This AI assistant will help you decide what clothes to wear
The app was launched in June however, it has managed to secure US$100,000 in angel funding
The app was launched in June however, it has managed to secure US$100,000 in angel funding .PHOTO: REUTERS
It sucks when you’re scouring through your wardrobe to find an appropriate outfit for the day but just can’t seem to decide on one. Or when you unwrap those cool new pants you bought recently but find there’s no shirt in your closet that pairs with them.
SuitApp wants to solve this problem for you. It’s an AI stylist accessible from an app on your phone. It gives you personalised styling recommendations based on the occasion, with the outfits determined from inventory in ecommerce stores as well as individual wardrobes.
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“We transfer the styling process from offline to online,” explains Jen Grebenshchikova, co-founder of SuitApp. “In the offline world you can’t always afford a stylist or spend time consulting one. Online it’s free and easy to use for everyone.”
The startup calls its recommendation algorithm the “Styling Fairy.” It’s been engineered with a combination of both human and machine intelligence, meaning it incorporates generic styling recommendations from actual stylists but understands individual preferences the more you use it.
Once you download the app and sign up, it’ll prompt you to input your gender, color preferences, and the kind of look you’re aiming for. Users can also take a selfie for the app to generate a personal avatar – with the result that you get a much better idea of how the clothes might look on you.
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SuitApp, which is accelerated at MaGIC, aggregates content from online stores Zalora and Lazada to come up with possible outfits. “There’s over 70,000 fashion items on Zalora alone,” explains Jen. “You might find something you like but it’s very difficult to find appropriate shoes and bags.”
The startup isn’t monetizing right now but the founders have already determined that the two avenues would be through affiliate marketing and promoted styles.
Too many clothes, too little time
Elena Chuiko, co-founder of SuitApp, says the idea behind the startup came after many people in her circle complained about a lack of time to go to the mall or follow the latest fashion trends.
Her male friends, who lead busy lives as businessmen, faced an awkward dilemma: they needed to look sharp and presentable for meetings but couldn’t tear themselves away from the office to physically shop for clothes. At the same time, women wanted something quick and accessible on their phones.
“They were saying I wish there was an app where I can press a button and there are outfit suggestions and then the outfit is delivered to your doorstep,” recalls Elena.
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The founders, who are originally from Russia, understood this was a common problem faced by busy millennials. They chose to start up in Malaysia because of the vast Southeast Asian market and the tilt towards online shopping.
SuitApp is now firmly targeting Malaysia, Singapore, and Brunei as its core markets.
The app launched in June so it’s too early to talk about traction. However, it has managed to secure US$100,000 in angel funding so there’s a bit of breathing space. For the future it plans on adding more content from online stores, sharpening its AI recommendation engine, and acquiring users at scale.
This article originally appeared on Tech in Asia.
SuitApp wants to solve this problem for you. It’s an AI stylist accessible from an app on your phone. It gives you personalised styling recommendations based on the occasion, with the outfits determined from inventory in ecommerce stores as well as individual wardrobes.
You can videocall people using Google now
“We transfer the styling process from offline to online,” explains Jen Grebenshchikova, co-founder of SuitApp. “In the offline world you can’t always afford a stylist or spend time consulting one. Online it’s free and easy to use for everyone.”
The startup calls its recommendation algorithm the “Styling Fairy.” It’s been engineered with a combination of both human and machine intelligence, meaning it incorporates generic styling recommendations from actual stylists but understands individual preferences the more you use it.
Once you download the app and sign up, it’ll prompt you to input your gender, color preferences, and the kind of look you’re aiming for. Users can also take a selfie for the app to generate a personal avatar – with the result that you get a much better idea of how the clothes might look on you.
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SuitApp, which is accelerated at MaGIC, aggregates content from online stores Zalora and Lazada to come up with possible outfits. “There’s over 70,000 fashion items on Zalora alone,” explains Jen. “You might find something you like but it’s very difficult to find appropriate shoes and bags.”
The startup isn’t monetizing right now but the founders have already determined that the two avenues would be through affiliate marketing and promoted styles.
Too many clothes, too little time
Elena Chuiko, co-founder of SuitApp, says the idea behind the startup came after many people in her circle complained about a lack of time to go to the mall or follow the latest fashion trends.
Her male friends, who lead busy lives as businessmen, faced an awkward dilemma: they needed to look sharp and presentable for meetings but couldn’t tear themselves away from the office to physically shop for clothes. At the same time, women wanted something quick and accessible on their phones.
“They were saying I wish there was an app where I can press a button and there are outfit suggestions and then the outfit is delivered to your doorstep,” recalls Elena.
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The founders, who are originally from Russia, understood this was a common problem faced by busy millennials. They chose to start up in Malaysia because of the vast Southeast Asian market and the tilt towards online shopping.
SuitApp is now firmly targeting Malaysia, Singapore, and Brunei as its core markets.
The app launched in June so it’s too early to talk about traction. However, it has managed to secure US$100,000 in angel funding so there’s a bit of breathing space. For the future it plans on adding more content from online stores, sharpening its AI recommendation engine, and acquiring users at scale.
This article originally appeared on Tech in Asia.