Lily AI
The semantic glue between product attributes and consumer search intent for enterprise retail.
AI-powered product discovery and smart merchandising for high-growth e-commerce.
Klevu is a sophisticated product discovery platform that integrates Natural Language Processing (NLP) and vector-based AI to revolutionize the e-commerce search experience. By 2026, its architecture has evolved into a 'Discovery Suite' that treats every search query as a multidimensional data point, utilizing semantic understanding to match shopper intent with SKU attributes in real-time. Unlike traditional keyword-only engines, Klevu employs a hybrid approach: combining high-speed keyword indexing with deep-learning-based vector search to ensure accuracy even with complex, long-tail queries. Its market position is defined by its ability to bridge the gap between AI-driven automation and human-led merchandising control. The platform provides a headless-first SDK and API ecosystem, making it a preferred choice for developers building high-performance PWAs and mobile apps on platforms like Shopify Plus, Adobe Commerce, and BigCommerce. Its 2026 focus emphasizes 'Self-Learning Search,' where the system autonomously adjusts product rankings based on click-through rates, conversion margins, and individual user behavior without requiring manual rule-setting for every synonym or typo.
Uses linguistic analysis to understand intent behind long-tail queries like 'dresses for a summer wedding under $100'.
The semantic glue between product attributes and consumer search intent for enterprise retail.
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.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
AI automatically tags products with missing metadata based on product descriptions and image analysis.
Allows shoppers to upload images to find similar products using computer vision embeddings.
A lightweight, framework-agnostic JS library for building custom frontend experiences.
Dynamically re-ranks products on category pages based on real-time inventory and margin data.
Reorders search results based on the individual user's previous browsing and purchase history.
Support for customer-specific pricing, volume discounts, and SKU-only search queries.
Shoppers often use descriptive language that doesn't match product titles (e.g., 'something for a rainy night').
Registry Updated:2/7/2026
Results are ranked by current stock levels and user preference.
Typing errors or slang often lead to no results, causing customer bounce.
Merchandisers want to prioritize items that are profitable but might not be top-sellers.