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Artificial Intelligence

Accelerate AI Adoption with the Pure Data Storage Platform

Accelerate model training and inference, maximise operational efficiency, and deliver cost savings with a reliable storage platform that provides the agility to grow with your AI environment.

Free Your AI Teams to Innovate without Boundaries

Multi-modal performance enables large model training in days rather than months, regardless of protocol, file size, or file/object count. Make AI infrastructure easy with simplified management and validated, full-stack architectures that enable dev teams to proceed without delays.

Accelerate AI-driven Insights

Accelerate model training, retrieval-augmented generation, and inferencing with a data storage platform that delivers consistent high performance through every step of your AI data pipeline.

Maximise Operational Efficiency

Streamline AI data operations with simple and consistent management of efficient, all-flash storage. Provision the right storage resources based on SLAs, with self-service capability in containerized AI environments.

Minimize Cost, Maximise Energy Efficiency

Keep massive repository data sets needed for future training on reliable, capacity-optimised all-flash storage—at a cost comparable to disk. Add additional GPUs in the same power footprint with storage that consumes 1/10th the energy of alternate solutions.

Future-proof AI Storage

As your enterprise AI strategy matures and data requirements grow, scale capacity or performance non-disruptively to meet dynamic growth with Evergreen® technology and flexible as-a-service offers.

What is AI Storage?

AI storage is a storage infrastructure and solution that is designed and optimised to support the needs of artificial intelligence (AI) applications and AI development workflows. AI involves the processing of large datasets and the training of complex models, which requires substantial storage capacity, high-speed data access, and efficient data management.

People also ask:

1. What are AI workloads?

AI workloads are specific tasks and computations that AI systems perform to accomplish various goals. These workloads cover a wide range of applications and use cases, relying on various AI processes and algorithms.

2. Does AI require big data?

AI and big data have a symbiotic relationship where both are generally better together. The bigger and higher quality the training data set, the smarter the AI will become. On the flipside, big data analytics pipelines can leverage AI to efficiently process large quantities of unstructured data spread across multiple siloed environments.

3. What considerations are there for AI at scale?

Cloud or legacy infrastructure is often used for early AI development or proof of concept, but when AI is used at production scale, data scientists need to consider infrastructure that is optimised for AI. 

Considerations should include:

  • Data set size and growth
  • Cost and availability of high performance GPUs, storage, and networking
  • Security, control, governance, and data ownership requirements.

Often, a hybrid or on-prem solution will offer better and faster results  with lower total cost of ownership.

Case Studies
Chang Gung Memorial Hospital logo on orange gradient background
“The computing speed of analysing medical data has been greatly increased after introducing AIRI.”
Chang-Fu Kuo
Director, Center for AI in Medicine
Chang-Fu Kuo
Director, Center for AI in Medicine
Kakao logo on yellow background
“We needed fast and reliable storage for AI projects, and FlashBlade® was an optimal choice for us. Since adopting FlashBlade, we are able to use data more efficiently and significantly reduce the cost of managing infrastructure.”
Il-seop Jin
Manager, Infrastructure Planning
Il-seop Jin
Manager, Infrastructure Planning
MediaZen logo on blue background
Accelerates AI-powered voice recognition modeling cycle by 96%
Abstract grey hexagons on a black background
"You need to consider storage to drive the success of AI projects. FlashBlade processes large amounts of data reliably at high speed, allowing us to build an infrastructure that always provides the optimal performance.”
Jargalsaikhan Narantuya
Professor, AI Graduate School
Jargalsaikhan Narantuya
Professor, AI Graduate School
Layered orange hexagons on a canvas colored background
Increase in GPU usage, from 30% to 80%


NVIDIA and Pure Storage deliver efficient, proven AI solutions.

"...Meta has continued to partner with Pure, and RSC is the latest example of how Pure is helping Meta achieve its AI research goals."

Vivek Pai

Storage Lead for AI Research SuperCluster, META

Meet with an Expert

Let’s talk. Book a 1:1 meeting with one of our experts to discuss your specific needs.

Questions, Comments?

Have a question or comment about Pure products or certifications?  We’re here to help.

Schedule a Demo

Schedule a live demo and see for yourself how Pure can help transform your data into powerful outcomes. 

Call Sales: 800-976-6494


Pure Storage, Inc.

2555 Augustine Dr.

Santa Clara, CA 95054

800-379-7873 (general info)

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