Dell unveils major AI Data Platform upgrades with NVIDIA & Elastic
Dell Technologies has announced advancements to its AI Data Platform aimed at helping enterprises eliminate data silos and improve performance and scalability for AI workloads through storage upgrades and enhanced partnerships with NVIDIA, Elastic and Starburst.
The Dell AI Data Platform is structured to enable organisations to convert fragmented data into actionable insights. The new updates focus on boosting both storage engines and data engines across Dell's offerings, catering to the increasing need for reliable, scalable AI infrastructure as enterprise AI adoption grows.
Storage engine upgrades
Dell PowerScale, the platform's network-attached storage component, now integrates with NVIDIA GB200 and GB300 NVL72.
This integration delivers 16,000-plus GPU-scale with reduced infrastructure requirements - up to five times less rack space, 88% fewer network switches, and up to 72% lower power consumption compared to competing solutions. Additionally, Dell PowerScale F710 has received NVIDIA Cloud Partner certification for high-performance storage.
Dell ObjectScale, described as the top-performing object platform, is available as both an appliance and a new software-defined option on Dell PowerEdge servers, offering speeds up to eight times faster than previous all-flash generations. ObjectScale now includes S3 over RDMA support, in technical preview from December 2025, promising up to 230% higher throughput, 80% lower latency, and 98% lower CPU usage versus traditional S3. Enhancements for small object performance provide up to 19% improved throughput and 18% reduced latency for deployment of 10KB objects. Integration with AWS S3 and bucket-level compression is intended to ease the task of storing and accessing large datasets.
Data engine enhancements
Alongside these storage developments, Dell has rolled out new and improved data engines.
In partnership with Elastic, Dell's Data Search Engine enables users to interrogate data using natural language, supporting workflows such as retrieval-augmented generation (RAG), semantic search, and generative AI pipelines. Integration with MetadataIQ allows for granular searches of billions of files on PowerScale and ObjectScale, with compatibility for tools like LangChain, helping to keep workloads efficient and databases current.
The Data Analytics Engine, developed in collaboration with Starburst, now features an Agentic Layer that uses large language models to turn raw data into business-ready assets within seconds. The platform offers enterprise-level AI model monitoring and governance, giving teams control over access and use. The Data Analytics Engine unifies queries across spreadsheets, databases, lakehouses, and more, expanding the range of available insights.
Dell's integration with NVIDIA cuVS adds GPU-accelerated hybrid search - combining keyword and vector approaches - to the Data Search Engine, providing faster and more efficient insights while maintaining on-premises control for data security. The combined solution aims to deliver a turnkey approach to scaling GPU-powered search as enterprise use cases expand.
Collaborator perspectives
"AI is transforming industries and its success depends on unlocking the full potential of enterprise data. The Dell AI Data Platform is purpose-built to simplify data complexity, unify pipelines and deliver AI-ready data at scale," said Arthur Lewis, president, Infrastructure Solutions Group, Dell Technologies. "From real-time diagnostics in healthcare to predictive maintenance in manufacturing, Dell Technologies and trusted collaborators like NVIDIA, Elastic and Starburst are empowering industries to move from AI pilots to production faster and with reduced risk."
Justin Boitano, Vice President of Enterprise AI Products at NVIDIA, commented, "AI finally gives enterprises a way to transform fragmented data into a strategic, scalable asset. Accelerated by NVIDIA AI, the Dell AI Data Platform delivers a new generation of intelligent storage that is designed to understand the meaning behind the data it holds."
Ajay Nair, GM of Platform Engineering for Elastic, highlighted the partnership's role in simplifying data access: "Data holds the key to incredible breakthroughs and our collaboration with Dell Technologies makes it easier than ever to unlock that potential. By fully integrating the Elasticsearch context engineering platform into the Dell AI Data Platform, we are providing a powerful engine for search and discovery. This collaboration empowers organisations to accelerate everything from semantic search to complex generative AI pipelines, turning large amounts of unstructured data into critical insight."
Justin Borgman, CEO of Starburst, said, "Access to all of your data is the foundation for enterprise AI success. Our expanded collaboration with Dell Technologies unites Starburst's data federation with Dell's AI Data Platform, giving organisations the ability to unlock insights from anywhere and accelerate their path to real-world AI outcomes."
Remi Duquette, Vice President of Industrial AI at Maya HTT, added, "The collaboration between Maya HTT, Dell Technologies and NVIDIA is transforming industries by turning massive amounts of unstructured data into actionable insights."
"From accelerating satellite production to enabling real-time telemetry and AI-driven efficiency for marine vessels, our solutions are not only connecting unconnected worlds but also driving sustainability and safety. With Dell PowerScale and NVIDIA AI infrastructure, we're delivering faster, smarter and more impactful AI outcomes for our clients."
Availability
Dell PowerScale with NVIDIA GB200 and GB300 integration and NCP validation is currently available.
Technical previews for Dell ObjectScale S3 over RDMA, and software updates, will begin from December 2025, while the first release of the Data Analytics Engine Agentic Layer and its MCP Server are slated for February 2026. The Data Search Engine and NVIDIA cuVS integration for the Dell AI Data Platform are expected to be available in the first half of 2026.
