Lily AI
The semantic glue between product attributes and consumer search intent for enterprise retail.
Real-time AI personalization engine for search, merchandising, and product recommendations.
Findify is an enterprise-grade AI-powered search and personalization suite designed for high-growth e-commerce brands. By 2026, the platform has evolved from basic machine learning to a sophisticated real-time intent-prediction engine. It utilizes advanced Natural Language Processing (NLP) and vector-based search to understand customer intent beyond keywords, accounting for synonyms, typos, and semantic relationships. The technical architecture is built for high-scale performance, offering sub-50ms latency for search queries across massive catalogs. Findify's primary value proposition lies in its ability to automate the merchandising process through 'Smart Collections' and 1:1 personalization, which dynamically re-ranks products based on individual user behavior, historical data, and real-time trends. Positioned as a direct competitor to Algolia and Bloomreach, Findify differentiates itself through its deep native integrations with platforms like Shopify and BigCommerce, combined with a 'headless-first' API strategy that allows for seamless deployment across web, mobile, and IoT touchpoints. Its analytical layer provides deep insights into search patterns and conversion attribution, enabling data-driven decision-making for growth teams.
Uses embeddings to represent products and queries in high-dimensional space, enabling context-aware results.
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.
Reranks search results and collection pages based on the individual's current session behavior and historical preferences.
Automatically manages the sorting and filtering of category pages using AI-driven ranking algorithms.
Allows merchants to set 'global' and 'local' boosting/burying rules that work alongside ML rankings.
Provides instant search suggestions, product previews, and popular searches as the user types.
A drag-and-drop interface for manually overriding AI rankings for specific visual aesthetics.
Native capabilities to test different algorithms or UI layouts within the search experience.
Manually re-ranking hundreds of items to clear old winter stock is time-consuming and inefficient.
Registry Updated:2/7/2026
Standard search engines often provide poor, non-responsive results on mobile devices where screen real estate is limited.
Users often leave a site if their initial search returns 'Zero Results'.