Our Hyper-Tagging Engine technology is at Velou's core.

Weaving together AI, machine learning, natural language, processing, and computer vision, we’re able to significantly improve the product data and make it easier for shoppers to find what they want.

Image Analysis

First, we scan each image to single out the product and then analyze it to identify hundreds of variations of product features. The measurement from the waist to hemline tells us the length of a dress. The shape and curve of a neckline differentiates a t-shirt. We can increase the search attributes for an entire product catalog tenfold.

Dress Style: Fit & flare
Embellishment: Shirring, Pleats
Neckline: Surplice v-neckline
Closure: Belt, Concealed zipper
Sleeve Length: Short

Length: Midi length
Sleeve Style: Cap sleeves

Fabric: Silk
Color: Red
Occasion: Baby Shower, Brunch, Tea

Pattern: Floral
Price: $185

Color Analysis

Our AI-powered color analyzer identifies the various colors in the product, while ignoring any colors in the rest of the image. Then it prioritizes color tags based on the percentages present in the product. So when shoppers include a color in their search, they get accurate and meaningful results.

Text Analysis

We use Natural Language Processing to analyze the text in product descriptions and the existing metadata to develop a deeper understanding of the products and generate a thorough list of tags.

Style: Tote
Color: Cognac brown
Closure: Hidden magnetic snap
Pattern: Woven
Handle: 8" gold chain strap drop
Interior: Fabric lined, Interior zip
Material: Leather
Dimensions: 14 ½" x 11 ½" x 7"

Human Intelligence

Our AI models continually monitor for search accuracy. If something isn't performing as expected, one of our fashion experts will step in to manually improve the system's understanding of product features.


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