Read Now: Survey report reveals how research organizations are responding to rising AI workloads & GPU demand
The company also enhanced its collaboration with Nvidia amid new requirements for governance, security, and operational efficiency
DDN has updated its AI data intelligence platform to help businesses accelerate the deployment of agentic AI.
The enhancements focus on strengthening governance and security, reducing operational complexity, and maximizing GPU efficiency across enterprise-scale AI infrastructures.
The data intelligence and storage company pledged that these updates will introduce real-time observability, policy-based control, secure multi-tenant isolation, and AI-native data orchestration.
The features are designed for large-scale training, inference, and autonomous AI workloads, helping companies transition their AI initiatives from pilot phases to production environments while improving overall performance and investment returns.
DDN’s platform updates saw it align with Nvidia offerings, including the BlueField-4 STX architecture unveiled at GTC earlier this year.
The data intelligence firm tapped the reference architecture, which also leans on DOCA software stack components, like the recently unveiled Argus, to help enterprise customers scale secure AI environments for training and inference.
The vendor contends that the converged offering offers inline security, memory observability, and policy-based protection for AI-native storage and agentic AI workloads operating at scale.
Jason Hardy, VP of storage technology at Nvidia, said: “As enterprises move autonomous AI from pilot to production, a new class of secure, high-performance data infrastructure is essential to manage the massive, real-time demands of agentic workloads.
“Combining Vera BlueField-4 STX and DOCA security frameworks with DDN’s AI-native data intelligence platform enables enterprises to operationalize secure, scalable AI factories for training and inference at scale.”
DDN already provides data infrastructure for large-scale AI environments, sovereign AI deployments, hyperscalers, and enterprise systems globally.
Powered by Nvidia accelerated computing, DDN’s platform aims to help organizations operationalize secure AI environments by combining high-performance data orchestration and multi-tenant isolation with real-time services optimized for training, inference, vector databases, retrieval-augmented generation (RAG) pipelines, and autonomous workflows.
The announcement highlights a broader industry shift toward implementing AI security at the infrastructure level. This model ensures that policy enforcement and protection occur directly within the AI data path rather than depending entirely on traditional host-based defenses.
In another step to take advantage of the growing demand for AI infrastructure, DDN recently added capabilities to its Lustre platform that allow users to share key-value (KV) cache to boost AI inference workloads.
Unveiled at Google’s annual Next event in April, the offering, which DDN manages with the hyperscaler, employs a shared cache layer across inference clusters rather than keeping KV-cache in each server’s local memory. As a result, DDN and its hyperscaler helper claimed total inference throughput was improved by as much as 75%.
SDxCentral, 32-38 Saffron Hill, London, EC1N 8FH
Email. [email protected]
SDxCentral is a subsidiary of InfraXmedia
More from InfraXmedia: DatacenterDynamics – Data Center Nation – The AI Cities Summit
Leave a Reply