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 Archived · Apr 25, 2025 AT&T AT&T needed to scale AI-powered customer-care agents without letting latency, operating cost, stale documentation, or model drift degrade the quality of service delivered across a massive and constantly changing support… 84% decrease in call center analytics cost NVIDIA AI Enterprise · NVIDIA NIM · NVIDIA NeMo Curator NVIDIA Sample Archived · Mar 19, 2025 Astellas Pharma Inc. Astellas needed to shorten early-stage drug discovery by predicting antibody properties and generating candidate molecular structures faster, but generic protein language models and conventional conformational screening… 2.4 billion sequences ESM-1nv · NVIDIA BioNeMo · NVIDIA DGX A100 NVIDIA Sample Archived · Mar 11, 2025 BMW Group BMW Group needed to scale industrial AI across quality assurance, production, and logistics, but limited training data, manual image labeling, and a lack of end-to-end lifecycle tooling slowed model development and made… 4–6X improved performance over prior legacy systems NVIDIA AI Enterprise · NVIDIA Base Command · NVIDIA DGX NVIDIA Sample Jan 27, 2025 University of Florida The University of Florida needed to close an AI skills and research-capacity gap across its colleges, but limited access to AI hardware, software, and AI-trained faculty made it difficult to give every discipline… $100 million in state funding for a new data center GatorTron · HiPerGator AI · NVIDIA A100 Tensor Core GPUs NVIDIA Sample Jan 21, 2025 Scaleway Scaleway needed a secure, scalable AI infrastructure that would let European customers train large models inside the EU while meeting data-sovereignty, privacy, and efficiency requirements. 1,016 NVIDIA H100 Tensor Core GPUs NVIDIA DGX H100 · NVIDIA DGX SuperPOD · NVIDIA H100 Tensor Core GPUs NVIDIA Sample Jan 17, 2025 National Informatics Centre NIC needed to reduce judicial backlog and improve accessibility in a court system with massive case volumes and many official languages, while giving judges faster ways to search and summarize legal material. 18,000 daily district court sessions NVIDIA AI Enterprise · NVIDIA DGX A100 Tensor Core GPUs · NVIDIA NIM NVIDIA Sample Jan 17, 2025 FPT Smart Cloud FPT Smart Cloud needed more natural, multilingual virtual assistants and more scalable employee upskilling systems, but high speech-synthesis training costs, long processing times, and the need for personalized… 100X improvement in speech synthesis model output in dimension and aptitude across 18 languages FPT AI Engage · FPT AI Mentor · Kubernetes NVIDIA Sample Jan 17, 2025 The Netherlands Cancer Institute The Netherlands Cancer Institute needed faster, higher-resolution cone-beam CT reconstruction so clinicians could adapt radiotherapy to a patient's current anatomy, but memory-heavy 3D reconstruction models and CPU-era… 14 minutes on the bare-metal RTX 8000 machine NVIDIA A100 80GB GPUs · NVIDIA AI Enterprise · VMware vSphere NVIDIA Sample Est. · Dec 8, 2024 Cohesity Cohesity needed to improve retrieval accuracy in its generative AI assistant so relevant enterprise documents were not missed before answer generation, especially in high-stakes use cases such as legal eDiscovery. Gaia’s errors were reduced by 13%. CUDA Python · NVIDIA A100 Tensor Core GPUs · NVIDIA NIM microservices NVIDIA Sample Oct 8, 2024 Lockheed Martin Lockheed Martin needed a secure way to scale generative AI across its U.S.-based workforce for code generation, data analysis, post-mission analytics, and question answering over production documentation without moving… more than 8,000 engineers and developers using AI Factory AI Factory · LMText Navigator · NVIDIA DGX SuperPOD NVIDIA Sample Archived · Oct 5, 2024 ControlExpert ControlExpert needed to process more than 18 million motor claims a year across 30-plus countries, but manual review of vehicle photos, documents, invoices, and fraud indicators slowed down insurers and made consistent… more than 30 countries NVIDIA AI Enterprise · NVIDIA Triton Inference Server · NVIDIA-Certified Systems NVIDIA Sample Archived · Sep 25, 2024 Amdocs Amdocs needed to help telecom providers automate complex customer and network workflows with domain-specific AI while lowering inference cost and latency enough for near-real-time production use. Reduced query latency by approximately 80 percent Llama Nemotron · NVIDIA AI Enterprise · NVIDIA DGX Cloud NVIDIA Sample Jul 3, 2024 United Imaging Healthcare United Imaging Healthcare needed to speed up compute-intensive MR image acquisition and reconstruction so hospitals could shorten scan times, improve image quality, and make MR procedures available to more patients. Further accelerated algorithms by 3X NVIDIA AI Enterprise · NVIDIA CUDA Toolkit · NVIDIA data center GPUs NVIDIA Sample Archived · Apr 21, 2024 Amgen Amgen needed to train custom protein language models on proprietary biologics data, but sparse public models, long screening cycles, and expensive post-training analysis slowed its ability to evaluate and optimize… 20 seconds per structure NVIDIA Base Command Platform · NVIDIA BioNeMo service · NVIDIA DGX Cloud NVIDIA Sample Archived · Mar 1, 2024 Baseten Baseten needed to offer customers a cloud inference platform that could scale from sporadic traffic to high-volume real-time demand while keeping cold starts, infrastructure costs, and operational complexity low. 2X inference performance boost for a customer's LLM deployment Amazon EC2 · NVIDIA A10 Tensor Core GPU · NVIDIA A100 Tensor Core GPU NVIDIA Sample Archived · Dec 10, 2023 BMW Group BMW Group needed to plan and reconfigure large factories years before production starts, but disconnected CAD tools, manual coordination, and expensive change orders made it hard for planners to collaborate and validate… Projected 30% savings from optimized factory planning and highly efficient processes FactoryExplorer · NVIDIA Omniverse · Omniverse Kit SDK NVIDIA Sample Archived · Oct 2, 2023 Amazon Amazon needed to correct misspelled product-search queries in real time so shoppers could find products quickly without sacrificing latency, throughput, or the time required to tune inference configurations for… 5X inference speedup Amazon Web Services (AWS) · NVIDIA TensorRT · NVIDIA Triton Inference Server NVIDIA Sample Aug 2, 2023 BEN Group BEN Group needed a scalable way to analyze huge volumes of media, creator, and audience data so brands could place product integrations and influencer spend more effectively while also detecting fraud and improving… 100,000 Instagram posts analyzed per week NVIDIA DGX A100 NVIDIA Sample Aug 2, 2023 RingCentral RingCentral needed a transcription platform that could handle hundreds of thousands of concurrent meeting users, different accents, specialized vocabulary, and noisy audio while still producing real-time results. 200,000 concurrent users NVIDIA DGX A100 · NVIDIA NeMo · NVIDIA Riva NVIDIA Sample Aug 2, 2023 CCC Intelligent Solutions Inc. CCC needed to train and iterate on large computer-vision models for insurance claims automation, but hybrid data movement, bursty GPU demand, and developer orchestration made it hard for data scientists to move models… 2X speedup in running data scientists' experiments NVIDIA AI Enterprise · NVIDIA Base Command Platform · NVIDIA DGX A100 NVIDIA Sample Aug 2, 2023 Hour One Broadcasters needed a faster and more affordable way to create premium video at high volume, but traditional studio production and human-presenter workflows were too slow and expensive for always-on, frequently updated… 100+ virtual humans NVIDIA CUDA · NVIDIA GPUs · NVIDIA RTX