Dell Technologies leveraged GTC 2026 to reinforce its Dell AI Data Platform with NVIDIA, a proposal aimed at addressing one of the most common problems in enterprise AI: not so much the lack of GPUs, but the challenge of transforming dispersed, slow, or poorly governed data into useful fuel for AI agents and applications. The company introduced new data orchestration capabilities, acceleration with NVIDIA GPUs, and several storage innovations designed for agentic AI workloads.
Dell’s message is clear: many companies fail to deploy AI pilots not due to lack of models, but because their data remains trapped in silos, lacking sufficient structure, business context, or governance. In such scenarios, AI lacks reliable access to the information needed to reason, retrieve context, or act. Dell assures that its platform, integrated as part of the Dell AI Factory with NVIDIA, seeks to solve exactly this bottleneck.
The company accompanies the announcement with ambitious figures: up to 12 times faster vector indexing, 3 times faster data processing, and 19 times less time to the first token compared to traditional approaches. It’s worth viewing these numbers with caution, as they stem from internal Dell tests and comparisons defined by the vendor, but they illustrate where Dell wants to focus: on the data layer, not just inference or training.
An orchestration engine to transform business data into AI-ready datasets
The most strategic part of the announcement is the new Dell Data Orchestration Engine, described by Dell as a no-code/low-code engine capable of automating the entire data cycle for AI: discovering, labeling, enriching, and transforming structured, unstructured, and multimodal information into governed datasets ready for production. Dell adds that this layer is powered by technology from its recent acquisition of Dataloop, a clear indication of the platform’s future direction.
This engine isn’t limited to pipeline automation. Dell explains it combines active learning and human-in-the-loop workflows, aiming to improve dataset quality and model accuracy without losing governance control. Furthermore, the Data Orchestration Engine Marketplace will enable deployment of ready-to-use workflows supported by a curated library of NVIDIA NIM microservices, NVIDIA AI Blueprints, and over 200 models, applications, and templates.
Simultaneously, Dell has confirmed support for the latest NVIDIA AI-Q blueprint, an open NVIDIA standard for creating enterprise agents capable of perceiving, reasoning, and acting on corporate knowledge. NVIDIA’s official NVIDIA AI-Q announcement features it as a core component of their new agent software strategy, with a hybrid architecture combining frontier models for orchestration and open Nemotron models for research and cost reduction. Dell aims to embed this logic into its own data preparation and retrieval layers.
Conversational SQL and CUDA-X acceleration within the data platform
Another notable innovation is the introduction of an AI Assistant within the Dell Data Analytics Engine, designed to provide a conversational interface directly for SQL analysis. The goal is for business users to query, visualize, and collaborate on governed data products without relying heavily on expert-level SQL knowledge. Dell presents this as a way to democratize data access and speed up decision-making, especially in organizations seeking to deploy agents capable of autonomously querying structured data.
Additionally, data layer acceleration will be achieved using NVIDIA RTX PRO Blackwell Server Edition GPUs and CUDA-X libraries such as cuDF for structured processing and cuVS for vector indexing and search. According to Dell, this combo could deliver up to 3 times better SQL query performance and 12 times faster vector indexing. Still, these figures are based on internal testing and comparisons defined by the provider.
Storage solutions to prevent GPU idle time
Dell dedicates a significant portion of the announcement to storage, likely because it remains one of the current bottlenecks in scaled enterprise AI. The company states that when projects move from pilots to production, many traditional architectures leave expensive GPUs underutilized because storage can’t deliver data quickly or consistently enough. Their response involves Dell Lightning File System and Dell Exascale Storage.
Dell Lightning File System is presented as a parallel file system oriented towards AI training and inference, capable of up to 150 GB/s per rack. Dell claims its performance density surpasses several competitors of scale-out flash storage. Its main goal is to avoid bottlenecks and keep GPUs fed with continuous data. Dell Exascale Storage, on the other hand, aims to provide an integrated platform for AI and HPC that supports object storage, file systems, and parallel file systems over a common hardware foundation using Dell PowerEdge servers.
A highlighted feature is support for NVIDIA CMX context memory storage platform and the use of KV Cache in shared storage over PowerScale, ObjectScale, and Lightning File System. This is especially important for long-context agents and models: it enables downloading part of the KV cache from GPU memory to high-speed shared storage, preventing GPU memory exhaustion during long interactions or systems requiring extensive historical context. Dell describes this as crucial for agentic AI workloads with long reasoning chains.
This approach directly ties into yet another NVIDIA innovation showcased at GTC 2026: BlueField-4 STX, an architecture designed for accelerated storage targeting long-context reasoning in AI agents. NVIDIA claims that STX can deliver up to 5 times more token throughput, 4 times better energy efficiency, and 2 times faster ingestion compared to conventional systems. Dell counts among its partners those building on this modular architecture for storage and infrastructure.
Dell offers a complete solution, not just individual pieces
Beyond specific technologies, the announcement fits into a broader narrative. On March 16, Dell highlighted that its Dell AI Factory with NVIDIA has already accumulated more than 4,000 customers, with early adopters experiencing up to 2.6x ROI in the first year, according to a study by Enterprise Strategy Group. While promotional and based on modeled scenarios, it underscores Dell’s commercial thesis: delivering an end-to-end integrated pathway to move from AI pilots to full-scale enterprise deployments.
Within that framework, the data platform now plays a central role. Dell no longer aims to compete solely with servers and storage as standalone components but seeks to provide a layer that unites data orchestration, acceleration for prep and search, parallel storage, and agent architectures. Essentially, Dell promotes the idea that enterprise AI success hinges not just on the models, but on how quickly a company can turn its internal data into a governed, accessible, and scalable system.
Frequently Asked Questions
What exactly has Dell announced?
Dell introduced new capabilities for its Dell AI Data Platform with NVIDIA, including a data orchestration engine, GPU acceleration within the data layer, and new storage solutions optimized for AI and agent workloads.
What is the Dell Data Orchestration Engine?
It’s a no-code/low-code engine that automates the entire data cycle for AI: discovering, labeling, enriching, and transforming structured, unstructured, and multimodal data into governed datasets ready for AI deployment. It is supported by technology from Dell’s acquisition of Dataloop.
How does this relate to NVIDIA AI-Q?
Dell supports NVIDIA AI-Q, an open NVIDIA blueprint for building enterprise agents capable of perceiving, reasoning, and acting on corporate knowledge. Dell aims to integrate its data and storage engines within such agent architectures.
Why is Dell talking about KV cache in shared storage?
Because in long-context and agentic AI workloads, the KV cache can consume significant GPU memory. Dell proposes offloading part of this context to high-speed shared storage to optimize GPU utilization without compromising interaction continuity.
When will these innovations be available?
Dell indicates that the Data Orchestration Engine and its marketplace will launch in Q1 2026, the AI Assistant will arrive in the first half of 2026, Lightning File System is expected in April 2026, and Exascale Storage is anticipated in early the second half of 2026.
via: Dell