Marqo

Marqo builds AI-native product discovery for retailers rather than bolting semantic search onto a legacy keyword stack. The core idea is that a shared, generic model does not understand your catalog: Marqo trains a dedicated model, MarqTune, on your real product data and shopper behavior using techniques like generalized contrastive learning, so relevance reflects what actually converts in your store rather than generic similarity.

Implementation is designed to be light. A single-line pixel starts capturing clicks, carts, and purchases, which both feeds the model and provides a dashboard of user interaction data. Deployment then happens through an API or one-click integrations with Shopify, Adobe Commerce, and Salesforce Commerce Cloud. The platform covers more than a search box: intelligent understanding handles semantics, typo tolerance, and multilingual queries; adaptive journeys shift between results, carousels, guided discovery, or conversational search; and strategic automation manages ranking, boosts, filters, and collections to reduce manual merchandising work.

The commercial pitch is measurable uplift. Marqo publishes retailer case studies citing double-digit gains in search revenue per user, conversion rate, add-to-cart rate, and revenue per collection, and positions image and multimodal search as an area where legacy search platforms fall short. It is aimed at enterprise commerce teams that treat discovery as a revenue channel and are willing to train and tune a model on their own data to get there. Pricing is quoted per engagement, so onboarding typically starts with a demo.