VAST Data Closes Series F at $30 Billion Valuation as AI Buildout Redraws the Data Infrastructure Map
VAST Data has closed its Series F financing round at a $30 billion valuation, more than tripling the $9.1 billion it commanded at its Series E in late 2023 and placing the data infrastructure company among the most richly valued privately held businesses built around the AI buildout. The round was led by Drive Capital, with Access Industries as co-lead, and included continued participation from Fidelity Management & Research Company, NEA, and NVIDIA, as well as new investors. Primary and secondary capital combined brought the total transaction value to approximately $1 billion.
The company said primary proceeds would be used to consolidate its position as the AI operating system at the centre of the AI ecosystem, with capital earmarked for global expansion and strategic transactions, including potential acquisitions.
VAST's funding history tracks the shifting economics of enterprise infrastructure more closely than most. Founded in 2016 by Renen Hallak, previously the head of R&D at Dell EMC-acquired XtremIO, alongside Shachar Fienblit, Jeff Denworth, and Alon Horev, the company emerged from stealth in February 2019 with $80 million in funding and a distributed systems architecture called DASE, short for Disaggregated Shared Everything.
A $100 million Series C followed in 2020, an $83 million Series D in 2021 at a $3.7 billion valuation, and a $118 million Series E in December 2023 that lifted the company to a $9.1 billion valuation.
Total disclosed funding prior to the Series F stood at roughly $381 million, a figure notable given that VAST has historically emphasised that it operates cash-flow positive and does not require capital to fund operations. At the time of the Series E, co-founder Denworth said the funding would sit in the bank alongside proceeds from previous rounds. The Series F is less an operating requirement and more a repricing exercise, setting a benchmark valuation ahead of any acquisition offer or public listing and providing the capital management has flagged for strategic transactions.
For comparison, publicly listed storage peers Pure Storage and NetApp currently have market capitalisations in the high tens of billions, while data platform companies Snowflake and Databricks trade at around $68 billion and $134 billion, respectively. VAST's $30 billion mark positions it squarely between traditional storage vendors and data platform heavyweights, aligning with the company's own positioning as a category that bridges both.
The macro backdrop: AI capital concentrating in infrastructure
The Series F lands in a funding environment that has tilted heavily towards AI infrastructure. According to Crunchbase data, global venture investment reached $300 billion in the first quarter of 2026 alone, with AI accounting for $242 billion or 80% of total funding. Four mega-rounds, comprising OpenAI's $122 billion, Anthropic's $30 billion, xAI's $20 billion, and Waymo's $16 billion, together raised $188 billion in that quarter. Beyond the frontier model labs, another ten companies raised rounds of $1 billion or more across generative AI, semiconductors, data centres, robotics, and autonomous vehicles.
The broader picture from 2025 is that $202 billion was invested in AI globally, a 75% year-on-year increase, with 58% of AI funding going into megarounds of $500 million or more. Enterprise AI revenue reached $37 billion in 2025 according to Menlo Ventures, roughly split between $19 billion in user-facing products and $18 billion in AI infrastructure. Against that backdrop, a Series F at $30 billion for a company with the revenue profile VAST has disclosed is not an outlier but part of a wider pattern in which late-stage capital is concentrating in businesses positioned at infrastructure layer chokepoints.
VAST disclosed $500 million in Committed Annual Recurring Revenue at the end of its most recent fiscal year, $4 billion in cumulative bookings, and what the company described as a Rule of X score of 228%, a metric combining growth rate and profitability margin. The company said it was operating at positive operating margin and positive free cash flow. These figures, if they hold up under eventual public scrutiny, place the business in a small category of high-growth software companies that have also achieved profitability, though the Rule of X framework is less standardised than metrics such as the Rule of 40 and the company did not disclose the exact underlying growth and margin components.
The competitive landscape is denser than the headline suggests
The market VAST operates in has become considerably more crowded than its positioning suggests. On the dedicated AI storage side, VAST competes most directly with DDN, which recently raised $300 million in private equity funding and has pushed hard on benchmark comparisons, and WEKA, which raised $140 million in 2024 at a $1.6 billion valuation but has since experienced executive turnover. Hammerspace is also increasingly present in the same deals.
The incumbents have taken notice. Hewlett Packard Enterprise has adopted a version of the DASE architecture in its Alletra MP X10000 system, effectively acknowledging the technical direction VAST pioneered. NetApp has a project to produce an AI-focused version of its ONTAP operating system, Dell has a project to parallelise PowerScale, and Pure Storage has signalled moves into AI training storage. Industry observers have noted that the incumbents have so far responded with internal development rather than acquisition, though analysts writing in trade publication Blocks & Files have suggested that a major acquisition by Dell, IBM, NetApp, or Hitachi Vantara is becoming overdue as the challenger cohort scales.
Benchmarking comparisons should be treated with some caution, as each vendor tends to publish tests that favour its own architecture. DDN has published data suggesting its EXAScaler system outperforms both WEKA and VAST on certain IO500 benchmarks, with one DDN analysis estimating a three-year total cost of ownership of $154 million for a DDN deployment against $328 million for WEKA and $743 million for VAST on equivalent workloads. VAST's customers, for their part, point to the unified architecture and breadth of data services rather than raw throughput as the reason for selection. The point is not which benchmark is correct but that performance leadership in the category is actively contested.
VAST is also pushing upwards in the stack, where it increasingly overlaps with data platform vendors such as Snowflake and Databricks. The company's description of its offering as an AI operating system, encompassing DataStore, DataBase, DataEngine, and DataSpace components, is a deliberate repositioning away from the storage category and towards a broader platform play. Whether that positioning holds under competitive pressure from companies that have been building data warehouses and lakehouses for longer remains one of the open questions the Series F does not answer.
Customer signals and what they imply
The endorsements VAST released alongside the funding announcement were selected to illustrate breadth across customer types. Timothée Lacroix, Co-Founder and CTO of Mistral AI, said VAST's data platform allowed his team to efficiently manage and scale the datasets required to train frontier models. Larry Feinsmith, Managing Director and Head of Global Tech Strategy, Innovation and Partnerships at JPMorganChase, described the platform as a key enabling technology for next-generation AI infrastructure and agentic workflows. Erwan Menard, SVP Product Management at Crusoe, said the AI cloud operator's partnership with VAST had grown more than 10x in the past year.
Chris Olsen, Co-Founder and Partner at Drive Capital, said the scale and speed of AI adoption were producing a new class of infrastructure company and that VAST was emerging as the clear leader in that category. Renen Hallak, VAST's Founder and CEO, said the layers of the AI stack were no longer independent, with applications, models, and infrastructure now operating as a single system through data.
The customer list lends credibility to the valuation, though it also illustrates VAST's concentration in a specific type of buyer. The GPU cloud operators, including CoreWeave and Crusoe, are themselves capital-intensive businesses whose own economics depend on the AI buildout continuing at current pace. The frontier model labs are similarly exposed. Enterprise deployments, represented by JPMorgan and Lowe's in the company's disclosures, are expanding but remain a smaller share of the overall business than the AI-native customer base. Any material slowdown in AI capital expenditure by hyperscalers and GPU cloud providers, which have collectively committed more than $300 billion in capex for 2025 with higher figures pencilled in for 2026, would flow through to VAST's growth trajectory faster than to a more diversified infrastructure vendor.
What it means for the sector
The Series F confirms several structural trends that have been visible in the market for some time. The first is that the data layer has been repriced as a strategic component of the AI stack rather than a storage cost centre, with valuation multiples for data infrastructure businesses now converging towards those of data platforms. The second is that the distinction between storage vendors, database vendors, and AI platforms is dissolving, with companies positioning themselves across multiple categories rather than defending a single one.
The third and perhaps most consequential implication is the pressure the round places on incumbents. Dell, IBM, NetApp, Hitachi Vantara, and Pure Storage now face a challenger with a $30 billion private valuation, $500 million in CARR, positive cash flow, and customer relationships with the market's fastest-growing infrastructure buyers. Internal development projects at each of those companies are intended to match the architectural advantages VAST and its peers have demonstrated, but the pace of that catch-up will determine whether the next phase of the cycle is characterised by organic competition or by acquisition.
For VAST itself, the round resolves some questions and sharpens others. It removes any near-term financing pressure, funds potential acquisitions, and sets a benchmark price for any eventual IPO or strategic transaction. It also raises expectations. A company valued at $30 billion in private markets will be held to growth and margin standards that leave little room for execution missteps, particularly if the broader AI capex cycle moderates. The pipeline of public companies with tens of billions of dollars in private capital behind them is already creating pressure on IPO markets to reopen in 2026, and VAST is now among the businesses most closely watched for that transition.
What the Series F does not settle is whether the category VAST has defined, sitting between storage, database, and AI platform, will prove durable once the incumbents have completed their own architectural updates and the hyperscaler-led AI capex cycle has reached its steady state. The answer to that question will shape not only VAST's trajectory but the valuation arithmetic for the entire AI infrastructure sector.