DDN, recognized globally as a leader in AI data platforms, has announced a deepened collaboration with NVIDIA to support the company’s next-generation AI factory architecture revealed at CES 2026. Through this partnership, DDN is aligning closely with NVIDIA’s latest innovations, including the NVIDIA Rubin platform and the NVIDIA BlueField-4 DPU, to help enterprises and hyperscalers deploy and scale AI systems faster and more efficiently. Together, the two companies are tackling one of the most persistent challenges in AI infrastructure data bottlenecks that restrict performance, utilization, and overall time-to-value.

As generative and agentic AI workloads rapidly advance, organizations are pushing toward million-token context windows, distributed inference models, and highly data-intensive reasoning. Consequently, businesses are realizing that simply adding more compute power is no longer sufficient. Instead, success increasingly depends on how effectively data is moved, cached, secured, and delivered across GPUs, DPUs, networks, and storage layers. This shift has placed data efficiency at the center of AI performance and business outcomes.

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This is precisely where the combined approach of DDN and NVIDIA is making a measurable difference.

“AI factories succeed or fail based on data efficiency,” said Alex Bouzari, CEO and co-founder at DDN. “Our collaboration with NVIDIA is focused on a single outcome: ensuring that the world’s most advanced AI platforms powered by NVIDIA Rubin and BlueField-4 are fed with data at full speed, at full scale, and with predictable performance. When data intelligence is built in, customers see higher GPU utilization, faster inference, and dramatically lower operational friction.”

Moving beyond traditional accelerator-centric designs, the NVIDIA Rubin platform introduces a rack-scale AI factory architecture. This design tightly integrates CPUs, GPUs, DPUs, NVLink fabrics, and high-speed Spectrum-X Ethernet networking through a co-designed approach. At the same time, BlueField-4 enhances this architecture by offloading networking, storage, security, and infrastructure services from host CPUs, effectively creating a programmable operating layer purpose-built for AI at scale. Notably, the BlueField-4 data storage processor enables a new tier of high-speed key-value cache storage, supporting long-memory inference within AI factories.

Working closely with NVIDIA, DDN has engineered its AI data intelligence platform to operate natively within this unified architecture. As a result, customers can translate architectural innovation into tangible business outcomes. These benefits include GPU utilization rates reaching up to 99% in large-scale AI environments, a 20–40% reduction in time-to-first-token for long-context inference workloads, faster model deployment through streamlined data pipelines, and lower infrastructure overhead by minimizing CPU load and inefficient data movement.

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Furthermore, DDN’s platform is optimized specifically for NVIDIA Rubin and BlueField-4. By leveraging NVIDIA Spectrum-X Ethernet for Storage and NVIDIA DOCA-accelerated services, DDN enables exascale data access capable of feeding dense Rubin GPU configurations at line rate. Additionally, distributed KV cache tiering supports the NVIDIA Inference Context Memory Storage Platform, extending inference context beyond GPU memory while maintaining ultra-low latency. Network-integrated storage services and telemetry-driven data placement further ensure performance remains optimized as workloads evolve in real time.

Beyond performance gains, the collaboration also addresses operational and security challenges as AI moves from experimentation to production. Together, DDN and NVIDIA help enterprises secure AI data end-to-end, enforce multi-tenant isolation, gain real-time visibility into data access patterns, and reduce audit and compliance preparation time by up to 70%.

Ultimately, this partnership reflects a shared vision for the AI factory era one where compute, networking, and data operate as a unified system. By deepening its collaboration with NVIDIA, DDN is enabling organizations to transform AI infrastructure into outcome-driven AI factories that deliver results faster, at scale, and with confidence.

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