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Fabulyst solves the problem of manual tagging for fashion retailers. Fabulyst offers a deep-learning and computer vision(CV) based tagging platform where retailers can now very easily generate the quality tags and avoid the struggles of manual tagging. The platform creates textual content from catalog images based on design elements and trends for Fashion e-commerce websites. In the last 6 months, Fabulyst has processed over 600k images for ecommerce websites including Myntra.com. Fabulyst AI generates content for filters, search and SEO to enhance product discovery which leads to 10%+ incremental revenue.
Below are more details:
Product Filter data: Fabulyst tags the well-formed keywords that can be directly used as filters on product list pages. E.g. Bell sleeves, round neck, floral print etc.
Product performance with regards to SEO: Fabulyst taxonomy has been designed to boost the number of searchable tags on each product by upto 3X. These tags are mined directly from google trends. E.g. concert dress, back to 90s etc.
In-website search metadata: Fabulyst provides SDK/API based integration to improve the website search index by adding the popular thematic tags based on historical data. These collection of tags and phrases make products directly mappable to in-website real world search strings. E.g. casual dress for workwear, peplum black tops etc.
The key differentiator we have is proprietary tech that can quickly build upon prediction of trends that update every 30 days.