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    Hyper-personalization in Apparel and Fashion Retail

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    Sold by: DataArt 
    DataArt provides accelerators and PoCs for Gen AI solutions tailored to E-commerce needs, focusing on the use cases described. One of the most demanding sectors in E-commerce requires a hyper-personalization approach in Apparel & Fashion. To illustrate our capabilities in Gen AI, we have selected StAIlist ME – a Gen AI-powered web-based utility for eCommerce stores. It helps users choose the right outfit based on reference images or style text prompts, providing personalized recommendations.

    Overview

    Challenge

    Online marketplaces offer an overwhelming range of clothing and accessories, making it difficult and time-consuming for users to find personalized outfits that fit their specific needs and preferences

    Solution

    StAIlist provides personalized fashion recommendations, ensuring users find outfits that match their specific needs and preferences such as style, size, occasion and others following the next steps:

    • Data Input: Users upload a photo with the desired outfit or write a prompt text explaining the way they want to be dressed (ex. Beach Party)

    • Request Conversion: SAIlist recognizes all provided data and shows the user outfits from the e-commerce shop assortment, according to the request

    • Finalization: Users implement filters to specify additional information regarding size, discount-only items etc. and can choose items and add them to the bucket.

    Highlights

    • The solution leverages Generative AI technology and is based on AWS's Claude model and can be easily integrated with modern eCommerce platforms
    • The solution is built as a public accelerator and can be tailored and enhanced based on the customer’s needs.

    Details

    Sold by
    DataArt 
    Categories
    Generative AI 
    Data Analytics 
    Implementation 
    Delivery method
    Deployed on AWS

    Pricing

    Custom pricing options

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