Vue.ai’s product tagging solution, VueTag, helps eCommerce retailers create detailed tags and product metadata in a matter of minutes - saving a lot of the time and cost involved in manual labour.
Trusted by over 150+ retailers across the globe
Vue.ai’s product tagging solution, VueTag, uses data extraction and data prediction to enhance product data. With AI, it extracts and enriches product data from structured or unstructured visual and textual inputs. The automated process is instant, learns from feedback, and can learn customized tags. It helps save manual effort, time, and resources.
Use VueTag's exhaustive vertical-specific taxonomy and build on it for custom requirements to standardise tags and manage your catalog classification efficiently.
Map product attributes to tags and create titles, descriptions, and other text content with AI.
Offer nuanced filters and categories as products are tagged across a wide range of attributes.
Rich product data with detailed tags that ensures that every search shows accurate results.
Detailed product tags along with relevant titles and descriptions ensure that shoppers make informed shopping decisions.
Vue.ai’s tags are SEO friendly, ensuring products are discovered when shoppers search for them on the web.
Map nuances in shopper preferences with deep product data and show them exactly the products they’d love.
For retail teams that curate products for different channels, detailed A.I. tags can help find relevant products and styles easily.
Standardize and enrich your product data with a consistent, domain-specific taxonomy for improved data integration, data retrieval, and data cleansing.
Automatically group products with similar attributes together for better product discovery, filtering and navigation.
Vue.ai’s ML tagging tool enables eCommerce retailers to structure and label product data efficiently. The tool can be used for building custom taxonomies and attribute structures based on business priorities. Through the tool, users can visualize the catalog spread and create AI models that can label, categorize and organize data at scale. Both the output structured product data and the trained models can be exported to fit into any existing systems.
*Observed for a European customer using Vue.ai’s tagging solution
Diesel observed faster product digitization in less time and a shorter go-to-market period with VueTag. They also saw a decrease in the effort taken to manually tag products and an improvement in the efficiency of product onboarding. The depth of the meta tags allowed enhanced search and detailed filters leading to better product discovery.
“Dedicated and supportive team that enhanced our journey.”
The initial onboarding was really smooth and efficient. Their team is very friendly and committed to our success - monthly performance reports + quarterly check-ins + being able to reach out via Slack are all very helpful.
Eileen Rizzo,
CIO, Ashley Stewart
We engaged with Vue.ai, which had the ability to actually reduce the headcount while increasing accuracy in increasing the throughput.
Anandamoy Roy Chowdhary,
Director of Technology,
Sequoia Capital India
The Vue.ai team is on a mission to put AI and intelligent automation in the hands of teams across the globe in ways that improve productivity and growth multi-fold.
Custom demos typically last for 30 minutes. In this time, you can expect to:
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The ultimate Excel alternative to build rich product data: AI Read how AI-powered systems extract and enrich retail product data.
READ BLOG POST »Creating and Enhancing E-Commerce
Product Data with AI
Find out how the global fashion brand Diesel fixed its product tagging challenges with VueTag
READ CASE STUDY »How Diesel uses AI to fix
their product data
How easily your product can be found, both within your site and through search engines, depend on your catalog’s metadata.
READ BLOG POST »Metadata: How Discoverable
Is Your Product
Diesel uses AI-powered product tagging to build customer-specific taxonomies while enhancing the quality and reliability of product data
Better process optimization, improved productivity,
and clarity in data with AI-powered tagging
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