bobbie — AI Fashion Assistant
Revolutionising online fashion retail with AI-powered digital wardrobe management — reducing returns and improving customer confidence in online apparel purchases.
Product · bobbie.aiOnline fashion retail loses billions to returns and dissatisfaction.
The online fashion sector faces significant operational overhead and consumer dissatisfaction due to garment fit issues. High return rates — often stemming from improper sizing or unrealistic product representation — result in substantial financial burdens for both retailers and consumers, alongside increased logistical complexity and environmental impact.
A clear market demand exists for solutions enabling consumers to visualise garment fit prior to purchase and to leverage peer-driven styling insights — but no one had built a consumer-facing product that combined both at scale.
The numbers make the case. Returns can erase 20 to 30% of online apparel revenue, and a large share trace back to fit uncertainty at the point of purchase. bobbie set out to close that gap before checkout rather than absorb the cost afterward.
Build bobbie — a comprehensive digital wardrobe platform.
Our team was strategically contracted to develop bobbie, an AI-powered fashion assistant. Now in MVP, bobbie effectively functions as a comprehensive digital wardrobe management system — letting users curate, assemble, and manage their clothing collections.
The strategic evolution includes development into an integrated fashion marketplace and social media platform — designed to empower users to make confident online purchases with pre-assured fit accuracy.
Under the hood, bobbie pairs a Flutter cross-platform client with a Node.js and PostgreSQL backend, object storage on Cloudflare R2 for the wardrobe imagery, and a recommendation stack built on TensorFlow and PyTorch. Users photograph or import garments, the models tag and embed each item, and the outfit engine assembles looks from what the user actually owns rather than from a generic catalogue.
The engagement ran lean and fast. We scoped the MVP around the two features users cared about most, the digital wardrobe and AI outfit generation, shipped them to the App Store and Google Play, and instrumented everything so the bobbie team could watch real behaviour instead of guessing. Weekly builds kept the founders in the loop and let us cut features that did not earn their place.
The roadmap from here is a social and marketplace layer: users follow stylists, shop looks they can already visualise on their own wardrobe, and check out with fit confidence built in. Because the recommendation models already understand each user's catalogue, that next phase extends the same data rather than starting over, which is what makes the path to scale realistic rather than aspirational.
Reliability mattered from day one. The Flutter client degrades gracefully on older devices, the Node and PostgreSQL backend scales horizontally on AWS, and wardrobe imagery sits on Cloudflare R2 so storage costs stay flat as collections grow. The result is a product that feels polished to a consumer and stays inexpensive to operate as the user base climbs.
“The Automators turned our concept into a real, polished product fast. The AI wardrobe and outfit generation are exactly what our users wanted, and adoption in the MVP phase has spoken for itself.”
Co-founder & CEO, bobbie
What actually shipped.
Digital wardrobe success
Users built digital wardrobes averaging 80+ catalogued items each, curating outfits and managing collections from a single app.
AI personalisation
The outfit-generation model produced personalised looks from user-imported garments, with roughly 4 in 5 generated outfits saved or worn.
Rapid user adoption
Over 2,000 active users joined within the initial MVP phase, growing about 25% month over month on organic referral alone.
Strong monetisation
800+ users (around 40%) upgraded to paid storage within weeks, a clear signal of willingness to pay and a path to scale.
The tools we shipped with.
Production-grade, vendor-agnostic — chosen for reliability and scale.
2,000+ users. 40% conversion. 800+ paid subs.
bobbie hit those numbers in MVP. Let's explore what's possible for your business.