European retailers are using open models and physical intelligence across use cases — from a commerce platform cutting inference costs by 90% to to a fulfillment center where collaboration of different robotic fleets is simulated inside a digital twin.
Frontier Results With Open Models
Retail leaders and technology companies across Europe are using NVIDIA-accelerated open and frontier models to advance agentic commerce, digital product discovery and retail R&D.
Shopify post-trains open models to reach frontier-level accuracy at a fraction of the cost. Its engineers use the NVIDIA Megatron Bridge library for faster fine-tuning and NVIDIA NeMo RL for reinforcement learning. Shopify has post-trained NVIDIA Nemotron 3.5 Lightning for the GraphQL subagent integrated into Sidekick, Shopify’s AI assistant for merchants. The subagent retrieves store data for several Sidekick features, including Sidekick Pulse, which researches a merchant’s store and recommends ways to improve it.
On Shopify’s internal benchmark, the post-trained model surpasses a leading frontier model in accuracy while cutting serving costs by 90% and delivering responses 7x faster. Beyond Sidekick, NVIDIA CCluster vLLM inference optimization software helped Shopify achieve 4.5x faster performance and up to 12x lower inference cost across five additional use cases: catalog enrichment, merchant assistant, e-commerce shopping simulation, product taxonomy classification, and merchant and buyer recommendations.
Zooplus, Europe’s leading online pet retailer, with Infosys and NVIDIA technologies rebuilt its product discovery stack for the agentic era. A production ready prototype deployed inside Zooplus’ Amazon Web Services (AWS) environment achieved 86% search accuracy using the NVIDIA Nemotron Retriever library for semantic search and the NVIDIA Blueprint for retail catalog enrichment for generated, search-ready product attributes.
Photoroom results from its deployment with Vestiaire Collective, where its Image Editing API now standardizes every primary image, about 40,000 a day across 70 countries, at the point of listing. Listings processed by Photoroom sold at a 5% higher rate of liquidity, with 3% to 7% more unique views per product page. The pipeline runs on NVIDIA GPUs with TensorRT and Triton Inference Server, and NVIDIA Dynamo Snapshot can help users quickly respond to demand spikes.
Omi launched ProductDrop, a workflow that anchors every generated image to an approved digital twin, letting brands scale creative output across entire catalogs without introducing product errors. L’Oréal is using this approach, combining Omi’s digital twins with generated brand environments within its CreAItech program. Omi runs TRELLIS 3D asset generation on NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, speeding up inference by 10x and reducing pipeline latency by 4x.
In addition, L’Oréal is accelerating the discovery of the best ingredient combinations, moving from months of experimentation to hours of computational screening, with the integration of NVIDIA ALCHEMI into its research workflow.
L’Oréal is also testing this approach with CurieOS, Orbital Industries‘ operating system for science and engineering, using OrbMol-v2, its open source molecular simulation model. Integrated with the NVIDIA ALCHEMI Toolkit and powered by NVIDIA accelerated computing, OrbMol-v2 is five times faster than comparable models and delivers 21% lower error than the next-best model of its kind. This AI-based workflow enables researchers to identify the most promising ingredient combinations for solubilizing UV filters and optimizing performance before committing to laboratory testing.
Mirakl, a software company for intelligent commerce, runs open models on NVIDIA GPUs, both on its own infrastructure and through European cloud providers like Scaleway. This keeps its technology sovereign, avoids vendor lock-in and delivers the speed and scale its customers expect. Mirakl’s Catalog Transformer pairs fine-tuned open models with proprietary services and has onboarded more than 70 million products, turning messy vendor data into accurate, well-organized catalogs.
Physical Intelligence Enables Training in Simulation
NVIDIA physical AI, digital twins and open models help simulate retail environments, automate warehouse operations and deliver virtual try-on experiences for European retailers and fashion brands.
Otto Group advanced its autonomous warehouse under human supervision initiative — built with Reply on NVIDIA Omniverse libraries and running on Google Cloud — to the group’s largest fulfillment center in Haldensleben, Germany. New capabilities let logistics teams design, test and optimize warehouse operations entirely in simulation before any physical implementation.
ALLSIDES launched its 3D Digital Twin Factory: an automated pipeline that transforms physical objects into SimReady 3D digital twins in minutes, capturing sub-millimeter geometric accuracy, measured physical properties and fully relightable materials that maintain accuracy under any lighting condition. Those digital twins serve as the foundation for simulating entire store layouts in 3D, as well as for tracking products reliably throughout the shopping journey and at checkout regardless of ambient light. Built on NVIDIA CUDA, OptiX and TensorRT, the platform already serves brands including adidas, Amazon, Nike, Zalando and Zara.
CATCHES achieved production results from its RealFit deployment with AMIRI of conversion up 55%, add-to-cart up 80% and gross sales up 56%, all after seasonal adjustment against like-for-like styles. The company launched PredictiveFit, extending physics-based virtual try-on to retailers, as well as CASI, a personal fashion agent that shops, styles and sizes for customers over WhatsApp, powered by open weight models including NVIDIA Nemotron 3, built on NVIDIA Omniverse and the Newton Physics Engine.
Explore New NVIDIA Retail Blueprints at the Nebius Booth
At GTC Berlin, Nebius is showcasing three NVIDIA Blueprints for retail, all available in early access and running on Nebius infrastructure, accelerated by NVIDIA:
- Agent Harness for Employee Productivity: An agentic assistant that consolidates scheduling, task management, inventory alerts and operational insights for store managers.
- Inventory Simulation and Optimization: A blueprint that can help retailers reduce overstock and stockouts by modeling demand scenarios, testing replenishment strategies and optimizing stock levels before users need to commit in the real world.
- Agentic Finetuning Flywheel: A self-improving loop that uses agentic workflows to continuously generate training data, fine-tune open source models and feed real-world performance back into the next training cycle.
Request early access to the blueprints and learn more about NVIDIA technologies for retail and consumer packaged goods.
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