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SIGGRAPH 2025: Dell Uses New NVIDIA and Elastic Capabilities to Boost Dell AI Data Platform
The Dell AI Data Platform, leveraging collaboration with NVIDIA and Elastic, is updated to support the full AI lifecycle, from data preparation to advanced AI inference and knowledge retrieval.
Key Highlights
- New strategic partnerships with Elastic and NVIDIA are a core part of the Dell AI Data Platform's enhancements, providing a comprehensive, integrated solution for customers.
- A new unstructured data engine, developed with Elastic, enables real-time access to large datasets, offering advanced vector search and intelligent retrieval crucial for AI applications.
- Dell's new PowerEdge servers, featuring NVIDIA's latest RTX PRO 6000 Blackwell GPUs, provide a high-performance and power-efficient foundation for enterprise AI workloads.
- The updated platform and new servers create a turnkey solution that accelerates AI development by eliminating the complexity of building and testing separate hardware and software systems.
- By handling unstructured data and providing an end-to-end platform, Dell gains a competitive advantage over rivals that offer fragmented or less integrated solutions.
The News
Dell Technologies, a provider of AI infrastructure, announced updates to the Dell AI Data Platform to help customers better support the full lifecycle of AI workloads from ingestion and transformation to agentic inferencing to AI-powered knowledge retrieval. For more information, read the Dell Technologies press release.
Analyst Take
Dell Technologies is updating its AI Data Platform to assist customers more effectively optimize their AI workloads. The enhancements target supporting the entire AI lifecycle, from data ingestion and transformation to running advanced AI inference and retrieving knowledge with AI agents.
Now the Dell AI Data Platform is designed to streamline the transition from AI experimentation to production by automating data preparation. The platform’s architecture uses specialized storage and data engines to connect AI agents to high-quality enterprise data. Dell is collaborating with NVIDIA and Elastic to expand these capabilities.
Through a new partnership with Elastic, the platform now includes an unstructured data engine with built-in GPU acceleration, enabling real-time, secure access to large datasets for tasks like advanced vector search and intelligent search. This new engine works alongside the platform’s other tools for structured data, large-scale data transformation, and fast, AI-ready storage.
Dell’s new PowerEdge R7725 and R770 servers, equipped with NVIDIA RTX PRO 6000 Blackwell GPUs, are designed to be the go-to computing foundation for enterprise AI. These servers offer a high-performance, air-cooled solution for a wide range of accelerated workloads, from virtual workstations to agentic and physical AI.
From my viewpoint, they are well-suited for running NVIDIA Nemotron and Cosmos models. The new NVIDIA GPUs deliver up to six times the performance for LLM inference and can support four times more concurrent users than the previous generation. Dell is also integrating the PowerEdge R7725 with its AI Data Platform to provide a turnkey solution that accelerates inferencing and semantic search for customers.
To manage the growing complexity of AI, businesses worldwide need powerful new infrastructure. Dell is meeting this demand by equipping its new 2U PowerEdge servers with NVIDIA RTX PRO 6000 GPUs, creating a highly efficient, accelerated platform for AI applications and storage built on the NVIDIA Blackwell architecture.
The Competitive Benefits of the Elastic Alliance
From my perspective, Dell gains immediate ecosystem credibility by co-developing its new unstructured data engine with Elastic. Elastic, with its core product Elasticsearch, holds several competitive advantages in the unstructured data and search market, particularly against rivals such as Apache Solr and OpenSearch. One key advantage is its unified, real-time platform that goes beyond traditional search. While many competitors focus on a single aspect, Elastic has built an integrated stack (ELK Stack: Elasticsearch, Logstash, Kibana) that combines data ingestion, powerful search, and rich visualization. This all-in-one approach simplifies the workflow for customers, allowing them to not only search but also analyze and visualize their data for a wide range of use cases, including observability, security analytics, and enterprise search, all from a single platform.
Another significant competitive edge is its advantageous performance for modern AI and search workloads. As enterprises increasingly rely on semantic search and vector embeddings to power their AI applications, Elasticsearch has innovated with a highly performant and scalable vector database. Benchmarks often show it outperforming competitors like OpenSearch in vector search, with the ability to handle large-scale, real-time queries. This, combined with its advanced features like hybrid search (blending traditional keyword search with vector-based semantic search), makes Elastic a compelling choice for companies that need to deliver fast, highly relevant results for their AI-powered applications.
Dell Directly Addresses Unstructured Data Needs of Customers
I see that unstructured data engines are essential for modern AI workloads because they are built to handle the vast majority of enterprise data. While traditional databases are well-suited for structured information like spreadsheets, an estimated 80-90% of all business data exists in an unstructured form, including text documents, images, and videos. AI, especially generative AI, needs this diverse information to learn and perform effectively, but it cannot process the data in its raw state.
To make this data useful, unstructured data engines automate the complex process of data preparation. This involves breaking down large files into smaller chunks, then converting that information into numerical vectors that capture the semantic meaning. The engine also enriches the data with metadata, making it easily searchable and ready for a wide range of AI applications. By streamlining these crucial steps, the engine ensures that high-quality data is consistently available for AI models.
These engines are also critical for delivering real-time performance and scalability. Unlike traditional databases, they are designed to manage petabyte-scale datasets and integrate with high-performance resources like GPUs. This infrastructure enables advanced search capabilities, such as vector search as well as semantic and hybrid search, which enable AI systems to retrieve information based on intelligent context and meaning, not just keywords. This performance and scalability provide the foundational layer needed for AI applications to run efficiently without being limited by data access or processing bottlenecks.
I find that enterprise data is growing exponentially and is mostly unstructured, yet only a small portion is currently ready for generative AI. To unlock the full value of this data, organizations need solutions that can continuously index content and convert it into embeddings for quick and accurate semantic search. As these AI workloads scale, the right infrastructure must streamline data preparation, unify access to data scattered across different systems, and deliver consistent, high-end performance.
Dell Technologies: Altering the AI Infrastructure Competitive Landscape
From my perspective, Dell’s new updates to its AI Data Platform provide a significant competitive advantage by offering a complete, pre-integrated solution for the entire AI lifecycle. Unlike many competitors who focus on a single piece of the AI puzzle, such as specialized hardware or software, Dell is delivering a comprehensive, turnkey platform. The deep, co-engineering partnerships with NVIDIA and Elastic are a key differentiator.
The new collaboration with Elastic provides a powerful unstructured data engine for real-time, AI-ready search and retrieval, while the ongoing work with NVIDIA ensures that the platform is tightly integrated with the latest GPU technology for exceptional performance. This combined effort creates a validated solution that removes the complexity and risk customers face when trying to build their own AI infrastructure from scratch, significantly accelerating their time to value.
The platform's ability to handle every stage of an AI workflow, from data ingestion and transformation to agentic inferencing and knowledge retrieval, positions Dell as a strategic partner for businesses looking to scale AI. The updates directly address a major challenge for organizations: making massive, unstructured data usable for generative AI.
By automating data preparation and unifying access to data silos, Dell helps customers move quickly from AI experimentation to production. This end-to-end, enterprise-grade approach not only simplifies deployment but also ensures the reliability, performance, and security needed for mission-critical AI applications, giving Dell an edge over competitors who offer fragmented, less integrated solutions.
Looking Ahead
I believe Dell’s collaboration with NVIDIA and Elastic is key to unlocking AI’s full potential by breaking down silos and simplifying access to enterprise data, The new updates to the Dell AI Data Platform are designed to meet the top most AI workload needs of customers including scaling AI with confidence and improving their business outcomes. The platform now streamlines the entire AI development and deployment process by improving how unstructured data is ingested, transformed, and retrieved. This turns massive, siloed datasets into reliable, high-quality, real-time intelligence for generative AI.
I expect that Dell can use its strategic alliances with NVIDIA and Elastic to significantly enhance the Dell AI Data Platform over the next 12 months. With NVIDIA, Dell can integrate new GPU technologies and software innovations as soon as they become available, ensuring its platform remains at the forefront of AI performance. This partnership enables Dell to offer validated, high-performance solutions that are optimized for the latest AI models, from training to inference.
At the same time, the collaboration with Elastic provides a crucial competitive advantage in data management and preparation. Dell can work with Elastic to further improve the unstructured data engine, adding more advanced features for vector search and intelligent real-time data retrieval. By tightly integrating these core capabilities, Dell can offer a more robust, end-to-end platform that automates the entire AI lifecycle and helps customers turn their massive, unstructured datasets into valuable business intelligence.
Ron Westfall | Analyst In Residence
Ron Westfall is a prominent analyst figure in technology and business transformation. Recognized as a Top 20 Analyst by AR Insights and a Tech Target contributor, his insights are featured in major media such as CNBC, Schwab Network, and NMG Media.
His expertise covers transformative fields such as Hybrid Cloud, AI Networking, Security Infrastructure, Edge Cloud Computing, Wireline/Wireless Connectivity, and 5G-IoT. Ron bridges the gap between C-suite strategic goals and the practical needs of end users and partners, driving technology ROI for leading organizations.