AI can help businesses work faster, make better decisions, and tackle data-heavy problems - but only if it runs on good, accessible data. The Dell AI Data Platform makes data AI-ready by improving how organizations store, access, process, and protect it, combining AI-optimized storage with an intelligent data foundation.
Here's how four organizations turned that approach into measurable outcomes - across research, automotive, enterprise GenAI, and secure engineering.
TL;DR
- Oregon State University uses Dell storage, AI infrastructure and data-protection technologies to analyze research data far faster than before
- With Dell PowerScale's support for all-flash storage and automated tiering, Subaru can manage 1,000 times as much camera data for AI training and inferencing
- Samsung SDS uses Dell storage and data orchestration to bring live enterprise data into generative workflows, with employee productivity benefits of up to 70%
- Worley uses Dell PowerScale and Dell AI Factory with NVIDIA to make sensitive data available for AI operations within secure on-premises infrastructure
Oregon State University turns ocean data into faster scientific insights
Oregon State University uses Dell storage, AI infrastructure, and data-protection technologies to quickly extract meaningful information from a mass of incoming data. The university works with the US-based Ocean Observatories Initiative, which collects real-time environmental data from more than 900 instruments – adding up to more than 20TB of new data each month. The challenge is turning this flow of information into research insights, without losing control of performance, protection or availability.
Dell helped OSU to manage the incoming data with storage and AI infrastructure; a key part of the environment is Dell PowerScale, the scale-out storage platform that enables OSU to ingest and distribute high volumes of unstructured data at high speed. Dell AI Factory meanwhile, enables AI infrastructure to be deployed directly on research ships, turning them into edge environments so analysis can begin closer to where the data is collected.
To safeguard valuable records, OSU additionally uses Dell protection technologies, including PowerProtect Data Manager. With automated threat protection, data integrity checks and recovery capabilities, OSU has been able to protect 16.6PB of data, stored with a 160:1 reduction ratio – and the university reports zero downtime since the installation of the Dell Cyber Recovery vault, despite more than 130,000 attempted attacks over the course of three months.
Thanks to Dell systems making the data more usable, OSU can analyze as much as 400TB of oceanographic research data within hours or days, instead of the previously estimated 25 person-years, while keeping that data managed and protected across distributed environments.
Subaru uses AI-ready data to improve driver assistance development
Subaru uses Dell PowerScale, part of the Dell AI Data Platform, to keep large volumes of vehicle camera data available for AI workloads. The company’s next-generation EyeSight Driver-Assist Technology relies on test-vehicle camera footage; new data can drive improvements, but only if it’s ingested, managed and made available across the teams developing AI models.
Dell PowerScale provides the AI-ready storage layer that helps Subaru keep its growing store of camera data accessible for model training, testing and inference. All-flash NVMe storage nodes enable high-performance data access for active AI workloads, while PowerScale’s integrated SmartPools and CloudPools tiering features help manage the totality of the data, with less active files being automatically moved to the most appropriate storage location, or onto cloud storage.
These capabilities help Subaru handle its data efficiently, while reducing manual file management. And because PowerScale abstracts file locations and types, developers and data scientists can work with the same datasets regardless of where they are, or where the information physically sits. The result is that Subaru can now store and manage 1,000 times as many files as before, while improving access to the data used for AI model training, inferencing and operational workflows.
Samsung SDS is using enterprise data to drive generative AI workflows
Samsung SDS uses Dell’s storage and AI infrastructure to turn enterprise data into live context for generative AI services. The enterprise cloud provider develops AI-powered products including Brity Copilot, which helps employees automate everyday knowledge tasks, and FabriX, which provides a protected connection between Samsung SDS’ generative AI tools and customers’ IT systems.
The data challenge here is that the AI needs to be able to find and retrieve relevant company information, and return useful outputs quickly enough to be useful. If retrieval is slow, the user experience suffers; if retrieval is incomplete, the answer might be incomplete too.
For Samsung SDS, the value of the Dell AI Data Platform is orchestration. This allows enterprise data to be made available to generative AI services, so they can retrieve relevant context for use inside live workflows. Dell PowerScale supports the project with high-performance, all-flash NVMe storage nodes and scalable capacity; Samsung SDS reports that its generative AI services reach up to 98% accuracy in retrieval-augmented generation, while Brity Copilot delivers productivity benefits of up to 70%, supporting moves towards multi-step workflow automation.
Worley uses secure AI infrastructure for engineering innovation
Worley uses Dell PowerScale and Dell AI Factory with NVIDIA to support generative AI services that involve sensitive information. As a global engineering and professional services company, Worley works across the energy, chemicals and resources sectors, and uses AI both to enhance internal productivity and to help clients address business challenges. Since engineering and client information can be confidential or commercially valuable, Worley needs to tightly manage data privacy, IP and security.
Dell PowerScale storage provides scalable storage with strong access controls for AI data, while Dell AI Factory with NVIDIA lets Worley run AI workloads onsite, under its own data-privacy and security rules. An on-premises deployment additionally benefits performance, helping reduce time-to-value for new AI initiatives while keeping development within a secure environment.
Organisation |
How Dell makes the data AI-ready |
Outcome |
Oregon State University |
Helps ingest, disperse and protect research data across distributed environments |
Analyzing up to 400TB within hours or days; 16.6PB of secure data storage with 160:1 reduction ratio |
Subaru |
Keeps large volumes of camera data accessible through fast, scalable, tiered storage |
Storing and managing 1,000 times as many files while improving AI data access and performance |
Samsung SDS |
Stores and orchestrates enterprise data for access by generative AI services |
Up to 98% accuracy in retrieval-augmented generation; productivity gains of up to 70% |
Worley |
Makes sensitive data available to AI tools within a secure, on-premises infrastructure |
Strong data governance with reduced time-to-value for new AI initiatives |
What do these case studies show about AI data?
These projects show that AI success depends on making data available where it's needed, organized for the task, and protected throughout the workflow - whether that means pulling remote data into research pipelines, managing vast volumes of unstructured information, running live queries on enterprise data, or securing sensitive IP.
The common thread: data isn't just raw material - it's the core resource that lets AI deliver. Across all four examples, Dell's AI data layer pairs high-performance storage with a unified data foundation to store, organize, process, and protect the information that makes AI useful.
You can find out more about the Dell AI Data Platform on the Dell website.
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