AI Data Platform for Enterprise

The NVIDIA Blackwell architecture provides powerful acceleration for AI workloads, optimizing data processing pipelines for agentic AI. These pipelines enhance ingestion, retrieval, and query workflows by delivering high-performance compute for large-scale AI models.

The NVIDIA BlueField-3 DPU accelerates data access across storage initiators, controllers, and targets, enabling multiple GPUs to efficiently share the same data stores. This optimizes data throughput and access for AI reasoning, reducing CPU overhead, enhancing data availability, and ensuring secure, efficient scaling of AI workloads.

Through RDMA Over Converged Ethernet (RoCE) adaptive routing and optimized congestion control, NVIDIA Spectrum-X accelerates storage performance by nearly 50 percent and reduces communication bottlenecks. With it, enterprises can efficiently scale AI applications while maximizing system utilization.

AI-Q, a new NVIDIA Blueprint, helps enterprises develop, profile, and optimize multi-agent systems that collaborate with other agents and analyze and create enterprise data at scale.

NVIDIA NeMo™ Retriever enhances enterprise AI with retrieval-augmented generation (RAG), combining optimized models, vector search, and multi-GPU acceleration to accelerate and scale data retrieval, improving LLM accuracy in real-time applications.

AI agents are the new digital workforce, revolutionizing business operations by automating complex tasks and collaborating to solve problems. Develop, optimize, and scale agentic systems with the new NVIDIA Blueprint.

NVIDIA Dynamo optimizes AI data movement and caching to scale inference, efficiently routing KV cache contexts to the best GPUs, memory, and storage locations for maximum performance and efficiency.

NVIDIA-Certified Systems are expanding to include enterprise storage, serving as the foundation for a new wave of AI data platforms. The new certification program validates storage systems that meet rigorous data requirements for enterprise AI deployments.