$P
AI NEEDS CHIPS.
BUT CHIPS ARE USELESS IF THEY CAN’T GET THEIR DATA FAST ENOUGH.
That’s where
$P comes in.
Most investors focus on
$NVDA,
$MU, or storage media names like
$STX and
$WDC.
They’re missing the company that sits one layer higher in the stack.
$MU sells the memory.
$P makes that memory usable for AI.
It doesn’t manufacture NAND.
It doesn’t build HDDs.
It builds the high-performance all-flash NVMe storage platforms that keep AI clusters fed with data.
As GPUs become exponentially faster, storage is quietly becoming one of the biggest bottlenecks in AI infrastructure.
That bottleneck is exactly where
$P operates.
Its FlashArray platform powers traditional enterprise workloads, while FlashBlade//EXA was built specifically for AI, HPC, and massive unstructured datasets.
These systems can deliver over 10 TB/s of throughput in a single namespace, allowing thousands of GPUs to access training data without waiting on storage.
The hardware is only part of the story.
$P layers Purity OS, AI-driven management through Pure1, Evergreen subscriptions, and new data intelligence capabilities that organize enterprise data into AI-ready datasets.
Instead of selling drives, it sells an intelligent data platform.
That’s an important distinction.
Its customers aren’t buying storage.
They’re buying performance.
They’re buying lower latency.
They’re buying higher GPU utilization.
Those advantages have helped
$P steadily take market share, gaining roughly 13% of the enterprise storage market since 2013 while continuing to displace legacy storage vendors.
The financial acceleration is becoming difficult to ignore.
Q1 FY27 revenue reached $1.05B, growing 35% YoY, one of the fastest growth rates the company has delivered in years.
Product revenue surged 55% YoY.
Annual recurring revenue climbed to roughly $2B, up 19%.
Storage-as-a-Service TCV sales jumped 73% YoY.
Perhaps the most important metric?
Remaining Performance Obligations (RPO) reached $3.8B, growing 41% YoY.
That backlog is growing faster than revenue itself.
It gives investors multi-quarter visibility into future growth and shows customers are making long-term commitments rather than one-off purchases.
Management was confident enough to raise full-year guidance.
FY27 revenue is now expected between $4.41B-$4.51B, representing roughly 22% growth at the midpoint.
Operating income guidance also increased to $820M-$860M.
Even more impressive, the business continues generating 70%+ non-GAAP gross margins, highlighting that this is far more than a commodity hardware company.
Because investors focused on near-term margin pressure.
NAND costs increased.
Supply chain inflation compressed free cash flow margins.
The company couldn’t immediately pass through higher component costs because many customer quotes have roughly 90-day pricing windows.
The market simply focused on profitability instead of backlog.
Hyperscale customers are also expected to contribute much more heavily during the second half of FY27.
This is why I believe
$P is still relatively early in its AI infrastructure cycle.
Unlike memory manufacturers, whose earnings can swing wildly with commodity pricing,
$P generates high-margin recurring software and subscription revenue through Evergreen while expanding deeper into enterprise AI.
It’s becoming the platform that turns flash media into AI-ready infrastructure.
Industry forecasts estimate the AI storage market could grow from roughly $35-45B today to well over $270B by 2034, driven by exploding AI datasets, inference workloads, and HPC deployments.
Competition certainly exists from
$DELL,
$HPE, and cloud-native providers.
But premium businesses with recurring revenue, expanding margins, accelerating backlog, and exposure to one of AI’s least-discussed bottlenecks rarely trade at bargain multiples.
That’s the problem
$P is solving.
We either bounce here at 100MA or go to 52$ 200MA.
Keep eyes x fam.