See why Pure Storage is named a Leader in the 2021 Gartner Magic Quadrant for Distributed File Systems & Object Storage
Artificial Intelligence

Smarter Infrastructure for AI

AI workloads process massive amounts of data from structured and unstructured sources. Turn to high-performance, architecturally optimised solutions that can harmoniously exist within existing data centers.

Accelerate Time to Insight, Seamlessly

In a data-rich world, shared data is infinitely more valuable than stored data. Pure accelerates modern analytics and AI workloads, delivering a single, scale-out storage platform that drives time to insight for data-driven businesses.

Speed Time to Insight

AI is transforming business everywhere. But data doesn’t analyse itself and legacy systems often can’t support the massive AI data pipelines required for modern analytics. Pure brings a massively parallel platform capable of delivering ultra-fast, all-flash performance to billions of objects and files.

Simplify Operations with AI Solutions

Data is stuck in 20th-century infrastructure and sprawling silos. It’s also the lifeblood of AI. From data capture to neural network training, Pure is built from the ground up to deliver a single, scale-out storage platform that consolidates AI workloads.

A Leader in Innovation

Recognized as the “Best AI Solution for Big Data” by the AI Breakthrough Awards. Pure offers simple and flexible AI-first infrastructure with the ability to flexibly adapt to demands for AI and launching enterprises into a new era by enabling faster innovation and a competitive edge for AI initiatives.

AI Breakthrough Award 2021

Pure Storage is Named as a Leader in the 2021 Gartner® Magic Quadrant™

for Distributed File Systems & Object Storage

What is artificial intelligence?

Artificial intelligence (AI) is a branch of computer science concerned with creating self-learning systems that can perform tasks that normally require human intelligence. From self-driving cars to predicting the future, AI is revolutionising the ways in which we can use data to shape our world.

People also ask:

1. How can AI power your data analytics?

AI can power your data analytics pipeline in a number of ways—from processing unstructured data like streaming video feeds to powering advanced predictive analytics tools. AI algorithms can give your analytics capabilities the boost you need to remain competitive.

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. AI vs. machine learning vs. deep learning—what’s the difference?

The difference between AI, machine learning (ML), and deep learning (DL) lies in the scope of specificity: 

  • AI deals broadly with building computer systems that can learn on their own. 

  • ML is a subset of AI that deals with algorithms that can self-learn from training data. 

  • DL is a subset of ML that deals with neural networks—specifically those that have more than one “hidden” layer between the input and output layers of the network.

Don't Take Our Word for It

We work with the best across all industries.

“Pure gives us credibility as we take on transformative AI initiatives for clients.”

Alexei Gavriline
Co-founder and President

The computing speed of analysing medical data has been greatly increased after introducing AIRI.

Chang-Fu Kuo
Director, Centre for AI in Medicine
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