AI Compute & Silicon · nvidia.com
NVIDIA
141 verified customer use cases (96% with quantified ROI · Avg Value Score 93.3 · 100% with mapped architecture components).
- Verified stories
- 141
- Quantified ROI
- 96%
- Avg value score
- 93.3
- Industries served
- 17
- Distinct products
- 428
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 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 NVIDIA Sample Aug 13, 2025 Shell Shell needed a domain-specific AI assistant for chemistry and R&D knowledge, but its vast archive of scientific documents required data curation, domain adaptation, and faster training than generic RAG and open-source… 154,000 high-quality documents NVIDIA NeMo · NVIDIA NeMo Curator · NVIDIA NeMo Framework NVIDIA Sample Aug 13, 2025 Perplexity Perplexity needed to customize frontier models for a search experience that returns direct answers instead of links, but rapid model releases, high query volume, and the need for low latency and high throughput made… 20% improved over the base model on search Llama · Mistral · NVIDIA NeMo NVIDIA Sample Aug 13, 2025 Deloitte Consulting LLP Deloitte needed to integrate large multimodal biomedical datasets, train custom protein and chemistry language models, and assemble drug-discovery pipelines far faster than manual infrastructure work allowed, because… 12 million nodes and 97 million connection edge links in the Atlas AI graph AlphaFold2 · ESMFold · MegaMolBART NVIDIA Sample Aug 13, 2025 Perplexity Perplexity needed a production-grade inference stack for pplx-api that could serve open-source LLMs with lower latency, lower first-token delay, and lower operating cost while still scaling elastically across large GPU… $600,000 per year in savings NVIDIA A100 GPUs · NVIDIA AI Enterprise · NVIDIA H100 GPUs NVIDIA Sample Aug 11, 2025 Magna Magna needed to improve efficiency, safety and agility across its global manufacturing operations while also helping its autonomous delivery vehicle platform adapt to new cities and complex physical environments. City Delivery platform · NVIDIA Cosmos Reason · NVIDIA Omniverse simulation APIs and libraries NVIDIA Sample Aug 1, 2025 Nasdaq Nasdaq needed an enterprise AI platform that could search and retrieve business data quickly and accurately for internal and external use cases, but slow embeddings, high latency, rising costs, and accuracy issues… 30% faster response times NVIDIA AI Enterprise · NVIDIA L40 GPUs · NVIDIA NIM NVIDIA Sample Jun 11, 2025 Trend Micro Trend Micro needed to bring its domain-specific Cybertron cybersecurity LLM into production quickly while preserving self-hosting, data sovereignty, auditability, and secure inference controls for enterprise and… NVIDIA Enterprise AI factories · NVIDIA Universal LLM NIM Microservice · Trend Cybertron NVIDIA Sample Jun 11, 2025 Trend Micro Trend Micro needed a way to deploy its proprietary cybersecurity LLMs securely and quickly across cloud, hybrid, and on-premises environments while preserving data sovereignty, zero-trust controls, observability, and… AI-Q Blueprint · NVIDIA Enterprise AI factories · NVIDIA NeMo Data Flywheel NVIDIA Sample Jun 11, 2025 CoRover.ai CoRover.ai needed a scalable way to serve multilingual AI agents across India's 22 official languages while reducing latency, raising throughput, and meeting enterprise-grade security and compliance requirements for… 20%-25% higher output token throughput NVIDIA A100 Tensor Core GPUs · NVIDIA AI Enterprise · NVIDIA DGX NVIDIA Sample Archived · Jun 9, 2025 Bristol Myers Squibb BMS needed a shared AI environment that could help scientists reason over huge biological, chemical, imaging, and clinical datasets across global R&D, because isolated compute and manual analysis slowed target… 400-fold higher protein expression for an mRNA and protein generative model NVIDIA AI Enterprise · NVIDIA BioNeMo Agent Toolkit · NVIDIA DGX SuperPOD NVIDIA Sample Apr 30, 2025 Skyrim.AI Skyrim.AI needed to deliver real-time, broadcast-quality spatial media for sports, but volumetric capture from dozens of cameras created interoperability, reconstruction, networking, and data-throughput challenges that… 120 frames per second Atlas platform · GPUDirect Storage · NIM