This white paper outlines how Pure’s storage platform supports AI workflows from ingestion to model training to production. It highlights reliability, efficiency, and long-life architecture, with systems designed to survive multiple overlapping failures, self-monitor, auto-tune, and upgrade without downtime. It explains direct benefits for GPU-accelerated AI, including high metadata performance, multi-protocol access, high-density DFMs, and large-scale capacity expansion. It also covers Pure’s collaboration with NVIDIA and how the platform anchors long-term AI projects through Evergreen modernization.

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