Google Cloud Sample Archived · Sep 2, 2025 Etsy ~80x increase in listings per theme with "algotorial curation" Nearly 90 million personalized shopping experiences for nearly 90 million shoppers 5% increase in visits and 3% conversion lift with SEO optimizations BigQuery · Gemini · Gemini platform 
NVIDIA Sample Sep 1, 2025 Innophore Innophore needed to predict protein-ligand interactions and off-target effects much earlier in drug discovery, but the scale of biomolecular computation made traditional CPU workflows too slow and too expensive for… 15 million new variants of SARS-CoV-2 AWS · AlphaFold · ESMfold 
Snowflake Sample Archived · Sep 1, 2025 RavenPack Delivering multi-petabyte financial data to clients across regions and clouds through FTP and ETL pipelines was too slow, siloed, and expensive for RavenPack's growing analytics and AI business. 14x lower egress costs AWS Bedrock · Bigdata.com · Egress Cost Optimizer 
Databricks Sample Sep 1, 2025 Steelcase Steelcase needed a better way to support AI-driven pricing recommendations and approval automation because manual pricing submissions across tens of thousands of deal scenarios were too slow and inconsistent to support… 1.5K+ Agent Bricks · Databricks Data + AI Platform · Delta Lake 
In-house Sample Aug 29, 2025 General Motors GM needed deeper visibility into supply-chain vulnerabilities and a stronger ability to anticipate, mitigate, and respond to supplier and facility disruptions after the semiconductor supply chain crisis exposed… over 18,000 global suppliers Risk Intelligence · SupplyAlert · SupplyHealth 
MongoDB Sample Archived · Aug 29, 2025 Avila Avila needed to transform fragmented grant documents and opportunity sources into a structured, searchable system that could help public-sector and nonprofit users find, understand, and draft grant applications faster. 100,000 grant opportunities indexed Anthropic · MongoDB Atlas · MongoDB Atlas Search NVIDIA Sample Aug 29, 2025 Siemens Healthineers Siemens Healthineers needed to speed up radiation-oncology model development and reduce the time clinicians spend contouring organs at risk so treatment planning could scale with rising cancer demand. 100 Gbps Mellanox InfiniBand network Mellanox InfiniBand · NVIDIA HGX-1 · NVIDIA HGX-2 NVIDIA Sample Aug 29, 2025 T-Mobile T-Mobile needed more accurate, lower-latency call transcripts so its Expert Assist software could recommend answers in real time without making customers repeat themselves in noisy service interactions. 10 percent higher accuracy NVIDIA A100 Tensor Core GPU · NVIDIA NeMo · NVIDIA Riva 
AWS Sample Aug 28, 2025 Volkswagen Group Volkswagen Group needed a standardized, resilient way to connect order intake, logistics, and manufacturing across its global factory network so it could deploy AI and production IT systems at scale, reduce the risk of… 114 production facilities worldwide AWS · Amazon SageMaker · Digital Production Platform (DPP) Databricks Sample Aug 28, 2025 Accuris Accuris oversees one of the world’s most extensive catalogs of electronic components, each component is enriched with structured and unstructured data such as parametric data, environmental attributes, pricing and… 10x Faster development velocity from vision to customer-facing features Agent Bricks · Apache Spark Declarative Pipelines · Databricks Data + AI Platform 
Huawei Cloud Sample Archived · Aug 26, 2025 Fengtu Technology Fengtu Technology needed to run GPU-heavy inspection and safety models in the cloud without wasting compute, while also improving fatigue detection and commercial-vehicle risk response for logistics customers. around 10% reduction in escort labor input DMS fatigue detection · FunctionGraph · ResNet image classifier 
IBM Sample Aug 25, 2025 Claims Connection Group Claims Connection Group needed to replace slow, fragmented and manual property-insurance claims handling so it could respond faster during disaster-driven spikes, interpret policy language more consistently, and reduce… 25-35% reduction in operational costs IBM Business Automation Workflow · IBM Robotic Process Automation · IBM watsonx NVIDIA Sample Aug 25, 2025 EEVE EEVE needed a practical personal robot that could autonomously handle lawn care and home security, make decisions in real time, and support continuous feature expansion without forcing customers to manage separate… over 2,500 EEVE robots deployed EEVE Robot Operating System (eOS) · NVIDIA CUDA Toolkit · NVIDIA Jetson Nano NVIDIA Sample Aug 25, 2025 Docusign Docusign needed to extract and operationalize data trapped inside agreements for its Intelligent Agreement Management platform, but CPU-based inference and fragmented serving infrastructure made it hard to scale… more than a billion people in over 180 countries Microsoft Azure · NVIDIA A100 Tensor Core GPUs · NVIDIA TensorRT NVIDIA Sample Aug 25, 2025 Vietnam Post and Telecommunications Group (VNPT) VNPT needed a high-performance traffic-monitoring system that could analyze thousands of camera feeds and hundreds of thousands of AI service requests to improve congestion management and road safety at busy… Reduced training time from weeks to days NVIDIA A30 · NVIDIA AI Enterprise · NVIDIA DGX A100 NVIDIA Sample Aug 25, 2025 Singtel Singtel needed to make its 5G enterprise offering compelling for AI-heavy customers, but real-time video analytics, AR/VR, and chatbot workloads required low-latency edge compute, shared GPU capacity, and… NVIDIA A40 GPUs · NVIDIA AI Enterprise · NVIDIA T4 GPUs NVIDIA Sample Aug 25, 2025 Kawasaki Heavy Industries Kawasaki needed to modernize railroad inspection and maintenance planning, but manual visual inspections, disconnected sensor data, and hand-built repair schedules made safety improvements and large-scale optimization… $218.4M saved per year Kawasaki Track Maintenance Platform · NVIDIA Jetson AGX Orin 64G · NVIDIA cuOpt NVIDIA Sample Aug 25, 2025 PacBio PacBio needed to raise the throughput and accuracy of its long-read sequencing instruments without increasing system footprint, power draw, or cost, but CPU-based base calling and consensus generation had become the… 1,300 human whole genomes annually at 30X coverage DeepConsensus · NVIDIA A100 Tensor Core GPUs · NVIDIA CUDA NVIDIA Sample Aug 25, 2025 Wealthsimple Wealthsimple needed a standardized way to deploy and serve machine-learning models for fraud, transaction routing, onboarding, and personalization, but framework-specific inference stacks were taking months to ship and… 145 million predictions NVIDIA A10G GPUs · NVIDIA AI Enterprise · NVIDIA GPU-Optimized AWS Machine Image NVIDIA Sample Aug 25, 2025 Tarteel.ai Tarteel.ai needed to give Muslims who are learning Quran recitation real-time, high-accuracy Arabic speech feedback even though many users do not speak Arabic and do not have easy access to qualified instructors. 4 percent word-error rate (WER) NVIDIA A100 Tensor Core GPU · NVIDIA CUDA Toolkit · NVIDIA NeMo NVIDIA Sample Aug 25, 2025 Microsoft Microsoft needed to deliver accurate live captions and real-time meeting transcripts in many languages for Teams while keeping inference latency low and compute costs under control at massive user scale. 28 languages Microsoft Azure Cognitive Services · NVIDIA GPUs on Azure · NVIDIA Triton Inference Server NVIDIA Sample Aug 25, 2025 Wellcome Sanger Institute The Wellcome Sanger Institute needed to analyze mutational signatures across large cancer datasets, but the non-negative matrix factorization workloads in its pipeline were so compute-intensive on CPUs that results took… 30X acceleration NVIDIA DGX-1 Server · NVIDIA NVLink · NVIDIA V100 Tensor Core GPUs NVIDIA Sample Aug 22, 2025 Siemens Energy Siemens Energy needed to automate leak and abnormal-noise inspections across complex power plants so sites would not depend on constant expert walk-throughs or full-time staffing for every inspection scenario. Hundreds of inspection types Model ensembles · NVIDIA GPUs on AWS · NVIDIA Triton Inference Server NVIDIA Sample Aug 22, 2025 Plabook Plabook needed to automate labor-intensive reading assessments so teachers could evaluate oral reading fluency and related literacy skills without spending hours on repeated manual running records. 75 percent of all fourth graders in the U.S. read below their grade level NVIDIA Riva · Plabook