Criteo (NASDAQ: CRTO), the global platform connecting the commerce ecosystem, today introduced its Agentic Commerce Recommendation Service, designed to power AI shopping assistants with accurate, relevant product recommendations built on Criteo’s commerce intelligence.
LLM platforms are rapidly evolving into AI shopping assistants, while retailers develop their own AI chatbots, influencing how consumers discover, compare, and purchase products online. As these AI-driven shopping experiences scale, AI assistants need a commerce-grade recommendation infrastructure that drives relevancy by accessing real shopping behaviour, not just publicly available product descriptions, to deliver the trusted and personalised results that consumers expect. This approach builds on Criteo’s previously published agentic commerce vision.
Built on Criteo’s commerce intelligence, its Agentic Commerce Recommendation Service delivered up to a 60% improvement in recommendation relevancy compared to third-party approaches based only on product descriptions in Criteo’s testing. This performance is enabled by the company’s unmatched scale of 720 million daily shoppers, $1T in annual transactions, and 4.5 billion product SKUs.
The service is available through Criteo’s Model Context Protocol (MCP) and directly connects AI-powered shopping assistants with merchant inventory, translating consumer shopping queries into curated, transaction-ready product recommendations. It enables AI assistants to surface the most relevant products for each individual consumer by applying real-world shopping and purchase signals that cannot be accessed through traditional crawling tactics.
How it Works: The Agentic Commerce Recommendation Service in Action
A shopping request: A consumer asks an AI shopping assistant for a product that matches their needs, preferences, and budget.
AI assistant query: The AI assistant queries Criteo’s Agentic Commerce Recommendation Service to identify relevant products.
Commerce intelligence-powered filtering: Criteo applies real-world shopping and purchase signals to filter and rank products based on what is most relevant for that individual consumer, considering nuances such as product popularity, availability, and user intent.
Curated results: Criteo returns a curated shortlist of product recommendations, rather than raw catalog data.
Personalized, easy consumer experience: The AI assistant reviews Criteo’s recommendations, presents the results, compares options, and can support add-to-cart or checkout within the agentic experience.
The Agentic Commerce Recommendation Service understands broad shopper intent and supports both exploratory and product-specific queries, delivering relevant product recommendations and expanding them with complementary items when appropriate.
“The real competitive advantage in agentic commerce will come from access to high-quality commerce data at scale,” said Michael Komasinski, chief executive officer of Criteo. “This service brings that intelligence into AI-driven shopping experiences in a way that works for the entire ecosystem, delivering relevancy for consumers while respecting retailer data, brand integrity, and platform trust.”
Criteo continues to test with a major LLM platform that began in 2025, while also expanding testing to additional LLM platforms, retailers, and brands. To learn more about how the Agentic Commerce Recommendation Service is powering the future of AI-assisted shopping, click here.
1 Based on internal testing of transactional data in January 2026, Criteo’s Agentic Commerce Recommendation Service demonstrated up to a 60% improvement in recommendation relevancy compared to third-party approaches based solely on product descriptions. Criteo defines relevancy as “the degree to which a product matches a shopper’s current intent, needs, and preferences, and therefore helps them progress toward a purchase.”
