ABSTRACT: Dell Technologies’ enhanced AI Data Platform establishes a unified foundation for the era of agentic AI and AI factories. Combining PowerScale and ObjectScale storage with Elastic for vector search and Starburst for federated analytics, Dell delivers a composable, hybrid data architecture that bridges cloud, core, and edge environments. New integrations like MetadataIQ and the PowerScale RAG Connector make unstructured data actionable for retrieval-augmented generation and generative AI workloads. Built on open standards such as Apache Iceberg and designed for interoperability with NVIDIA’s AI Factory ecosystem, Dell’s platform enables enterprises to operationalize AI faster, reduce data silos, and extract measurable business value—turning data infrastructure into the backbone of intelligent, hybrid enterprise systems.
A Foundation for the AI Factory Era
Dell’s message is clear: data platforms are the new infrastructure foundation for AI. As enterprises struggle to turn AI proofs-of-concept into production value, Dell’s approach begins with fixing the foundation, unifying data storage, management, and access across hybrid environments.
As I stated in our analyst Q&A:
“If you don’t have the right foundation to a house, the house will fall over. The same goes for AI. Without quality, accessible data across silos, you can’t get from POC to production.”
Dell’s AI Data Platform addresses that by integrating four architectural pillars:
- Storage Engines – PowerScale and ObjectScale provide unified file and object storage for unstructured and semi-structured data, with optimized performance for training, inference, and RAG (retrieval-augmented generation) workloads.
- Data Engines – Elastic powers vector and real-time search, while Starburst (built on Trino) enables federated analytics across hybrid data estates.
- Cyber Resilience – Dell integrates native protection and recovery into the platform to ensure trust and compliance in AI pipelines.
- Data Management Services – A composable control plane unifies governance, pipelines, and metadata to make the environment adaptable and agent-ready.
Why Now: From Data Chaos to AI Readiness
The timing of this platform refresh coincides with an industry pivot. After years of “AI experimentation,” enterprises are realizing that data readiness, not model complexity, determines AI success.
Fragmented data across multi-cloud and on-premises environments has stalled production AI adoption. The Dell AI Data Platform simplifies this by connecting storage, compute, and analytics engines under one operational fabric.
As Dell partner Maya HTT demonstrated, this unified foundation can produce tangible results:
- Aerospace design acceleration through faster model iteration and real-time data access.
- 3% efficiency gain in fuel consumption for shipping company CSL, driven by telemetry-driven AI insights.
These use cases showcase Dell’s ability to move AI from pilot to production, where ROI becomes measurable.
What’s New: From Storage to Intelligence
While Dell’s AI Data Platform builds on proven technologies, several 2025 innovations redefine its intelligence layer:
- Elastic for Vector Search & RAG – Delivers GPU-accelerated real-time search and semantic enrichment for generative AI workloads.
- Starburst Integration – Brings federated query capability across multi-domain data sources and open table formats (Apache Iceberg).
- MetadataIQ – Enables intelligent indexing of billions of files to accelerate AI pipelines.
- PowerScale RAG Connector – Streamlines retrieval-augmented generation workflows by tightly coupling unstructured storage with model retrievers.
Together, these updates make Dell’s platform AI-aware, not just AI-ready.
Composable, Not Constraining
A key differentiator for Dell’s approach is composability. Instead of locking customers into a single stack, Dell provides an opinionated architecture that supports plug-and-play data engines and frameworks.
As I noted during the discussion: “Dell’s special sauce is that aggregation and composability layer. It’s VxRail-style simplicity applied to the data platform, tight integration with optionality.”
This means organizations can start with Dell’s recommended stack, PowerScale, ObjectScale, Starburst, and Elastic, but maintain flexibility to swap in their preferred tools (Spark, Python frameworks, or custom AI models) as needs evolve.
That flexibility also future-proofs investments as the AI ecosystem shifts toward multi-agent architectures and domain-specific retrieval systems.
Tying It to Dell AI Factories
The AI Data Platform serves as the foundation layer of Dell’s AI Factory strategy, which was co-developed with NVIDIA. It connects directly into NVIDIA’s NeMo, NIM retrievers, and GPU-accelerated RAG workflows, forming an integrated AI operations stack.
This alignment brings three strategic advantages:
- Certified Interoperability – Dell storage is validated across NVIDIA’s AI Factory deployment models.
- Performance Acceleration – Unified file/object layers eliminate re-architecture between training and inference workloads.
- Simplified Deployment – Pre-tested blueprints reduce time-to-value for enterprise AI initiatives.
As NVIDIA’s Jensen Huang noted at GTC, Dell is now “number one at end-to-end integration,” a title earned by connecting infrastructure, data, and AI operations under one umbrella.
Unstructured Data as the AI Frontier
AI innovation is constrained not by computing but by unstructured data. Dell’s PowerScale and ObjectScale platforms directly address this challenge by enabling parallel processing, RAG integration, and flexible data movement, without the need to refactor existing architectures.
- PowerScale handles high-performance file workloads, which is ideal for model training and inference.
- ObjectScale provides S3-compatible object storage for massive data lakes.
This dual-engine design gives enterprises unified visibility across formats and seamless scalability, making it a critical enabler for multimodal AI that blends text, image, video, and sensor data.
Open by Design: Reducing Lock-In
Dell has leaned hard into openness in a market wary of vendor lock-in. The platform embraces:
- Apache Iceberg for open table formats.
- OpenAPIs for extensibility across analytics and AI ecosystems.
- Interoperability with third-party governance and catalog systems.
This strategy positions Dell as an ecosystem-first player, ensuring its platform can participate in broader data fabrics and AI supply chains.
I also mentioned that “Dell’s embracing of open standards means their platform can be part of any data system, reducing lock-in and future-proofing customer investments.”
Hybrid and Multi-Cloud Reality
Dell’s AI Data Platform bridges the divide as enterprises rebalance workloads between cloud and on-prem environments. Roughly 80% of enterprise data remains on-prem, often in mission-critical, high-ROI use cases.
By integrating hybrid control and cross-cloud interoperability, Dell enables AI workloads to run where the data lives, minimizing data movement costs and latency while maintaining compliance.
This positions Dell’s architecture as the data operating system for hybrid AI, powering agentic applications that require speed and governance.
Analyst’s Take: From Hype to Operational AI
Dell’s AI Data Platform exemplifies a broader market trend: AI success is shifting from model innovation to data operationalization. Enterprises that master unified data access, metadata intelligence, and hybrid orchestration will lead the next wave of AI-driven transformation.
Dell’s edge lies in its ability to deliver enterprise-grade composability, the same advantage that propelled VxRail to dominance in hyper-converged infrastructure. The company has translated that DNA into a platform that simplifies, secures, and scales AI data foundations.
In short:
- Dell is not just building infrastructure for AI; it’s engineering AI-ready infrastructure.
- Its partnerships with Elastic, Starburst, and NVIDIA create a multi-layered data ecosystem.
- Its embrace of open standards and hybrid architectures ensures long-term agility.
As AI factories evolve into the data centers of the future, Dell’s platform is well-positioned to be the foundation layer of enterprise intelligence.
Our ANGLE
The Dell AI Data Platform is more than a storage modernization story; it’s their blueprint for AI-native data operations. By unifying unstructured data, open standards, and composable services, Dell has redefined how it views data platforms’ role in AI infrastructure.
Enterprises seeking to operationalize AI without losing governance or flexibility should look at Dell’s platform not as a replacement for cloud services, but as a hybrid anchor that keeps data gravity, performance, and trust under control.
Dell’s hybrid AI Data Platform can potentially connect today’s infrastructure and tomorrow’s agentic systems. We see this as a pragmatic approach as Agentic infrastructure matures and morphs, leaving flexibility and composability as options.
Disclosure: TheCUBE is a paid media partner for Dell Technologies, the sponsor of theCUBE’s event coverage, Dell Technologies nor other sponsors have editorial control over content on theCUBE Research, theCUBE, or SiliconANGLE
