Breuninger invests in lifestyle and fashion product images venture autoRetouch

autoRetouch, an AI powered image editing platform for fashion and lifestyle brands, has secured seed funding of €3.2 million, with European apparel retailer Breuninger leading the investment. 

The startup moved out of beta late last year.

“Today, we offer the first commercial technology for fashion and lifestyle brands to efficiently speed up editing apparel images in bulk,” says autoRetouch co-founder and CEO Alex Ciorapciu.

“If you’re selling online, customer experience is everything. More and better product images drive higher conversion rates and lower return rates.”

Automatically edit fashion product images up to 90% faster with AI for only €0.10 per image (first 10 images are free). Create automated workflows for background removal, skin retouch, face cropping, PSD Export, dimension adjustments, new backgrounds, etc.

“Through autoRetouch, we’re unlocking a significant amount of value, currently lost due to inefficient image editing technology, by giving the editor more time to focus on the creative work that might be needed and moving the heavy lifting to the AI.”

“We’re also helping retailers and brands of all sizes maintain competitiveness, or even to start competing in a purely digital world.”

“As a retailer in a very dense and competitive online market, we have recognised the importance of a good technological solution to significantly minimise the time between the photo shoot and getting the images on the product sales page,” says Holger Blecker, CEO at Breuninger.

“When we saw what the autoRetouch team could do with apparel images, we knew they were doing something that was previously thought impossible in image editing.”

As part of the received funding, autoRetouch has expanded its team of data scientists and engineers from five to sixteen.

“We’re building a deeptech B2B platform adhering to a product design philosophy that results in a B2C like product experience,” says Ciorapciu.

“Very few other startups have built a similar level of R&D expertise in computer vision in such a short amount of time.”

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