Unlock the full potential of your AI initiatives—at every stage. Get high performance at any scale.
Break down data silos, integrate diverse data sources, drive cost savings and efficiency for better GPU utilization, and streamline your entire project on a unified platform.
Achieve AI project success with an AI-ready, storage-as-a-service platform that grows with you and mitigates risk, with non-disruptive Evergreen® upgrades.
Deliver industry-leading performance with proven metadata capabilities. FlashBlade//EXA™ simplifies management at scale and supports AI innovation with a highly configurable and disaggregated architecture.
85%
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Streamline your AI infrastructure and reduce the number of tools required, simplifying storage management and speeding up deployments.
Fast-track and future-proof enterprise AI and HPC initiatives with a certified, turnkey solution from AI infrastructure leaders NVIDIA and Pure Storage.
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AI storage is a storage infrastructure and solution that is designed and optimised to support the needs of AI applications and 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.
Generative AI (GenAI) is the application of machine learning algorithms to large data sets to generate content, such as text, images, audio, and video. Popular GenAI tools include ChatGPT, DALL-E, Bard, and Midjourney.
Retrieval-augmented generation (RAG) optimises the output of large language models (LLMs) by consulting an authoritative knowledge base outside of its original training data before generating a response, effectively extending its capabilities beyond its original training data. RAG is a cost-effective way to improve LLM outputs for specific domains, by leveraging an internal database of proprietary, custom data.
The most important attribute for AI storage is performance agility. AI storage must have the ability to grow from a few hundred gigabytes to petabytes, perform well with rapidly changing mixed workloads, serve data to training and production clients simultaneously throughout a project’s life, and support the data models used by project tools. The additional attributes of an ideal AI storage solution are: capacity flexibility, availability and data durability, space and power efficiency, support for data models, security, and operational simplicity.
1 2024 Pure Storage and Vanson Bourne market research study of 1,500+ relevant decision makers.
2 2023 Pure Storage and Wakefield Research market research study of 500 relevant decision IT buyers.
