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Case study·Luxury fashion·AI styling

Vêtir

Avatar in a camel coat with fur collar and brown flares Avatar in a cardigan and olive mini skirt Vêtir avatar Vêtir avatar

From a scattered MVP to an integrated
shopping & styling ecosystem, powered by AI.

Role
Lead Product Designer
(sole designer)
Team
2 frontend · 2 backend
1 QA · Founder
Platforms
iOS app · Web (desktop + mobile)
Internal CRM
Timeline
May ’25 – Sept ’26
The problem

The features were there.
The product wasn't.

Vêtir launched with a big vision: shopping, professional styling, personalization, and AI. The ingredients were there, but the experience had grown feature by feature, without a clear product language connecting everything together.

Shopping wasn't as effortless as it could be. Styling was difficult to recognize as a core part of the experience. And the early AI Stylist felt more like search than an intelligent styling partner.

Across the product, inconsistent visual patterns, weak hierarchy, fragmented navigation, and disconnected experiences made Vêtir feel more like a collection of features than one product.

As the sole designer, I set out to change that.

The goal wasn't simply to make Vêtir look more luxurious. It was to make the product easier to understand, easier to use, and much clearer about the value of styling and personalization at its core.

I rebuilt it module by module, inside the existing roadmap. As the product evolved, so did the experience—from a rudimentary AI layer and fragmented shopping flows toward richer styling experiences, including AI-assisted outfit creation and avatar try-ons.

At a glance
190
stylists on the platform, up from ~14 when I joined
200+
components brought into one shared system
↑
organic search traffic and orders after the design overhaul
Before

The scattered MVP.

Vêtir had strong individual features, but no shared language connecting them.

The product had grown quickly, and every new feature added another pattern. The result was an experience that felt inconsistent visually, structurally, and functionally.

Old Vêtir closet screenios / closeteverything in
one list
owned or
wishlist?
stylist picks
get lost
Old Vêtir AI Stylist screenios / aiAI help lived in
a separate chat
results felt like
search, not styling
products, not
styled looks

Visually

No shared language. The app used Helvetica, the web mixed Libre with assorted fonts, and there was no type hierarchy, which also hurt SEO. For a luxury fashion platform, the result felt more mass-market than it should have.

Structurally

Engineering had developed its own component set independently of design. Every new feature introduced another pattern, making the experience harder to keep coherent.

Functionally

Strong features in silos. Shopping and styling both existed, but neither felt as seamless as it could be. Navigation hid parts of the product. Important functionality was difficult to discover. And the styling proposition wasn't immediately obvious.

Each feature worked on its own.
Together, they didn't add up to one product.

Insights

No research budget. Plenty of signal.

Insight 01

People couldn't find what already existed.

Navigation hid the product's range, so existing features went unused.

01 / 04
Signals from

Google Analytics · UX audit · Product feedback · Competitor analysis

Serving Lookssince 2024
Model in a styled outfit, standing on the serving tray
Design principles
Principle 01

AI as a stylist, not a search engine.

A stylist serves you a look. Search hands you a list. Every AI feature was tested against this, and wherever something returned a static list when it could collaborate with the user instead, that became the problem to solve.

Principle 02

One system,
one luxury identity.

Minimal and editorial: imagery does the emotional work, restraint does the credibility work. Every new feature is built inside the system, not bolted on as an exception.

Buy-in

It was live. It wasn't clicking yet.

Traction and revenue were low, and people were confused about what Vêtir actually offered: a store, a styling app or a stylist marketplace?

Adding more features felt like the obvious fix. I needed to show that the real problem was the experience holding those features together, and make that case on business terms, not aesthetics.

Step 01 · Audit

A series of audit presentations

I mapped where the experience broke down, where functionality was difficult to discover, and where the visual language felt inconsistent with the luxury brands Vêtir sold.

Step 02 · Trial

The Outfit Module as the trial

Rather than proposing a disruptive redesign of the entire product, I used the Outfit Module as the trial. It was a high-value part of the product where the new approach could be demonstrated clearly.

Step 03 · Proof

The trial became the plan

The ops team, who onboard clients and stylists every day, started relaying positive feedback. The redesign continued module by module. The redesign became the way the roadmap was executed.

Roadmap

Redesigning through
the roadmap.

RedesignRoadmap

A styled outfit: denim jacket and skirt, black bag, sunglasses, gold earrings and black heels
· ResearchMay
· OutfitJun
· ClosetJul
· CheckoutAug
· ConsignmentSep
· AI StylistOct
· Avatar + try-onNov
· Homepages ×3Jan
· Stylist dashboardMay
Total8 modules · 1 designer
0525 0926 2026
Shipped

A big-bang redesign wasn't realistic for a five-person engineering team at our funding stage.

Instead, every incoming feature request became the entry point to redesign its whole module in the new system. The redesign absorbed the roadmap rather than competing with it. Many smaller flows shipped between these milestones.

The tradeoff

For months, two design systems ran side by side. Keeping the product feeling coherent across converted and unconverted pages took constant judgment calls. High-value surfaces went first, internal tools last, and the AI Stylist's agentic flows were scoped into phase two. The old system is now fully retired.

System

Quiet by design. Built to scale.

Type
Helvetica Neue
Vêtir runs on functional flows, so it needed a highly legible family and a clear hierarchy. That hierarchy also gave every web page a proper heading structure, which lifted organic search.
Role · tokenWeight · Size · Tracking
Display & headings
Page titleH1Regular · 20 · -2%
DisplayH2Light · 40 · 0%
Banner titleH3Regular · 24 · -2%
Section headingH4Medium · 14 · -2%
Body
$1,220 PriceRegular · 20 · -2%
Description · InputRegular · 14 · 0%
Button CTAMedium · 14 · 0%
LinkMedium · 14 · 0%
LabelRegular · 12 · -2%
CaptionLight · 11 · 0%
Colour
Brand
Obsidian Black#222222
Porcelain White#FFFFFF
Accent · AI only
Light gradient#FFF → #CFB286
Dark gradient#FFF → #B08D57
AI text#A27843
Status & feedback
Error#D83F31
Warning#EAC282
Nudge#E2DACB
Info#009CA7
Success#37B358

Black and white carry the product. Gold is reserved for AI, so users recognize "the stylist is here" at a glance. Nine warm neutrals and muted status colours keep the editorial mood.

4ptspacing; separate grids for iOS and web
200+components on Figma variables that map to code
Allshared ownership, internal visual check before push

Type App styles at actual size, headings in the order they appear on a page. On web the same roles scale up: Display 48, Banner title 40, Page title 80, Section heading 24.

Iconography
System · 24 px, 1 px stroke
Home
Search
Image search
Camera
Add photo
Voice
Chat
Send
Email
Notifications
Pin
Play
Tutorial
Grid view
Select
More
Styling & AI
Closet
Outfit
Menswear
Try-on
AI stylist
AI stylist
Magic edit
Packing list
Shop
Price tag
Calendar
Trends
Analytics
Orders & business
Shipped
Returned
Cancelled
Card
Earnings
Invoice
Weather · for daily outfit suggestions
Sunny
Partly cloudy
Rain
Windy
Snow
Sizes
16
20
24
32
Bottom navigation, Home active
Order status list with status iconsSaved card row
Outfit actions menu
Add item menuCreating your avatar loader
Signature components
Product card: gold watch with add-to-bag and wishlist actions, brand and price
Product card
AI Stylist prompt: Hi, what do you want to wear today?
AI prompt
Premium upsell modal: unlock personalized styling, premium tools, packing lists and virtual try-on
Premium upsell
Cart item: brown leather jacket with size, return policy, sale price and quantity stepper
Cart item · sale
Editorial look card: Wedding Guest Looks, styled for an upcoming event
Editorial look card
Nudge: You have 2 events coming up! Create outfits
Events nudge
Shop This Look sheet: every piece in the look with sizes, added to cart in one tap
Shop this look
Voice search bar, listening
Voice search
Skin tone selector for the try-on avatar, from Porcelain to Espresso
Skin tone · try-on
Outfit card: Classy Evening Look flat lay with try-on, add-to-bag and AI actions
Outfit card
Empty state: Create your next look, with Create Outfit and Ask AI Stylist actions
Empty state · AI entry
AI prompt card: Get your Friday fit in an instant
AI prompt card
Ask AI Stylist pill with the gold AI sparkle
AI entry
Earning potential: $356 a stylist could earn from this look
Stylist earnings
Collection banner: Paris Vacation '26 with a flat lay of the looks
Collection banner
Cart item: pink satin pumps with size, size chart, price and quantity stepper
Cart item · full price
Chapters

Six modules.
One product.

Chapter 01

Personalized homepages

Three audiences, three homepages. Shoppers and clients open on weekly try-ons across diverse avatars, followed by stylist picks, new arrivals, edits and a direct way into the AI Stylist. Guests get a lighter introduction to the product.

Deep dive · coming soon
Homepage · The Shopper
Styled looks first
Homepage · The Stylist
AI assistant + earnings first
Homepage · The Guest
A lighter introduction

Every screen scrolls on its own. Hover to pause, click for the full page.

Homepage · The Guest on web
Engineering

From two systems
to one language.

Rolling the system out module by module meant components arrived gradually, instead of a disruptive handoff. Engineering adopted the new components, and once we added an AI-assisted Figma-to-code workflow, variables and components mapped almost one-to-one into code.

01Design QA pass after every feature ships
02Interaction docs for each redesigned module
03On-call handovers for edge cases and missing states
04Design work tracked in Jira alongside engineering
For stylists

The Stylists’ Studio

Stylists were Vêtir's growth engine: each one brought their own clients. So the product grew a toolkit around a stylist's working day: commissions on every client purchase, digitized client closets, AI-assisted styling, a look calendar, invoicing and a performance dashboard.

Together, they made Vêtir a place where a stylist could run their whole business.

  • Earn & grow
  • Run the business
Outcomes

Finally, it looked the part.

13×

Stylists on the platform (~14 → 190), as it became something stylists could run their business on.

↑ organic

More search traffic and orders after the type and hierarchy overhaul.

–40% drop-off

Lower drop-off, higher engagement. More active users, longer sessions.

12K users

7.4M interactions since launch.