Dell Technologies has introduced new advancements to its AI Data Platform, aiming to help enterprises transform distributed, siloed data into actionable insights for faster, more reliable AI outcomes.
The Dell AI Data Platform is built around four key components: storage engines for smart data placement and movement, data engines for insight generation, built-in cyber resiliency, and comprehensive data management services.
Integrated with the NVIDIA AI Data Platform reference design, the architecture decouples storage from processing to eliminate bottlenecks and enhance workload flexibility.
At the core of the storage layer are Dell PowerScale and Dell ObjectScale, the platform’s storage engines designed for performance, security, and multi-protocol access. PowerScale delivers high-performance NAS capabilities optimized for AI workloads, with new integrations for NVIDIA’s GB200 and GB300 NVL72 hardware offering scalable management and reliable throughput.
ObjectScale, meanwhile, now supports a software-defined deployment option on Dell PowerEdge servers, boasting up to eight times faster performance than previous all-flash object storage.
New advancements in ObjectScale include S3 over RDMA, promising 230% higher throughput and 80% lower latency compared to traditional S3. Additional upgrades enhance small object efficiency, delivering up to 19% better throughput and 18% lower latency for 10KB objects, alongside deeper AWS S3 integration and bucket-level compression for improved developer workflows.
On the data processing side, Dell is expanding its data engines in collaboration with Elastic, Starburst, and NVIDIA. The new Data Search Engine, co-developed with Elastic, allows users to interact with data through natural language queries, enabling tasks like semantic search and RAG pipelines. Integrated with Dell’s MetadataIQ, it can search billions of files stored on PowerScale and ObjectScale, while tools like LangChain can leverage it to maintain up-to-date vector databases efficiently.
The Data Analytics Engine, developed with Starburst, supports unified data querying across diverse sources and introduces an Agentic Layer that uses large language models to automate documentation, generate insights, and embed AI directly into SQL workflows. It also includes governance tools for tracking and managing AI usage, along with the new MCP Server to support multi-agent and AI application development.
Additionally, Dell’s integration with NVIDIA cuVS introduces GPU-accelerated hybrid search capabilities that combine keyword and vector search for faster, on-prem AI insights and turnkey deployment.
Dell confirmed that PowerScale’s NVIDIA integrations with NCP validation are already available, while ObjectScale’s RDMA and software updates will roll out in December 2025. The first releases of the Data Analytics Engine Agentic Layer and MCP Server are planned for February 2026, with the Data Search Engine and NVIDIA cuVS integration coming in the first half of 2026.
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