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The affiliate sourcing for the "missing piece" sometimes points to something close but not quite the same silhouette or color as what the creator actually wore, so I've had to double check a couple of suggested buys against the original photo before trusting it. Would help to show a rough match confidence or flag "closest match, not exact" so you know when to look closer.
I'd looked at Villoid before for the same kind of "plan an outfit before you buy" idea, but it felt more like styling for fun with friends than something tied to what I actually own. Revy's whole pitch is the closet-first check, which is the part that actually changes my buying habits instead of just being a nicer lookbook.
@dheeraj18 Great Work!
Getting the vision layer right is what makes the recommendations actually useful.
@yashekbote Thanks Yash. That was the bet. It's the part nobody sees, but it's the only reason the recs actually land.
Product Hunt! Excited to be here. I'm Kaylin, Founder and CEO of Revy.
I started Revy because I was constantly saving outfit inspiration, but when it came time to actually get dressed... I’d still wear the same things over and over again. And somehow, despite having a closet full of clothes, I was always buying more that would then go unused in a month.
That was really the starting point for Revy.
We’ve spent a lot of time building, changing things, realizing we were wrong about things, and learning from the people actually using it. So getting to share it here feels pretty surreal.
More than anything, I’d love feedback. What makes sense, what doesn’t, what you’d change, all of it.
And I’m curious: how much of your closet do you think you actually wear? I have a feeling the answers are going to be pretty bad (lol).
@kaylin_goddard Curious to know -- did you do Revy while doing a full time job? Did you ever worry about any conflicts/IP issues?
Hey Hunters 👋, I'm Tanmay, ML Engineer at Revy. My work at Revy spanned 3 major areas:
Training computer vision models to detect and segment clothing items, and optimizing these models to run efficiently both on-device and in the cloud.
Building data pipelines to load, embed, and store fashion products so that users can have access to a wide range of product recommendations.
The GPU inference service that accelerates all of AI at Revy. This service is optimized for high throughput, memory efficiency, and, most importantly, cost 😅. (We all know how pricey renting GPUs can get.)
We'd love to hear your experience using Revy!
Heyyaa Product Fam!
I'm Divya (Div - like the HTML ones haha), growth + eng lead @ Revy.
Something that always surprised me is that most affiliate platforms for creators are built around scale - the bigger your following, the more you can earn.
At Revy, we want to empower microinfluencers and crerators. Everyone is a creator at Revy. We built our model the opposite way on purpose, so a creator with a small but real audience earns the same way someone huge does.
Curious what people here think: does follower count actually deserve to be the gatekeeper for who gets to monetize their content, or is that just the default because it was easiest to build?
@better_shaya Thanks Shaya. That's exactly why we started with the closet instead of the store. If most of a look is already hanging in your wardrobe, you should hear that before you see a buy button. The shopping part should only ever cover what's actually missing.
@better_shaya Yes! Exactly.
But the reality is also that people still do like to shop - so we help them make smarter purchasing decisions by showing them how what they are shopping for, fits within their current closet! At the end of the day, sustainable fashion is -- wear more of what you own, and when you shop, shop smarter --




Revy
Gal! Thank you so much for taking the time to share this! The closet-first piece you mentioned is really at the heart of why we built Revy, we want shopping to start with what you already own, not just give you another reason to buy more.
And really appreciate the feedback on the missing-piece matches. Adding more transparency around how closely a recommendation matches the original is a great callout and something we’ll be thinking about as we continue improving the experience. (hopefully as we grow our product catalog - the matching will be closer and closer!)
Thank you again for trying Revy and sharing such thoughtful feedback!!