Kua.ai
The All-in-One AI Marketing Platform for E-commerce Growth and Content Automation.
The semantic glue between product attributes and consumer search intent for enterprise retail.
Lily AI is a leading enterprise-grade product attribute platform that utilizes advanced computer vision and natural language processing (NLP) to bridge the gap between how retailers describe products and how consumers actually search for them. By 2026, the platform has evolved into a comprehensive 'Intent Intelligence' layer, moving beyond basic tagging to understand subjective customer preferences—such as 'boho-chic' or 'minimalist architecture.' Its technical architecture is built on multi-modal deep learning models specifically fine-tuned for the fashion, home, and beauty verticals. The platform ingests raw product imagery and metadata, then automatically generates thousands of granular attributes that sync directly with PIM (Product Information Management) and search engines like Algolia or Salesforce Commerce Cloud. This semantic enrichment significantly reduces search abandonment, improves SEO rankings, and powers hyper-personalized recommendation engines by aligning the retailer's catalog with the idiosyncratic language of the modern shopper. Lily AI operates as a headless API or via native integrations, ensuring that every touchpoint in the customer journey—from social ads to checkout—is informed by the most accurate product data available.
Uses convolutional neural networks (CNNs) and vision transformers to identify objective (color, sleeve length) and subjective (style, occasion) traits from images.
The All-in-One AI Marketing Platform for E-commerce Growth and Content Automation.
Transforming legacy open-source e-commerce into autonomous AI-driven storefronts.
The lightweight, high-performance AI engine for rapid e-commerce deployment.
The world's first truly interactive AI web design assistant for high-conversion digital presence.
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Injects long-tail keywords and synonyms into search indexes, bridging the 'vocabulary gap' between merchants and customers.
Algorithms that categorize products by lifestyle usage (e.g., 'work from home', 'formal gala') rather than just physical categories.
Automatically pushes enriched attributes to Google, Meta, and Pinterest ad feeds to improve ROAS.
A dynamic dictionary that updates in real-time as new fashion and home trends emerge in social media and search data.
Leverages the granular attribute data to suggest 'visually similar' or 'stylistically compatible' items.
Analyzes correlation between attribute descriptions and return rates to identify sizing or description inaccuracies.
Customers search for 'summer wedding guest' but the retailer's search engine only recognizes 'dresses'.
Registry Updated:2/7/2026
Manual tagging of 5,000 new SKUs every month is slow and prone to human error.
Generic 'new arrival' emails have low click-through rates.