There's a standard story about where power accumulates in a gold rush: not in the miners, but in the people selling shovels. In the current AI gold rush, the shovels are data infrastructure. And right now, the company that may be building the most critical set of those tools just raised at a valuation that should get everyone's attention.

by Kasun Illankoon, Editor in Chief at Tech Revolt

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VAST Data, which describes itself as an "AI Operating System" company, has closed its Series F financing round at a $30 billion valuation. That number is striking on its own. What makes it genuinely significant is the trajectory behind it: VAST was valued at $9.1 billion in late 2023. In roughly 18 months, it added more than $20 billion in perceived value. The round was led by Drive Capital, with Access Industries as co-lead, and included continued backing from Fidelity, NEA, and NVIDIA.

So what is VAST Data actually doing, and why does Wall Street and Silicon Valley seem so convinced it's worth this much money?

The unglamorous problem at the center of everything

To understand VAST, you have to start with a problem that doesn't get much airtime in the mainstream AI conversation: how do you actually move, store, and process the staggering volumes of data that modern AI systems consume?

Training a large language model requires feeding it vast quantities of text, images, or other data at extraordinary speeds. Running that model at inference, serving answers to users in real time, creates its own data demands. At the scale that serious AI companies now operate, the storage and data pipeline layer isn't a background concern. It is frequently the bottleneck.

VAST was founded in 2016, which is itself notable. The company didn't pivot to AI after the ChatGPT moment in late 2022. Its founders, according to the company's own account, built the architecture specifically anticipating that AI would eventually demand something fundamentally different from existing storage systems. The resulting design, which VAST calls DASE (Disaggregated Shared Everything), was engineered to break what the company describes as longstanding tradeoffs between scale, simplicity, performance, and cost.

That early positioning now looks prescient. The company says it supports environments that collectively power millions of GPUs, serving customers that range from CoreWeave, the GPU cloud provider, to the U.S. Air Force, to coding assistant platform Cursor, to Lowe's. That is an unusually broad cross-section of the economy to find in a single infrastructure company's customer list.

The financial picture behind the headline

The valuation is impressive, but the underlying business metrics are arguably more revealing. VAST reports it has surpassed $4 billion in cumulative bookings and exited its most recent fiscal year with more than $500 million in committed annual recurring revenue. Perhaps even more remarkable, the company says it is operating with positive operating margin and positive free cash flow, a combination that is genuinely unusual for a company growing at this pace.

The Rule of X score of 228% puts it in rare company. Most venture-backed software companies that grow quickly do so by burning cash. VAST appears to be doing both: growing fast and generating real financial returns. That combination, if it holds, is exactly what justifies the kind of valuation multiple investors are willing to pay right now.

That early positioning now looks prescient. The company says it supports environments that collectively power millions of GPUs, serving customers that range from CoreWeave, the GPU cloud provider, to the U.S. Air Force, to coding assistant platform Cursor, to Lowe's. That is an unusually broad cross-section of the economy to find in a single infrastructure company's customer list.

The financial picture behind the headline

The valuation is impressive, but the underlying business metrics are arguably more revealing. VAST reports it has surpassed $4 billion in cumulative bookings and exited its most recent fiscal year with more than $500 million in committed annual recurring revenue. Perhaps even more remarkable, the company says it is operating with positive operating margin and positive free cash flow, a combination that is genuinely unusual for a company growing at this pace.

The Rule of X score of 228% puts it in rare company. Most venture-backed software companies that grow quickly do so by burning cash. VAST appears to be doing both: growing fast and generating real financial returns. That combination, if it holds, is exactly what justifies the kind of valuation multiple investors are willing to pay right now.

"We are already supporting AI environments spanning millions of GPUs globally, operating across every layer of the AI stack. What is becoming clear is that these layers are no longer independent. Applications, models, and infrastructure now operate as a single system through data. VAST sits at the center of how that system works, which is why we are seeing this level of demand at global scale."

Renen Hallak, Founder and CEO, VAST Data

Hallak's framing is interesting because it gestures at something larger than a storage company. The argument VAST is making, and that investors appear to be accepting, is that data is not just a resource AI systems consume. It is the connective tissue that links applications, models, and infrastructure into a unified system. Whoever sits at that junction controls a great deal.

Why the timing makes sense

It would be easy to dismiss a $30 billion valuation for a storage-adjacent company as another symptom of AI hype. But there are structural reasons why the timing of this raise reflects something real.

The AI buildout is entering a new phase. The first phase was about building large models and demonstrating what they could do. The current phase is about deploying AI at industrial scale, in data centers, in enterprises, in consumer products, across every vertical of the global economy. That deployment phase has fundamentally different infrastructure requirements than the research phase that preceded it.

When AI moves from experiment to operation, the demands on data infrastructure shift from "impressive benchmark" to "never goes down, never loses data, scales to arbitrary size." That is a very different bar, and it's one that favors companies that have been building for reliability and performance at scale since before the current boom.

"The scale and speed of AI adoption are creating a new class of infrastructure company. VAST is emerging as the clear leader in this category, with the architecture and momentum to support the world's most demanding AI environments. The step-change in valuation reflects both that momentum and our conviction in VAST's role at the center of this market."

Chris Olsen, Co-Founder and Partner, Drive Capital

Drive Capital's Olsen is pointing at something the broader market is increasingly recognizing: the companies that will define AI infrastructure aren't just the model makers. They are the companies building the systems that make models deployable, scalable, and economically viable. NVIDIA sits at one layer of that stack, the GPU layer. VAST, if its thesis holds, is making a claim on the data layer.

What enterprise customers are actually saying

Perhaps the most telling evidence of VAST's position comes not from its investors but from its customers. Mistral AI, one of the leading frontier model companies, relies on the platform for training pipelines. JPMorganChase has publicly described it as a key enabler for AI infrastructure initiatives. Crusoe, which builds GPU cloud infrastructure for AI workloads, reports that its partnership with VAST grew by more than ten times in a single year.

"As we push the boundaries of large-scale model training, the foundation of our infrastructure becomes critical. VAST's data platform enables us to efficiently manage and scale the massive datasets required to train frontier models, ensuring high performance and flexibility across our training pipelines."

Timothee Lacroix, Co-Founder and CTO, Mistral AI

That kind of customer testimony from a company like Mistral, which is pushing the frontier of what's technically possible in model training, carries more weight than an investor pitch. Frontier model training is arguably the most demanding environment a data platform will ever face. If VAST is doing that work reliably, it is plausibly doing everything else reliably too.

"Our partnership with VAST Data has grown more than 10x this past year and continues to accelerate -- a reflection of how critical an AI data platform is to training and inference workloads on Crusoe Cloud. Together, we've built a storage service which many model labs, leading AI agent companies, and physical AI pioneers rely on."

Erwan Menard, SVP Product Management, Crusoe

The risk the valuation doesn't fully price

There is, of course, a version of this story where the valuation is too rich. Data infrastructure is a competitive space. Hyperscalers like AWS, Google, and Microsoft all have native storage solutions that are deeply integrated into their AI platforms. Enterprise customers often prefer to consolidate vendors. The gravitational pull of cloud-native infrastructure is real, and it doesn't favor independent companies over the long term.

VAST's answer to this concern is, essentially, that its architecture is differentiated enough that customers choose it even when cheaper alternatives exist. The company's commercial traction, across a genuinely diverse set of industries and use cases, is evidence in favor of that argument. So is the NVIDIA participation in this financing round, which suggests a strategic alignment between GPU supply and the data infrastructure built to serve it.

"The VAST platform is a key enabling technology for next gen AI infrastructure initiatives -- providing a modern, flexible data architecture for Gen AI applications and agentic workflows."

Larry Feinsmith, Managing Director, Head of Global Tech Strategy, Innovation and Partnerships, JPMorganChase

JPMorganChase's endorsement is significant in a specific way: major financial institutions are not early adopters by nature. When a bank at that scale publicly positions a vendor as a strategic technology partner for AI, it suggests the vendor has cleared a compliance and reliability bar that most companies cannot. That kind of customer validation is hard to manufacture.

What comes next

VAST says it will use the primary proceeds from this round to expand globally, pursue strategic transactions, and deepen its technology footprint. The secondary component of the financing, which brings the total transaction to approximately $1 billion, suggests some early investors or employees may have also taken liquidity. That is not unusual at this stage, but it is a signal that the company is maturing in its investor base structure.

The broader question is whether VAST's positioning as an "AI Operating System" is a category it can actually own or a marketing claim that will erode as competitors and hyperscalers close the architectural gap. The company's Rule of X performance and customer diversification are the strongest arguments that it is currently ahead. The next 18 months, as AI deployment accelerates and customers begin to lock in long-term infrastructure relationships, will be revealing.

For now, the $30 billion valuation is the market's answer to a simple question: in the AI economy, who sits at the center? VAST's investors believe the answer, increasingly, is the company controlling the data layer. The revenue numbers and the customer roster suggest they are not wrong about that, at least not yet.