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Vibin hero

Vibin

(brief)

Vibin is a live social discovery app for Gen Z. People at a venue post the vibe in real time, GenAI turns it into data, and the map shows what is actually happening right now. Co-founded, designed, and shipped to the App Store.


Company
Vibin (co-founder)
Tools
Figma, iOS, GenAI
Role
Product Designer
Year
2025

(my role)

I co-founded Vibin and designed the product end to end: the research, the information architecture, the wireframes, the final UI, and all the brand and marketing collateral, posters, flyers, merch. After launch I iterated using real behavioral data from our users.

(the problem)

Five apps to make one plan.

To decide where to go tonight, people check the map, Instagram, stories, reviews, and group chats, and still do not know what a place feels like right now. Photos are old, reviews are older. The one thing that matters, the live vibe, is nowhere. Our research showed the decision runs on FOMO and spontaneity, not on star ratings.

(1)

I mapped the information architecture twice, then let users pick

There were two honest ways to build this app, and arguing about them would have wasted weeks. So I built both structures out properly.

The first organised everything around places: you open a map, you browse venues, the people are a detail inside each one. The second organised everything around people: you open a feed of who is out tonight, and the venue is a detail attached to them.

I put both in front of real users and watched which one they could actually use. Places won, clearly. People opened the app asking "where is good right now", not "who is out". So the map became the home screen, and I filtered it by vibe instead of by category, because nobody was choosing a night out by the word "bar".

Vibin IA around places Vibin IA around people
Vibin wireframes

Early wireframes for the vibe-first map

(2)

I designed a loop that takes seconds to post

Posting a vibe takes seconds, one photo, one line, and GenAI does the heavy lifting: it classifies the atmosphere into structured data, so "packed rooftop, live music" becomes something you can search and filter. Every venue gets a live Vibe Report, a scorecard built from what people posted in the last hour, not last year.

Post in seconds

One photo and one line, GenAI handles the rest

Browse by vibe

Chill, party, eats, live, the map filters by feeling

Vibe Report

A live scorecard per venue, built from the last hour

50+
active users reached with zero paid promotion
0%
commission, Posh charges 15%, Eventbrite 3.5% + $1.59
2
sides of the marketplace get value from day one
Vibin final UI, live map

The final map, live vibes filtered by feeling

Vibin product screens, final

Posting flow and the Vibe Report screen

(3)

I built a brand for nightlife, not software

Vibin had to feel like the streets, not like an app. I designed every asset in-house, event posters, vendor flyers, branded merch, social content, all pulling from the same gradient-and-glow system as the app itself, so a poster on a wall and a screen in your hand read as one brand.

Vibin event poster Vibin marketing flyer Vibin event poster, second
Vibin branded merch bag Vibin event brochure

(4)

I designed a marketplace that charges no one

Vendors get visibility and foot traffic, users get live vibes and exclusive deals. Eventbrite charges 3.5% + $1.59 per ticket, Posh takes 15% commission. Vibin charges neither side, the marketplace runs on presence, not fees. Post-launch behavioral data invalidated three assumptions from our interviews, real usage beats what people say.

For vendors

Visibility and foot traffic without commission

For users

Live vibes and exclusive deals at the door

For the product

Every post makes the map smarter

Vibin two-sided marketplace diagram
Vibin traction

(the outcome)

Live on the App Store.

Vibin shipped as a real product with real users and a two-sided marketplace that charges neither side. I ran more than ten usability sessions after launch and used what people actually did, not what they told us, to decide each next change.

What I learned: ship early, because real behaviour beats opinions. Post-launch data killed three assumptions we were confident about from our interviews. A month of extra polish would not have taught us any of that.

Next project: Pastiche →