NVIDIA Transforms European Retail, From Digital Discovery to Physical Operations

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.

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.

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.

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.

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.

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.

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.