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NVIDIA NIM

NVIDIA NIM provides prebuilt, optimized inference microservices for rapidly deploying the latest AI models on any NVIDIA-accelerated infrastructure, including cloud, data center, workstation, and edge. NIM microservices come prepackaged with the latest AI foundation models, optimized inference engines, industry-standard APIs, and runtime dependencies in enterprise-grade software containers, and can be deployed with a single command and integrated with just a few lines of code.

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9published use cases
6industries
4countries on record
Generative AI
top AI capability

Evidence mix: High 9 · Medium 0 · Low 0 — bands are computed from each record's evidence signals.

Industry
Country

9 use cases

Financial ServicesPredictive AnalyticsGenerative AIConversational AI

Digital Bank Debunks Financial Fraud With Generative AI

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.

bunqNVIDIA GPUs · NVIDIA RAPIDS · NVIDIA AI Enterprise +2
ManufacturingLarge Language ModelsGenerative AIAgentic AICode Generation

MediaTek Accelerates AI Development With an AI Factory

MediaTek established an on-premises AI factory powered by NVIDIA DGX SuperPOD with NVIDIA Blackwell-based systems to accelerate enterprise AI efforts, including development of its Breeze series LLMs and a 480-billion-parameter traditional-Chinese model. The AI factory processes approximately 60 billion tokens per month for inference and completes over 24,000 model-training iterations monthly, training models exceeding 480 billion parameters within one week (versus 7-billion-parameter models in a week previously). Using NVIDIA NIM and TensorRT-LLM, MediaTek achieved a 40% improvement in inference speed and 60% increase in token throughput. NVIDIA Mission Control consolidated GPU provisioning and system monitoring, while AI-assisted code completion and an AI agent for chip design documentation reduced documentation time from weeks to days. NVIDIA Riva was integrated into NVIDIA DGX Spark for agentic voice control features like internet search, calendar and messaging.

MediaTekNVIDIA DGX SuperPOD · NVIDIA Blackwell · NVIDIA NIM +5
Government & Public SectorRetrieval-Augmented GenerationNatural Language ProcessingConversational AI

WideLabs Justice Intelligence platform makes legal services more accessible for 8 million citizens in Rio Grande do Sul, Brazil

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.

Public Ministry of Rio Grande do Sul (MPRS)· BrazilNVIDIA NeMo Retriever · NVIDIA NIM · NVIDIA NeMo Curator +3
TelecommunicationsAgentic AIGenerative AILarge Language Models

AT&T Drives AI Agents' Accuracy, Efficiency, and Performance With NVIDIA

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.

AT&TNVIDIA NeMo · NVIDIA NIM · NVIDIA AI Enterprise +1
Technology & SoftwareGenerative AIRetrieval-Augmented GenerationDocument Intelligence

COMLINE launches GenAI-as-a-service based on HPE Private Cloud AI from German data centers

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.

COMLINE SE· GermanyHPE Private Cloud AI · NVIDIA AI Enterprise · NVIDIA NIM +2
EducationConversational AILarge Language ModelsGenerative AI

University of Florida builds NaviGator AI platform on HiPerGator supercomputer using NVIDIA NIM and Nemotron

The University of Florida uses its HiPerGator supercomputer with NVIDIA NIM microservices and Llama NIM to power NaviGator, a suite of self-service AI tools including chatbots and a toolkit giving students, faculty, and staff access to proprietary and open-source models. The platform is a hybrid service combining on-premises HiPerGator infrastructure with AWS, Google Cloud, and Azure, built for cost predictability, data privacy, and on-premises control of sensitive research and student PII data. Key takeaways include nearly 24,000 unique users for NaviGator Chat, 1,500+ unique uses of NaviGator ToolKit (52% from university staff), and 20 LLMs available in NaviGator.

University of Florida· United StatesNVIDIA NIM · NVIDIA Nemotron · Llama NIM
Government & Public SectorDocument IntelligenceConversational AIGenerative AIAgentic AI

ThinkDeep's DeepBrain AI agents help automate public services for the French government

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.

French Ministry of Economy and Finance· FranceNVIDIA AI Enterprise · NVIDIA NIM · NVIDIA NeMo Retriever +4
TelecommunicationsGenerative AIRetrieval-Augmented GenerationAgentic AI

Amdocs Builds Generative AI Agents for Telecom

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.

AmdocsNVIDIA DGX Cloud · NVIDIA AI Enterprise · NVIDIA NIM +2