AI
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Introducing CLEPR, our model for semantic understanding
At Criteo, retail media is about helping brands reach shoppers directly on retailers’ property, right at the digital shelf where purchase decisions are made. Through CMAX, our unified retail media platform, we connect advertisers to retailers’ audiences with Sponsored Products that appear alongside native results in onsite search and browsing experiences. In this context, the…
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Beyond the demo: Why agentic evaluation matters
Agentic systems powered by LLMs can be incredibly impressive in demos. With a few well-crafted prompts, they can demonstrate reasoning, calling tools, and solving complex tasks [1]. Demos are effective at showcasing what’s possible. Production environments, however, are where those capabilities are tested at scale and under real-world conditions. The same agent that performs perfectly…
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AdTech, culture, diversity, and AI: Notes from our latest Women In Tech Meetup
On a weeknight in Bucharest, Criteo opened the doors of its new tech hub for a Women in Tech meetup under a simple but clear theme: Driving Change in Tech. The agenda moved from a deep‑dive keynote on ad tech at scale to a panel about culture, diversity, and AI, and finally, networking. The result…
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Agentic AI Symposium 2026
A science‑fueled, multidisciplinary approach to Agentic AI Authors: Jean-Yves Franceschi & Mariia Vladimirova At the Criteo AI Lab, we believe that making AI both trustworthy and useful requires a continuous and open dialogue between scientists, engineers, policymakers, regulators, and industry leaders. As AI systems evolve from passive predictors to agentic systems capable of planning, using tools,…
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Our Experience at Snowcamp 2026
Ten years of the coolest dev conference in Grenoble 🏂 Authors: Nicolas Terreyre, Sylvain Dedieu, Arnaud Becquet, Nicolas Drufin, Nicolas Beaudouin, and Léo Gatellier For the fourth consecutive year, Criteo was proud to partner with the Snowcamp conference in Grenoble. Furthermore, we had the privilege of hosting the “Snowcamp Tremplin” at our Grenoble office last November,…
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Leveraging Commerce Data for Outcome-Based Relevancy in Agentic Recommendation Systems
TL;DR Most agentic commerce recommendation services today rely on content embeddings or mainstream LLMs (e.g., Claude, Llama, GPT). While effective for semantic understanding, these models are not grounded in real shopping behavior and are not optimized for commercial objectives such as clicks or conversions. In this article, we show that leveraging commerce data at both…
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My notes from GoTech World 2025
During the second week of November, I attended GoTech World, the largest B2B expo-conference in Central and Eastern Europe and my second tech event after DevCon earlier that month. I hadn’t planned to go, but I unexpectedly won an Instagram giveaway from Supertree, a coworking company that partnered with DevCon, so I embraced this opportunity!…
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Criteo Boosts Ad Performance with Latest AI Advancements
Abstract. Everyone talks about AI today, and it seems AI has become an off-the-shelf tool providing plug-and-play capabilities. However, when addressing the hardest problems, such as those arising in the Commerce Media and AdTech industry, things are far more complex and require advanced AI (more specifically, machine learning) expertise. In this post, we share the…
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Agents, APIs, and Advertising: Lessons From Engineering Our MCP Server
MCP, Model Context Protocol, has made quite some noise in the past year as it promises a simpler, user-driven, integration of tools into Large Language Models (LLMs). At Criteo, we believe that MCP will be key to empowering our clients and giving them the control to create and manage advertising campaigns in a new way:…
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The Future is Now: Key Insights from the AI Engineer Paris Conference
When I walked into the conference, there was a mix of excitement and unease in the air. Everyone seemed to sense it: we weren’t just talking about “what’s coming someday”, we were already living through a shift. The main idea came up again and again, in different words and contexts: we’re moving from writing code…