VueTag uses computer vision and Natural Language Processing to extract data from images and text, and power a wide range of solutions. The platform includes solutions to assess the quality of product images and text, build and enrich product tags and metadata, and sort data to give assortment and catalog insights. The A.I. systems are able to process thousands of products in mere minutes - saving time and resources, while improving quality.
50%
increase in catalog accuracy for better search and discovery
27hrs
time saved per person
per week
689M
tags predicted
in 2020
*Observed on an average for VueTag customers across the globe
Map product attributes to tags and create titles, descriptions, and other text content with A.I. Use VueTag’s exhaustive vertical-specific taxonomy and build on it for custom requirements to standardise tags and manage your catalog classification efficiently.
The A.I. can extract data from both structured and unstructured sources present in a retailer's catalog.
When there is no data available, VueTag can predict data based on product images and other catalog information.
With every round of QA, the solution is able to register the feedback and learn based on that - becoming better with each use.
When provided with certain rules or guidelines, VueTag can assess data - both images and text - to check if they are compliant.
VueTag can sort and visualize catalog data in different ways for retailers to be able to make better decisions.
The VueTag dashboard allows users complete control over what needs to be done and easy way to review and QA.
The product can be integrated by retailers in a number of ways - from the dashboard, to APIs, to even integrating with their existing PIM system.
The A.I. can be customized with new tags and rules defined by the retailer based on their business goals and priorities.
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