Powering AI Factories with NVIDIA Enterprise Reference Architectures

The next wave of enterprise productivity is being built on AI factories. As organizations deploy agentic AI systems capable of reasoning, automation, and real-time decision-making at scale, competitive advantage increasingly depends on the infrastructure that supports them. Success requires more than raw compute. It demands a scalable, predictable foundation that can orchestrate intelligent agents, manage data movement efficiently, and deliver consistent performance from pilot to production. AI factories powered by NVIDIA bring industrial-grade discipline to AI, changing infrastructure into a strategic engine for speed, reliability, and accelerated innovation. Infrastructure is one of the five layers of AI, and represents the foundation for AI factories. Building that foundation, however, requires more than selecting high-performance hardware. Enterprises need proven architectural guidance that removes integration risk, reduces time to deployment, and ensures performance at scale. NVIDIA Enterprise Reference Architectures (Enterprise RAs) provide that infrastructure guidance for on-premises deployments, defining how compute, networking, storage, software, and system components integrate into a production-ready AI platform. With Enterprise RAs, organizations can move from experimentation to scalable AI operations, producing tokens that drive intelligence and business outcomes at an industrial scale. The NVIDIA Enterprise AI Factory validated design completes the picture by curating a full stack of NVIDIA software and ecosystem partner software validated by NVIDIA, for enterprises to operationalize the AI factory for their agentic AI workloads. Based on NVIDIA-Certified Systems and built in collaboration with partners, NVIDIA Enterprise RAs power enterprises to deploy and scale on-premises AI factories. These RAs provide detailed, end-to-end guidance on everything from GPU count, memory, storage, networking, and observability, to full-stack integration, encompassing hardware, software, orchestration, and monitoring. Once server nodes are NVIDIA-Certified, they form the foundational building blocks for enterprise RA clusters. Enterprise RAs form the foundation of AI factories To get started with building AI factories, three NVIDIA AI Factory configurations can accelerate computing architectures: the NVIDIA RTX PRO AI Factory (with NVIDIA RTX PRO Servers), NVIDIA HGX AI Factory (with NVIDIA HGX-based systems), and NVIDIA NVL72 AI Factory (with rack-scale systems based on NVIDIA GB300 NVL72 platform). Each operates at different scales, infrastructure requirements, workloads, and performance objectives. Organizations can begin with the configuration and architecture that aligns with their immediate needs, and scale as AI ambitions expand. Mature AI deployments often include a blended portfolio of the mentioned AI factory configurations to optimize performance across a range of different inference, training, and visual computing workloads. NVIDIA RTX PRO AI Factory: The universal accelerator The NVIDIA RTX PRO AI Factory, based on 2-8-5-200 (CPU-GPU-NIC – E/W Bandwidth) reference configuration, delivers a modular, power-efficient foundation for enterprise AI. Built around NVIDIA RTX PRO Blackwell Server Edition GPUs, this architecture is optimized for small to medium model inference, fine-tuning, generative AI, visual computing, and industrial AI workloads. It enables enterprises to bring AI closer to core business workflows—supporting multimodal agentic systems, simulation, analytics, and rendering within a standard enterprise data center footprint. Each NVIDIA-Certified RTX PRO Server integrates up to eight GPUs, delivering high-performance AI compute within a flexible,…