, action, and progress.

The visual direction focused on making AI-powered skincare feel approachable, premium, and easy to navigate.

I used clear information hierarchy, visual indicators, structured metrics, and contextual explanations to turn complex analysis into digestible information.

The interface was designed to balance the technical nature of AI with the personal and lifestyle-oriented nature of skincare, keeping important actions such as scanning, following routines, and exploring recommendations easily accessible.

Interactive prototypes were created to validate the most important product journeys, particularly the AI scanning experience, skin analysis results, product recommendations, and personalized routines.

The design was refined around a simple principle: every insight should lead to a meaningful action.

This helped create a smoother transition from understanding the user's skin to knowing what products to use, which routine to follow, and how to track progress over time.

Personalized skincare experience: AI-powered analysis was translated into personalized insights, recommendations, and routines based on each user's skin needs.

Actionable AI insights: Complex skin metrics were presented in a way that helps users understand their concerns and take the next step.

Connected skincare journey: Scanning, recommendations, routines, progress tracking, and social features work together as one cohesive experience.

Progress-driven experience: Users can compare previous scans and monitor changes over time, making skincare feel measurable and motivating.

Scalable design system: A modular component system provides a consistent foundation for expanding Lustra with additional skincare features and experiences.