NVIDIA AI Enterprise
12 use cases using this technology
Digital Bank Debunks Financial Fraud With Generative AI
bunq
European neobank bunq, with more than 12 million customers and 8 billion euros of deposits, built an automated, AI-powered transaction-monitoring system to detect fraud and money laundering, replacing labor-intensive rules-based systems with supervised and unsupervised learning. Using NVIDIA GPUs, bunq accelerated its data processing pipeline more than 5x and, using the open-source NVIDIA RAPIDS suite of GPU-accelerated data science libraries, trained its fraud-detection model nearly 100x faster, improving model accuracy and reducing false positives. Bunq is also exploring NVIDIA NeMo Retriever, part of NVIDIA NIM inference microservices, to improve the accuracy of Finn, its personal AI assistant powered by a proprietary large language model.
Terray Therapeutics uses NVIDIA DGX Cloud to train generative AI foundation models for small-molecule drug discovery
Terray Therapeutics
Terray Therapeutics leverages NVIDIA DGX Cloud and NVIDIA Base Command Platform to train COATI, a multimodal encoder-decoder foundation model for chemistry, reducing model training time from a week to a day and improving infrastructure utilization by over 4x compared to alternate cloud services.
WideLabs Justice Intelligence platform makes legal services more accessible for 8 million citizens in Rio Grande do Sul, Brazil
Public Ministry of Rio Grande do Sul (MPRS)
WideLabs built the Justice Intelligence platform for the Public Ministry of Rio Grande do Sul (MPRS) in Brazil, consisting of two AI agents — the TORI Investigation Assistant and the Archiving Intelligence Assistant — plus a Citizen Access Agent for the public. The platform uses NVIDIA NeMo Retriever for RAG pipelines, NVIDIA NIM microservices for deployment, NVIDIA NeMo Curator for document preprocessing, NVIDIA NeMo Customizer for domain-specific model tuning, and NVIDIA NeMo Guardrails for safety and consistency. The system went into full production in January 2025, serving more than 8 million citizens across 497 municipalities, and per MPRS deputy attorney general João Cláudio Pizzato Sidou, procedures that could last months or years can now be resolved or advanced in less than a day.
Accelerating the Radiological Workflow With AI at University of Wisconsin–Madison
University of Wisconsin–Madison Department of Radiology
The UW-Madison Department of Radiology uses NVIDIA DGX BasePOD with the MONAI imaging framework (integrated into Flywheel's healthcare data platform) and NVIDIA FLARE for federated learning to curate imaging datasets and rapidly iterate on AI models for tasks like pediatric bone age assessment and opportunistic screening. Ten thousand abdominal CT cases that previously took six to eight months to process manually can now be processed in a day; over one million images can be processed in under a day. The tools are being deployed via containers to a 21-site global clinical trial.
AT&T Drives AI Agents' Accuracy, Efficiency, and Performance With NVIDIA
AT&T
AT&T built 'Ask AT&T' customer service AI agents and worked with implementation partner Quantiphi to use NVIDIA AI Enterprise, NVIDIA NeMo and NIM microservices to build a data-flywheel platform for continuous fine-tuning and evaluation. The pipeline uses NeMo Curator to clean training data, NeMo Customizer to fine-tune base models (Mistral 7B was selected as optimal), NeMo Evaluator to measure performance (Rouge, BERT F1), and NeMo Retriever for up-to-date retrieval, with models deployed as NIM microservices. AT&T reports up to 40% improvement in response accuracy after fine-tuning and an 84% decrease in call center analytics cost, and is collaborating with Arize AI to automate identification of difficult AI interactions.
COMLINE launches GenAI-as-a-service based on HPE Private Cloud AI from German data centers
COMLINE SE
German IT service provider COMLINE SE is expanding its cloud offering with HPE Private Cloud AI, co-developed by HPE and NVIDIA, deployed within its existing GreenLake environment operated from data centers in Berlin and Frankfurt/Main. COMLINE's first generative AI project will use HPE Private Cloud AI to classify 1.6 million legal documents per day for compliance checks for a real-estate business customer, while ensuring data sovereignty from German cloud data centers. COMLINE will also use the solution to further automate its own IT operations.
BMW Group boosts production efficiency with NVIDIA DGX and generative AI
BMW Group
BMW Group uses NVIDIA DGX systems to train deep-learning-based synthetic data generation models that power SORDI (Synthetic Object Recognition Dataset for Industries), the largest open-source dataset for industrial AI with over 800,000 photorealistic images across 80 categories. DGX systems deliver an 8x boost in data scientist productivity and 4-6x improved performance over BMW's prior legacy systems; AI training for door-sill defect detection now takes under an hour using as few as five images, and the time required for employees to implement AI automation in QA tasks overall has been cut by more than two-thirds.
ThinkDeep's DeepBrain AI agents help automate public services for the French government
French Ministry of Economy and Finance
ThinkDeep AI developed DeepBrain, a multi-agent assistant platform for France's Ministry of Economy and Finance and Ministry of Defense, built on NVIDIA AI Enterprise (NIM, NeMo Retriever, NeMo Guardrails, Llama Nemotron models) running on-premises on NVIDIA DGX H100 systems to keep sensitive data within government infrastructure and comply with the EU AI Act. DeepBrain agents process millions of PDF documents, scanned images, schemas and videos for use cases including fraud detection and legal document processing. Document retrieval time fell from two days to two minutes, a typical 100-user deployment saves 1,000 work hours per month, and the Ministry of Finance has saved €2 million deploying DeepBrain at scale to 10,000 employees.
United Imaging Healthcare Enhanced the Speed and Quality of MR Imaging
United Imaging Healthcare
United Imaging Healthcare worked with NVIDIA since 2018 to accelerate its magnetic resonance (MR) imaging products with AI, developing an AI-assisted compressed sensing (ACS) technology to speed up MR image acquisition and reconstruction. Using NVIDIA data center GPUs, the CUDA Toolkit, cuSolver matrix computation library, and NVIDIA AI Enterprise software (with support from NVIDIA DevTech engineers and solution architects), United Imaging Healthcare reduced image reconstruction time by nearly 95%, with NVIDIA's support teams further accelerating algorithms by an additional 3x, on top of an initial 10x increase in computational speed from a tailored algorithm.
Boosting Innovation and Cutting Costs Through Lockheed Martin's AI Factory
Lockheed Martin
Lockheed Martin centralized compute resources, MLOps tools and best practices into the Lockheed Martin AI Factory, built on an NVIDIA DGX SuperPOD reference architecture, to build and deploy trustworthy AI at scale on-premises under strict data governance requirements. Developers can now get GPU-backed environments running in minutes instead of weeks, and training times dropped from weeks to days. The AI factory processes over one billion tokens per week and now serves 7,000 engineers and developers, supporting internal chatbots and coding assistants such as Lockheed Martin Text Navigator, and has consolidated 30+ models on-premises.
Nasdaq improves generative AI response times 30% with NVIDIA NeMo Retriever and NIM
Nasdaq
Nasdaq built a generative AI platform for internal chatbots and search, running NVIDIA NeMo Retriever and NVIDIA NIM microservices as part of NVIDIA AI Enterprise. After running four global hackathons to prototype AI applications, Nasdaq deployed self-hosted GPU embeddings on NVIDIA L40 GPUs, achieving 30% faster response times and 30% improved chatbot accuracy while reducing embedding costs.
Amdocs Builds Generative AI Agents for Telecom
Amdocs
Amdocs built amAIz, a domain-specific generative AI platform helping telecom companies transform customer experiences, automate processes and optimize decision-making, using NVIDIA DGX Cloud, NVIDIA AI Enterprise software, NVIDIA NIM inference microservices, and NVIDIA Nemotron open-source reasoning models. amAIz agents, enhanced with NVIDIA's Llama Nemotron, autonomously handle complex multistep customer journeys spanning sales, billing and care. Using NVIDIA NIM microservices and telecom-based retrieval-augmented generation, Amdocs reduced tokens consumed by as much as 60 percent for data preprocessing and up to 40 percent for inferencing, and reduced query latency by approximately 80 percent.