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Powering a new class of enterprise infrastructure for agentic AI.
The NVIDIA AI Data Platform is a customizable reference design that integrates NVIDIA accelerated computing into enterprise storage to centralize intelligent data handling and deliver AI-ready data while reducing latency, enhancing data security, and maximizing performance. These data platforms are built by enterprise storage leaders to improve the performance and accuracy of agentic AI workflows.
The NVIDIA AI Factory is the full-stack solution designed to manage the entire AI lifecycle and manufacture intelligence at scale, transforming raw data into insights. However, the data that fuels this factory is often unstructured, fragmented, and rapidly changing. By embedding GPU acceleration directly into the data path, NVIDIA AI Data Platform handles the complexity and rapid changes of your data as a background operation. This ensures your enterprise data is always AI-ready to fuel the AI factory and drive intelligent, real-time decision-making.
Look Inside the AI Data Platform
The NVIDIA AI Data Platform brings together enterprise storage, NVIDIA accelerated infrastructure, and NVIDIA enterprise software to speed up data extraction and retrieval processes while creating seamless connections between AI agents and your valuable business data.
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™ Ethernet accelerates storage performance by nearly 50% and reduces communication bottlenecks. With it, enterprises can efficiently scale AI applications while maximizing AI system utilization.
NVIDIA NIM™ is a set of easy-to-use inference microservices for accelerating the deployment of foundation models and keeping data secure. NVIDIA NIM is optimized for enterprise-scale inference.
NVIDIA NeMo™ Retriever enhances enterprise AI with retrieval-augmented generation (RAG). It combines optimized models, vector search, and multi-GPU performance to accelerate and scale data retrieval and improve large language model (LLM) accuracy.
NVIDIA cuVS is an open-source library for GPU-accelerated vector search and data clustering that enables faster vector searches and index builds, letting developers enhance data mining and semantic search workloads
Key Benefits
Transform enterprise storage systems to deliver AI-ready data.
- Real-Time and Accurate Insights - Continuous indexing of multimodal data for hybrid search and retrieval ensures AI applications operate on the most recent and relevant information.
- Turnkey Platform - Enterprise storage solutions from industry leaders fully integrate NVIDIA accelerated computing, networking, and AI software, delivering a turnkey AI data platform for enterprise deployment.
- All Data, AI-Ready - Untapped, unstructured data is made AI-ready with intelligent data handling that discovers, orchestrates, and connects information across agentic applications.
- Data Protection and Compliance - The zero-trust architecture and granular security policies safeguard enterprise data across every node. Encryption is accelerated for data at rest and in transit, and threats are detected in real time.
Why NVIDIA AI Data Platform with WWT?
WWT is the key executor of the NVIDIA AI Data Platform (AIDP) by combining deep storage expertise and strong alignment across the storage OEM ecosystem—including DDN, Dell, Everpure, NetApp, VAST Data, and WEKA. WWT holds modern data center expertise and hands-on data and software integration to turn reference designs into production-ready solutions. The result is a faster, lower-risk path to AI-ready data with repeatable delivery and optimized performance for agentic AI, enterprise RAG, semantic search, and VSS use cases.
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