Walaland is an AI-powered fashion discovery platform
built for a generation who shops through screenshots, not search bars.
Date
Role
Company
Contribution
And…everyone's asking the same question : Where can I get that?
Image source : INSTAGRAM Account (@style_Moabom)
Define problem
As we dug deeper, one thing became clear, the desire was there, but the path was broken.
How might we
Asking real world again
72%
Take outfit screenshots weekly
Screenshots are the default way to save style inspiration |
92%
Could not find exact product afterward
Search tools fail their visual-first habits |
67%
Tried typing outfid descriptions into search
But results were too broad or irrelevant |
58%
Gave up mid-search
Frustration often blocks purchase intent |
Hypothesis
Hypothesis
We believe that
replacing keyword-based search
with a visual-first discovery experience
will
increase conversion & engagement
if
visually driven users
can explore and shop
from screenshots with ease.
Asking real world again
solution walkthRough
We started building a product
that listens to the way people see.
Screenshot search - Pull based behavior
From screenshot to shoppable, in under 10 seconds.
Style-to-brand redirection - Push based behavior
Tag the style. Jump to the brand
Users exploring celeb lookbooks or moodboards can tap on any outfit -
and get instantly redirected to where that item (or the closest match) lives.
No more asking strangers for links and waiting. Just tap and go.
Exploring Walaland app
Users open the app and freely browse content. They see photos of outfits worn by celebrities, and can tap to get redirected to sites selling similar items.
Exploring Walaland app
Users can also swipe through short-form videos like Reels - where outfits worn by celebrities are featured and made shoppable.
Overall mobile APP screeNs
Designing with AI in the loop
And behind that simplicity? A 38-layer AI engine, working quietly in the background.
I designed the system to surface these signals clearly - without users needing to ask.
Instead of dropdowns or filters, the UI simply showed what the AI saw :
structured recommendations, top/bottom splits, and scrollable matches by type.
AI understood garment strucuture
WALA’s backend used a 38-layer deep learning model to scan a screenshot and detect visual signals:
tops vs bottoms, sleeve type, neckline, overall silhouette.
But raw detection alone wasn’t enough.
Designing with AI in the loop
After finalizaing our 1st version of product,
We tested with Gen Z K-pop fans, and listened. Closely.
These two personas revealed one clear insight: Not all users shop the same way - but both expect the product to understand their intent.
Our hypothesis was simple: If we designed a visual-first experience, both vibe-driven browsers and brand-driven hunterscould find what they love - in their own way.
Persona 1
Emotion-first user
“I don’t know the brand… I just want more things like this.”
Scrolls TikTok and K-drama screenshots daily, loves the feeling of an outfit, not the name. For her, discovery means vibe first, shopping later.
Titok lover
Moodboard scroller
Screenshot collector
Casual discoverer
Style-driven, not brand-driven
Persona 2
Brand precise hunter
“If I fall for something, I need to know the exact brand.”
Tracks airport fashion and styling tags, builds moodboards by idol. Wants to buy the real item - not just something close.
Style perfectionist
Airport fashion tracker
Brand ID detective
Idol stylist follower
Exact-match shopper
The result?
Both types found what they were looking for, whether it was a mood or a match.
Designing with AI in the loop
What stayed with users wasn't the AI.
It was how natrual the experience felt.
What did I really learn from designing WALALAND?
Designing with AI in the loop
We didn’t just build a product.
We surpassed what we set out to prove.
It was right after WalaLand was first launched on the App Store, when I tried running the app for the very first time!
What started as a tool to simplify discovery grew into a trusted platform.
With $5.3M raised, 500+ brands onboarded, and real traction from Gen Z users,
More than a product launch, it proved what thoughtful design can achieve.