Dell AI Data Platform Advancements Unlock the Power of Enterprise Data to Accelerate AI Outcomes
Story Highlights
- Dell AI Data Platform advancements help customers break down data silos to unlock deeper business insights and accelerate AI outcomes
- Dell PowerScale and Dell ObjectScale, the Dell AI Data Platform’s storage engines, deliver enhanced performance and scalability for demanding AI workloads
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Deepened collaborations with NVIDIA, Elastic and Starburst expand
Dell data engines capabilities, enabling faster, real-time insights from structured and unstructured data
Why it matters
As enterprise AI adoption surges and data grows, organizations need a platform that can securely transform distributed, siloed data into actionable insights. The Dell AI Data Platform, a critical component of the
The platform, integrated with the NVIDIA AI Data Platform reference design, is powered by four core building blocks:
- Storage engines for smart data placement and seamless data movement
- Data engines to turn data into actionable insights
- Built-in cyber resiliency
- Data management services
Together, they create a scalable, flexible foundation for customers to realize AI's full potential.
Dell AI Data Platform storage engines deliver peak AI performance
Dell PowerScale and Dell ObjectScale, the Dell AI Data Platform’s storage engines, offer the performance, security and multi-protocol access essential for AI data.
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Dell PowerScale delivers NAS (network-attached storage) simplicity and parallel performance for AI workloads like training, fine-tuning, inferencing and retrieval-augmented generation (RAG) pipelines.
- With new integration of NVIDIA GB200 and GB300 NVL72 and ongoing software updates, Dell PowerScale delivers reliable performance, simplified management at scale and seamless compatibility with applications and solution stacks.
- PowerScale F710, which has achieved NVIDIA Cloud Partner (NCP) certification for high performance storage, delivers 16k+ GPU-scale with up to 5X less rack space, 88% fewer network switches and up to 72% lower power consumption compared to competitors. 2
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Dell ObjectScale, the industry’s highest-performing object platform, 3 provides extremely performant, scalable S3-native object storage for massive AI workloads. ObjectScale is available as an appliance or through a new software-defined option on Dell PowerEdge servers that is up to 8 times faster than previous-generation all-flash object storage. 4 New advancements improve ObjectScale’s speed, scalability and efficiency.
- S3 over RDMA support will soon enter tech preview. It will offer up to 230% higher throughput, 80% lower latency and 98% lower CPU usage compared to traditional S3.5
- Small object performance and efficiency improvements for large deployments deliver up to 19% higher throughput and up to 18% lower latency for 10KB objects.6
- Deeper AWS S3 integration and bucket-level compression gives developers and data scientists better tools to store, move and use large amounts of data.
Dell AI Data Platform data engines power real-time AI
- The new Data Search Engine, developed in collaboration with Elastic, speeds decision-making by allowing customers to interact with data as naturally as asking a question. Designed for tasks like RAG, semantic search and generative AI pipelines, it integrates with MetadataIQ data discovery software to search billions of files on PowerScale and ObjectScale using granular metadata. Developers can build smarter RAG applications in tools like LangChain with the engine, ingesting only updated files to save compute time and keep vector databases current.
- The Data Analytics Engine, developed in collaboration with Starburst, enables seamless data querying across spreadsheets, databases, cloud warehouses and lakehouses. The new Data Analytics Engine Agentic Layer transforms raw data into business-ready products in seconds, using LLMs to automate documentation, glean insights and embed AI into SQL workflows. It also unifies access to vector stores, enabling RAG and search tasks across Iceberg, Dell’s Data Search Engine, PostgreSQL + PGVector and more. Enterprise-grade AI model monitoring and governance helps teams track, audit and control AI usage. The new MCP Server for Data Analytics Engine enables multi-agent and AI application development.
- Dell AI Data Platform integration with NVIDIA cuVS delivers the next major leap in vector search performance and turnkey deployment for enterprise AI environments. The integration brings GPU-accelerated hybrid (keyword + vector) search to Data Search Engine, delivering faster, more efficient insights with full on-prem control. Powered by NVIDIA cuVS and Dell’s secure infrastructure, IT teams can enjoy a fully integrated, turnkey solution to deploy and scale GPU-powered search out of the box.
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
“AI finally gives enterprises a way to transform fragmented data into a strategic, scalable asset,” said
"Data holds the key to incredible breakthroughs and our collaboration with
“Access to all of your data is the foundation for enterprise AI success,” said
"The collaboration between Maya HTT,
Availability
- Dell PowerScale NVIDIA GB200 and GB300NVL72 integration with NCP validation is available now.
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Dell ObjectScale S3 over RDMA will be available in Tech Preview in
December 2025 . -
Dell ObjectScale software updates will be available in
December 2025 . -
First release of Dell Data Analytics Engine Agentic Layer will be available in
February 2026 . -
MCP Server for Dell Data Analytics Engine will be available in
February 2026 . - Data Search Engine in the Dell AI Data Platform will be available in 1H 2026.
- NVIDIA cuVS integration in the Dell AI Data Platform will be available in 1H 2026.
Additional Resources
About
Copyright © 2025 Dell Inc. or its subsidiaries. All Rights Reserved.
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IDC Semiannual Artificial Intelligence Infrastructure Tracker, 2024H1.
Feb 2025 . -
Based on
Dell internal analysis of NVIDIA-validated reference designs for 64 SU configurations that adhere to the NVIDIA Cloud Platform Reference Architecture specification for high-performance storage,August 2025 . -
Based on
Dell internal analysis of publicly available data as ofMar. 2025 .Dell performance is based on large object read throughput per node and cluster configurations configured with ObjectScale XF960 and Ethernet networking. Actual results may vary. -
Based on
Dell analysis comparing ObjectScale 4.2 on PowerEdge R7725xd toECS 3.8 on ECS EXF900 for object read performance,Sept. 2025 . Actual results may vary. -
Based on
Dell internal ObjectScale S3 over RDMA testing,May 2025 . Actual results may vary. -
Based on
Dell analysis comparing ObjectScale 4.2 to ObjectScale 4.1 for object reads and latency,Aug. 2025 . Actual results may vary.
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