10131568Shades Digital Skin MatchClosedCollaborative R&DInnovate UKThe main motivation for our project stems from the glaring lack of inclusivity and representation within the dancewear industry. Despite the increasing diversity of dancers across the globe, most dancewear brands have not met the unique needs of dancers with diverse skin tones. This has left many dancers from global majority communities struggling to find dancewear that accurately complements their skin tone, hindering their confidence and limiting their ability to fully embrace their identity. Shades is a trailblazing UK brand that is revolutionising the dance industry by seamlessly blending cutting-edge technology with a commitment to inclusivity and representation. Our mission is to empower dancers of all skin tones to confidently embrace their unique identities and celebrate their diversity on the dance floor. Our innovative project focuses on developing a prototype of **skin match platform** that enables dancers to accurately match their skin tone with our dancewear products. At the heart of our project is the development of an immersive AR web feature that leverages AI, 3D journeys and rendering. This solution will allow dancers to virtually try on our dancewear and visualise how it looks on their unique skin tone, empowering them to make informed purchasing decisions and reducing the likelihood of returns due to mismatched shades. Recognising the lack of representation and inclusivity in the dance space, Shades is the first UK dance brand to offer four distinct shades of skin tone across all its products, including dance supports, in both child and adult sizes. This unprecedented level of shade diversity ensures that dancers from diverse ethnic backgrounds can find dancewear that accurately reflects their identity, fostering a sense of belonging and confidence on the dance floor. Our cutting-edge technology not only streamlines the development process, allowing for reduced production costs, and shorter time-to-market, but also promotes sustainability by minimising the need for physical samples and reducing product returns due to better-informed purchasing decisions.