Tag: agentic

Dell AI Factory with NVIDIA Delivers Proven Path to Enterprise AI ROI

Dell Technologies marks the two-year anniversary of the Dell AI Factory with NVIDIA by announcing advancements across its AI data platform, end-to-end AI infrastructure, and AI solutions and services portfolio that help enterprises move AI from pilot to production at scale. With over 4,000 customers deploying the Dell AI Factory, and early adopters seeing up to 2.6x ROI within the first year, Dell proves that an end-to-end approach delivers measurable business results.

Why This Matters

The enterprise AI landscape is undergoing a fundamental shift. As AI code assistants and agentic workflows drastically lower the cost and time to build custom applications, CIOs are increasingly choosing to develop AI capabilities in-house, on-premises—driving the need for owned infrastructure.

Yet unclear ROI remains the top obstacle preventing AI deployments at scale. Two years of the Dell AI Factory with NVIDIA has revealed three critical requirements for achieving measurable returns: data platforms that make enterprise information AI-ready, infrastructure that seamlessly scales the latest innovations efficiently from pilot to production, and solutions and services that compress time to value by simplifying deployments and accelerating ROI. Dell is the premier provider delivering all three with NVIDIA technology at the core, creating a proven path from AI investment to business outcome.

Three Capabilities That Define Enterprise AI Leadership

As the top AI infrastructure provider, Dell’s AI infrastructure portfolio—the industry’s broadest—delivers integrated capabilities across data, infrastructure, solutions and services.

Data platforms that turn institutional knowledge into AI fuel

AI is rapidly shifting from assistive tools to autonomous, agentic systems, but its effectiveness is constrained by the data it can access, trust and act upon. The Dell AI Data Platform with NVIDIA addresses this challenge with a unified platform for AI that combines Dell’s high-performance storage, modular data engines, and NVIDIA accelerated computing, networking, software and CUDA-X libraries. As the data foundation of the Dell AI Factory with NVIDIA, it handles workloads from retrieval-augmented generation (RAG) and multimodal search to agentic workflows and large-scale data processing. Advancements announced today make it faster and easier for companies to turn data into real AI results.

Infrastructure that enables AI workflows from desktop to data center

Dell’s next-generation infrastructure supports AI workflows at every stage, from rapid prototyping to production deployment at scale.

For desktop AI development and autonomous agents:

For production AI at scale:

  • PowerEdge XE9812 is Dell’s flagship liquid-cooled server leverages the NVIDIA Vera Rubin NVL72 platform for massive real-time training and inference.
  • PowerEdge XE9880L, XE9882L, and XE9885L are liquid-cooled servers featuring NVIDIA HGX™ Rubin NVL8 designed to accelerate validated AI performance within existing data center footprints and power constraints.

For enterprise workloads in the data center:

For high-performance networking and emerging technologies:

  • Dell PowerSwitch SN6000-series are NVIDIA Spectrum-6 Ethernet switches with 1.6Tbs, liquid cooling and co-packaged optics options for Vera Rubin-based Dell platforms.
  • PowerSwitch SN5610 and SN2201 now offer expanded network OS choices including Cumulus Linux and Enterprise SONiC Distribution by Dell Technologies.
  • NVIDIA Quantum-X800 InfiniBand Q3300-LD liquid-cooled switches deliver high-bandwidth networking for AI and cloud-native workloads.
  • Dell Integrated Rack Scalable Systems (IRSS) expands to include Dell PowerSwitch and NVIDIA liquid-cooled switching, providing unified, rack-level power and cooling management for AI infrastructure.

NVIDIA NVQLink and NVIDIA CUDA-Q support – Dell is the first OEM to integrate NVIDIA NVQLink with CUDA-Q across PowerEdge servers featuring NVIDIA AI infrastructure, allowing enterprises and research institutions to explore emerging quantum-classical computing use cases. These capabilities accelerate discoveries in advanced drug development and materials science simulations by combining the processing power of Quantum Processing Units with NVIDIA accelerated computing for quantum systems control and error correction on a trusted foundation of Dell PowerEdge servers.

Solutions and services that accelerate deployment and prove ROI

Updated Dell AI Solutions combine new modular architecture with Dell Automation Platform blueprints and NVIDIA AI Enterprise software to deliver enterprise outcomes while simplifying operations and reducing deployment complexity. New services bridge skill gaps and scale deployments from experimentation to production.

 

Accelerating enterprise AI workloads:

  • Knowledge assistant provides the foundation for designing, deploying and managing intelligent assistants, working with industry leaders like Aible, Cohere’s North and NVIDIA.
  • ClearML blueprint improves agentic AI environments for enterprises with secure, efficient GPU cluster management and workload scheduling.
  • Agentic AI platform, in collaboration with Cohere’s North, DataRobot and NVIDIA allows enterprises to securely deploy and manage AI agents with orchestration, governance and observability.
  • Dell Accelerator Services for Agentic AI provide packaged capabilities to support businesses at any stage, from experimentation and validation to enterprise-wide integration, closing skill gaps and reducing technical complexity.

 

Simplifying AI infrastructure deployment:

  • Dell AI Factory with NVIDIA modular architecture offers a clear, simplified path to enterprise AI by addressing deployment complexity, managing rapid technology change and supporting continuous adoption. Integrated automation gives organizations the flexibility to start at the right size and scale as needs evolve.

 

Michael Dell, chairman and chief executive officer, Dell Technologies: “Two years ago, enterprises were asking how to access AI technology. Today, they’re asking how to make their data AI-ready, how to operationalize AI at scale and how to prove ROI. The Dell AI Factory with NVIDIA answers all three questions. We’re brought in from the start as a trusted advisor, helping customers navigate their entire AI journey—from turning raw data into AI fuel, through deployment and to measurable business outcomes.”

Jensen Huang, founder and chief executive officer, NVIDIA: “AI infrastructure is being built everywhere — every company will be powered by it, every country will build it— and it demands integrated data platforms, scalable infrastructure and deployment expertise. Dell Technologies delivers all three, with NVIDIA at the core. The Dell AI Factory with NVIDIA is a proven infrastructure blueprint for every phase of AI powering the next industrial era.”

Availability

  • Dell Pro Precision 5 and 7 Series mobile workstations with NVIDIA RTX PRO Blackwell GPUs will be available in May.
  • Dell Pro Precision 9 T2/T4/T6 will be available in May.
  • Dell has shipped Dell Pro Max with GB300 to select customers in March 2026, with plans to ship more broadly in the coming months.
  • Dell PowerEdge XE9812 will be globally available 2H 2026.
  • Dell PowerEdge XE9880L, XE9885L will be globally available Q3 2026.
  • Dell PowerEdge R770, R7715 and R7725 with NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs are globally available now.
  • Dell PowerEdge M9822 AND R9822 will be globally available in September.
  • Dell PowerSwitch SN6000-Series will be globally available starting in July.
  • Dell SONiC with Spectrum-based PowerSwitch SN5610 and S2201 will be globally available in March.
  • NVIDIA Quantum-X800 Q3300-LD will be globally available by Dell Technologies in Q4 2026.
  • Dell PowerEdge NVIDIA NVQLink and CUDA-Q integration is available now.
  • Knowledge assistant is globally available now.
  • Agentic AI platform with Cohere’s North and DataRobot are available now, agentic AI platform with ClearML will be available in March.
  • Dell AI Factory with NVIDIA modular architecture will be globally available in April.
  • Dell Accelerator Services for Agentic AI are available now.

Meet Amazon Quick Suite: The agentic AI application reshaping how work gets done

Quick Suite helps you cut through the noise of fragmented information, siloed applications, and repetitive tasks to focus on what matters.

Key takeaways

  • Quick Suite is AWS’s agentic AI application that helps employees transform how they find insights, conduct deep research, automate tasks, visualize data, and take actions across apps.
  • Quick connects to your information across internal repositories like wikis and intranets, popular applications, AWS services like S3 and Redshift, and access integrations with MCP to connect to 1,000+ apps.
  • Ask any question and get insightful answers.
  • Battle-tested by tens of thousands of Amazon employees and dozens of customers, you can use Quick for tasks consumer AI shouldn’t handle.

Read more below

We’ve all experienced how AI can transform our personal lives, but this same experience hasn’t been unlocked at work—yet. Consumer AI solutions aren’t connected to all your business data. They don’t have access to the tools you need to get things done at work. And many organizations won’t even let you use consumer offerings, because they lack critical security and privacy features.

That’s why we invented Amazon Quick Suite. It’s the AI experience people love with the security and privacy enterprises trust. Quick is your AI teammate that collaborates with you to get work done. With Quick, you can ask questions and get detailed answers, conduct deep dive research, analyze and visualize data, and create automations for workflows to save time and let you focus on the big picture. And thanks to the enterprise-grade security and privacy standards, Quick can work across all your information, so you finally get the fully featured gen AI experience you want at work, while knowing your queries are never used to train a model.

With Quick, we are entering a new era of work. Interact with Quick through an intuitive, web-based experience or integrations across your browser, Office 365, and more. Working with an AI agent is now as simple as chatting with a teammate. Make a request, ask a question, or automate a task. Quick works with you to help you go from insight directly to action. To see these capabilities firsthand, watch my video overview of Amazon Quick Suite.

We’ve been testing Quick with employees across Amazon and key customers to ensure it’s up to the demands of today’s workplace, and the results speak for themselves. Amazon employees are turning tasks that used to take days into minutes, automating the development of critical reports, and building their own benches of personalized agents. Propulse Lab, a leading marketing automation company, used Quick to streamline their customer service workflows, reducing the average time spent handling tickets by 80%—with a planned expansion of this workflow, they predict they will save over 24,000 hours annually. Based on the results they’ve already seen with Quick, DXC Technology, a global provider of information technology services, is planning to deploy it across more than 120k users, while Vertiv, a provider of critical digital infrastructure, plans to scale their users by more than 25% in 2026.

So how does Quick Suite work?

Bring everything together with Quick Index and Spaces

Quick Index makes it simple for you to connect to the sources and applications that matter. With over 50 built-in connectors for applications like Adobe Analytics, SharePoint, Snowflake, Google Drive, OneDrive, Outlook, ServiceNow, Databricks, Amazon Redshift, and Amazon S3, Quick brings together all your data securely to ensure you have full context for every decision. Using integrations with OpenAPI or Model Context Protocol (MCP) customers can connect to custom resources and 1,000+ apps by taking advantage of popular MCP servers from Atlassian, Asana, Box, Canva, PagerDuty, Workato, Zapier, and many more. You can then add additional files, dashboards, and other information to dedicated Spaces for you and your team to collaborate.

Ask questions and build agents

Once you’ve connected your data to Quick, you can start interacting with the chat assistant. You can ask Quick to write and send communications for you, or if you want Quick to write in your style or for a particular task (like writing a case study), you can use natural language or point Quick at existing guides or documentation to create a custom agent able to communicate in your intended style.

Analyze and visualize data with Quick Sight

Quick Sight makes business intelligence accessible to everyone with a new agentic experience, helping you gain insights to make better decisions. Unlike traditional business intelligence tools that work only with databases and data warehouses, Quick Sight’s agentic experience analyzes all forms of data across all your systems and apps, including your documents.

For example, a marketer can now easily look at a dashboard of their campaign data with metrics and customer feedback and ask questions in natural language about how the campaign is performing. They get a crisp analysis of the data in seconds without hours of manual statistical analysis, compiling sentiment from feedback, and summarizing the findings into a narrative—no business intelligence or data science experience required.

Dive deep into complex questions with Quick Research

Quick Research is the most accurate and reliable research agent on the market, ready to answer your most in-depth questions. It’s like having your own personal Ph.D. to provide comprehensive answers and reports to questions that require extensive research. It uses sophisticated analysis capabilities and extended processing to dive into your company’s data, and the public internet, including real-time information from 200+ outlets like The Associated Press, The New York Times, Washington Post, and Forbes. Quick Research can turn weeks-long research projects into quick-turn results, all with fully cited sources you can trust.

We tested Quick Research on DeepResearch Bench, a comprehensive benchmark for evaluating research agents, using a collective jury, where it provided the most accurate and reliable research across a range of tasks. The Last Mile Delivery team at Amazon used Quick Research to assess the potential impact of new legislation on a particular country that had been previously enacted in other countries. In 30 minutes, Quick Research delivered an in-depth analysis of how this legislation impacted other countries and their associated partner organizations, while also providing details on references and research methodology. This sort of research previously took multiple team members two weeks to complete.

Streamline repetitive tasks with Quick Flows

We all have those routine tasks, like compiling weekly reports or preparing for a recurring meeting, that take up your time every week. Quick Flows helps you use simple prompts to create automated workflows that handle repetitive tasks, reducing errors and freeing you and your team from busy work. For example, a program manager at AWS created a Flow to report on new, in-progress, and closed Asana tickets from the past week, compare them against the previous week’s status and committed items, and generate an executive summary email for leadership, saving multiple hours of manual work each week.

Handle complex multi-system workflows with Quick Automate

When these processes get complex and require hundreds of steps to be securely executed across multiple enterprise systems, like insurance claims processing or onboarding a new employee, teams wish that these tasks could be streamlined, but they lack the sophisticated automation tools and expertise to do it. With natural language prompts or by simply using existing documentation for their standard operating procedure, Quick Automate coordinates even the most complex business workflows across multiple applications, systems, or departments.

For instance, the Amazon Finance team uses Quick Automate to reconcile thousands of invoices every month. Quick Automate pulls information across multiple external transportation management systems, cross referencing this content with internal data from Amazon systems to help teams forecast cashflow, identify payment blockers, and conduct root cause analysis. The team built this automation without a dev team in days instead of weeks, and Quick made it easy to scale across multiple teams. Customers, such as Kitsa, have found the computer use agent in Quick Automate to be the most accurate solution for browser automation, helping them reliably automate their most complex and sensitive workflows across applications at scale.

Quick works wherever you are. With an intuitive web application, extensions in popular browsers like Chrome and Firefox, and extensions in Microsoft Outlook, Teams, and Word, Quick helps you find answers and act immediately in your flow of work.

Quick Suite is already transforming work for Amazon employees and customers

Quick serves people across every department and role—from sales reps to marketers, to CEOs and CIOs, to engineers and IT. Employees across Amazon, along with customers like Vertiv, DXC, 3M, Jabil, dLocal, Propulse Lab, and Kitsa, are already seeing amazing results with Quick:

Research in high gear

Jessica Gibson, vice president and associate general counsel at Amazon, sees an enormous benefit using Quick Research to help the Legal, Public Policy, and Compliance departments keep up with shifting global requirements that impact their business. From a single prompt, Quick Research helps her team synthesize complex requirements for specific geographic regions and provide recommendations at remarkable speed. “This same task used to require many hours of outside counsel, research, and writing,” said Gibson. By using Quick Research to compile these reports, her team can “stay agile while optimizing both time and resources.”

Automations that work

Kitsa, a customer that builds software to help expedite clinical trials, used Quick Automate to pore through hundreds of webpages and found that they were able to analyze sites for clinical trials in days that previously took months—with a 91% cost savings. “Compared to similar offerings like Manus and ChatGPT Operator, we achieved the highest accuracy and data coverage for our use case,” said Rohit Banga, the company’s co-founder and CTO.

Data-driven business decisions

Robbie Wright, a senior product marketer at AWS, uses Quick Flows to build a repeatable workflow to draft monthly business reviews based on business metrics from Quick Sight, campaign performance reporting from Adobe Analytics, and content from emails, and other internal documents. This saves time and helps his team make more informed decisions about ongoing campaigns faster.

“The workflow makes it simple to combine multiple sources into a concise update for our leaders,” Wright said. “I can now complete these projects 90% faster, and the quality of my reports has improved dramatically because I spend less time chasing numbers and more time providing my own insights.”

An AI-driven transformation

Jabil, a global leader in engineering, supply chain, and manufacturing solutions, is embracing Quick so that employees can use natural language to research regulatory updates across key industries faster and to optimize account collections and request for quote (RFQ) submissions. The automations in account collections and RFQs alone are expected to save about $400,000 annually as a result!

“The multi-tier AI architecture powered by Quick consolidates chatbots and information sources, increasing our manufacturing speed and flexibility,” said May Yap, Jabil’s CIO. “As part of our AI-driven transformation, these unified capabilities are helping us drive efficiencies and operational excellence.”

Complex workflows made simple

Natalie Fischbeck works in business development on Amazon’s Workforce Staffing team, and in one week she built 39 customized AI agents using Quick to help her complete complex tasks in minutes.

“Quick has given me the opportunity to create an accessible hub of institutional knowledge that would otherwise be scattered,” she said. “We now have scalable, logic-based agents that track all our leads and solutions at a high level. Because they pull from all our most recent emails and documents, they can provide dynamic updates almost instantly.”

Beyond productivity: A whole new way of working

What strikes me about these examples isn’t just the time saved—it’s how Quick is fundamentally changing our relationship with work. It’s removing the busy work that used to consume valuable time and energy and gives us the time back to focus on what matters. It brings together all the data, metrics, and institutional knowledge you need to make decisions, and helps you act on these decisions to drive outcomes.

We’ve been blown away by all the creative ways people have used Quick so far, and we’re excited to see how others will use it in the future. There are so many possibilities to dig into with these tools, and our team is hard at work finding ways to make them even more useful for customers in the future.

Understanding Agentic AI: The New Autonomous Frontier

Agentic AI represents the next frontier in artificial intelligence innovation where autonomous agents work together as a team. Although agentic AI is in its early stages, it has the potential to help enterprises achieve remarkable gains in productivity, efficiency, and scalability by eliminating inefficiencies and seamlessly scaling an organization’s collective skills. With AI agents, enterprises can gain a competitive advantage by delivering insights faster and making strategic decisions more effectively.

Neil Bowden, Director of Data Analytics & AI, Dell Technologies Ireland tells us more below

AI lessens the burden of using complex tools and dissolves siloes by augmenting human capabilities. Now, employees can contribute more meaningfully to specialized tasks with the assistance of AI. Teams working with AI are three times more likely to be in the top decile of performance than individuals working with AI or teams working without AI.

Defining Agentic AI

An AI agent is a software system that uses artificial intelligence to autonomously make decisions and take actions to achieve a set of objectives. AI agents have the power to reason, learn and adapt based on their perception of the work environment. As a result, they can be given a goal and carry out complex tasks to reach that goal, with minimal or potentially no human interaction.

AI agents surpass automation by adapting and learning within complex workflows. To tap into the potential of agentic AI, it’s important to understand the difference between automation and autonomy. Automation is a predefined set of actions that are performed by a piece of technology, whereas autonomy is an intent that is given to technology and the technology then determines and performs the task. Autonomy happens when the human ceases to be the “doer” of the work or ceases to define the workflow.

Take supply chain management as an example. An automated robot can be designed to pick, pack and ship goods in a productive manner that reduces errors, achieving faster order completion and customer satisfaction. An autonomous agent, or AI agent, can optimize supply chain management by predicting demand, managing inventory levels, and coordinating with suppliers to ensure timely restocking. It could identify potential disruptions and suggest solutions to maintain the smooth flow of goods.

Generative AI vs. Agentic AI – Understanding Their Unique Roles

AI agents are different from GenAI chatbots and assistants. GenAI chatbots and assistants help us unlock the power of data, so we can more effectively interact with and act on it. In contrast, AI agents interact with the data and act on our behalf based on our desired goals and without our intervention.

An AI agent is typically composed of a core (i.e., a persona, goals, and a list of available tools); a memory; tools to perceive and interact with its environment; and some form of reasoning function that is likely based on an AI model (e.g., LLM). The capabilities of these building blocks determine the AI agent’s reasoning ability and influence its degree of autonomy.

Balancing Autonomy and Oversight for Effective AI Integration

Humans are critical to agentic AI because they provide intentionality for AI agents. Despite the autonomous nature of AI agents, there is still a human involved in defining what success looks like to the AI agents. The biggest shift from GenAI chatbots and assistants to AI agents is that humans are in the loop with GenAI tools. This means humans are deeply involved in defining how work is going to be done.

With the current slate of AI agents, humans are on the loop. This means that you define the outcome and the intent, but you have delegated the AI agent to figure out how to perform the task. AI agents will become one of the most impactful tools that accelerate enterprise efficiency by taking on complex tasks while continuously improving themselves through learning and adaptation.

These questions of oversight, governance, and the evolving relationship between humans and AI are not just theoretical, they are at the heart of the conversations we’ll be having at the Dell Technologies Forum in Dublin on September 23rd. From exploring how Irish businesses can build trustworthy, autonomous AI systems to examining next-generation AI infrastructure, to understanding how GenAI and Agentic AI work in tandem. This year’s Forum will bring these concepts to life with real-world examples and the insights of Dell experts.

Practical Applications of Agentic AI

AI agents are autonomous and function-serving, which means they are capable of interfacing with other systems and taking actions in those systems. However, the first generation of AI agents are captive within a particular product, system, or vendor. As the technology advances and interoperability standards are defined, it can be leveraged across software programs and across business units from sales to finance, marketing to HR, and in the supply chain.

To prepare for agentic AI, enterprises should look at their technology infrastructure foundation and ensure it is equipped to power and scale AI agents. Identify priority use cases to plug AI agents and start thinking about how to integrate them into your workflows across enterprise software systems and other IT operations.

At this year’s Forum, speakers will provide practical advice for decision makers that can help their organisation overcome infrastructure challenges, unlock productivity, and prepare their workforce for new roles in an AI-driven environment. Sessions will dive into how IT leaders can balance innovation with security, compliance, and ethical considerations while scaling AI initiatives.

The Potential Impact of Agentic AI

Before we know it, AI agents will become the new Application Programming Interface (API) of business, enhancing the way enterprises operate regardless of industry. The real value of AI agents is not when they are in isolation, but rather when they start to work together. This could be an ensemble of agents working inside your company (e.g., different AI agents with different frameworks), or the next evolution: when your AI agents can interact with someone else’s AI agents. With interoperability standards soon to be defined, it won’t be hard to imagine your AI agents interworking with the AI agents of vendors, partners, and customers. The possibilities are endless.

I’m excited for what the future holds for agentic AI and how it will propel enterprises into the future. Dell Technologies Forum will be an important forum for these discussions, bringing together Ireland’s business community to explore agentic AI and its impact on business transformation, leadership, and competitiveness in the AI era.

Join them at the Royal Dublin Society in Dublin on September 23rd for the 2025 Dell Technologies Forum, run in collaboration with NVIDIA, Intel, and Microsoft. For more information and to register for this event, click here

 

Dell AI Data Platform Advancements Help Customers Harness Data to Power Enterprise AI with NVIDIA and Elastic

Dell Technologies, the world’s No. 1 provider of AI infrastructure, today 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.

Why it matters

Enterprise data is massive, growing rapidly and increasingly unstructured, but only a fraction of it is usable for generative AI today. To unlock its value, organisations need continuous indexing and a vector retrieval engine that converts content into embeddings for fast, precise semantic search. As workloads grow, organizations need infrastructure that streamlines data preparation, unifies data access across silos and delivers end-to-end enterprise-grade performance.

The latest updates to the Dell AI Data Platform enhance unstructured data ingestion, transformation, retrieval, and compute performance to streamline AI development and deployment – turning massive datasets into reliable, high quality real-time intelligence for generative AI.

Accelerating AI inferencing and analytics

The Dell AI Data Platform helps customers quickly move from AI experimentation to production by automating data preparation.

At the core of the Dell AI Data Platform’s architecture are specialized storage and data engines that help seamlessly connect AI agents to high quality enterprise data. Together, the Dell AI Data Platform and the NVIDIA AI Data Platform reference design provide a validated, GPU-accelerated solution that integrates storage engines and data engines with NVIDIA accelerated computing, networking and AI software to power generative AI systems.

Expanding the capabilities of the Dell AI Data Platform is the new unstructured data engine, designed to provide real-time, secure access to large-scale unstructured datasets for inferencing, analytics, and intelligent search. This engine, made possible through a new collaboration with open-source Search AI leader Elastic, will offer customers advanced vector search, semantic retrieval and hybrid keyword search capabilities—key capabilities for powering AI applications. Additionally, the unstructured data engine will leverage built-in GPU acceleration to deliver breakthrough performance.

The unstructured data engine works alongside the platform’s other tools, like a federated SQL engine for querying scattered structured data, a processing engine for handling large-scale data transformation, and storage designed for fast, AI-ready access.

Powering enterprise AI discovery

As AI becomes increasingly crucial for business-as-usual operations, Dell PowerEdge R7725 and R770 servers featuring NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs provide the mainstream computing foundation for accelerated enterprise workloads, from visual computing, data analytics and virtual workstations, to physical AI and agentic inference. These servers are ideal for running NVIDIA AI reasoning models such as the latest NVIDIA Nemotron models for agentic AI, as well as NVIDIA Cosmos world foundation models for physical AI.

Offering better price for performance for a wide range of enterprise use cases, these air-cooled systems make flexible high-density AI compute more attainable. The NVIDIA RTX PRO 6000 offers enterprises up to six times the token throughput for LLM inference,[ii] double the capacity for engineering simulation performance[iii] and can support four times the number of concurrent users compared to the previous generation with support for MIG.

The Dell PowerEdge R7725 server will also be the first 2U server platform to integrate the NVIDIA AI Data Platform reference design. When the Dell PowerEdge R7725 server featuring NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs is paired with the Dell AI Data Platform and its new unstructured data engine, enterprises can take advantage of a turnkey solution without the need to architect and test their own hardware and software platforms. The combination of the two delivers faster inferencing, more responsive semantic search and support for larger, more complex AI workloads.

See innovation in action at SIGGRAPH 2025

Dell Technologies is showcasing how customers can accelerate media production pipelines and power intelligent asset management at scale using the Dell AI Data Platform, NVIDIA Omniverse software and Dell infrastructure at this year’s SIGGRAPH conference (August 10-14) in Vancouver, Canada. Dell will also feature the new Dell Pro Max high-performance PC portfolio, including laptops, desktops and the upcoming Dell Pro Max with GB10, a compact AI developer workstation.

“The key to unlocking AI’s full potential lies in breaking down silos and simplifying access to enterprise data,” said Arthur Lewis, president, Infrastructure Solutions Group, Dell Technologies. “Collaborating with industry leaders like NVIDIA and Elastic to advance the Dell AI Data Platform will help organizations accelerate innovation and scale AI with confidence.”

“Enterprises worldwide need infrastructure that handles the growing scale and complexity of AI workloads,” said Justin Boitano, vice president of enterprise AI at NVIDIA. “With NVIDIA RTX PRO 6000 GPUs in new 2U Dell PowerEdge servers, organizations now have a power efficient, accelerated computing platform to power AI applications and storage on NVIDIA Blackwell.”

“Fast, accurate, and context-aware access to unstructured data is key to scaling enterprise AI,” said Ken Exner, Chief Product Officer at Elastic. “With Elasticsearch vector database at the heart of the Dell AI Data Platform’s unstructured data engine, Elastic will bring vector search and hybrid retrieval to a turnkey architecture, enabling natural language search, real-time inferencing, and intelligent asset discovery across massive datasets. Dell’s deep presence in the enterprise makes them a natural partner as we work to help customers deploy AI that’s performant, precise, and production-ready.”

Availability

  • Unstructured data engine in Dell AI Data Platform will be available later this year.
  • Dell PowerEdge R7725 and R770 servers with NVIDIA RTX PRO 6000 GPUs will be globally available later this year.