Alphabet’s growth-stage investment fund, CapitalG, and chipmaking powerhouse Nvidia are in advanced discussions to back Vast Data, a rapidly growing AI infrastructure company, in a new round of funding that could value the company at up to $30 billion. If completed, the deal would mark one of the largest private financing rounds in the artificial intelligence sector this year and position Vast Data among the most valuable privately held AI infrastructure firms globally.
The funding round is expected to include several billion dollars in new equity, potentially bringing in a mix of venture capital, sovereign wealth funds, and strategic corporate investors. Discussions are ongoing, and terms could still change, but multiple parties familiar with the matter say a valuation in the $25–30 billion range is currently under consideration.
From Storage Innovator to AI Infrastructure Leader
Founded in 2016, Vast Data has undergone a striking transformation from a niche storage startup into a critical player powering the back-end infrastructure of modern AI workloads. The company specializes in building high-performance, unified storage systems designed to support massive amounts of data processing in real time. Its unique architecture, which integrates data storage, database, and compute into a single software-defined layer, has proven especially valuable for large-scale AI models running on GPU clusters.
Originally conceived to solve the bottlenecks of legacy storage for enterprises dealing with unstructured data, Vast Data now positions itself as a key enabler for next-generation AI platforms — the kinds used by cutting-edge players in fields ranging from autonomous systems and scientific research to generative AI development and national security.
The company’s rapid pivot to become a cornerstone of AI infrastructure reflects a broader trend: as AI systems become more sophisticated, the demand for high-throughput, low-latency data storage and retrieval has exploded. Vast Data’s offering, which leverages all-flash storage and software optimization to maximize efficiency and scalability, has proven to be both timely and technically robust.
Financial Momentum and Rare Profitability
Vast Data’s financial performance has outpaced even optimistic projections. As of early 2025, the company is said to have reached approximately $200 million in annual recurring revenue (ARR), with internal forecasts predicting ARR could grow to nearly $600 million within the next year. This trajectory puts Vast among the fastest-growing companies in the AI hardware and infrastructure space.
Even more striking is its reported financial discipline. At a time when many AI startups are burning through cash to support scale, Vast has emerged as one of the few companies in the sector that is free cash-flow positive. This rare combination of rapid top-line growth and operational profitability is seen as a key driver of investor interest — and a sign that the company could be preparing for an eventual public listing.
To that end, Vast recently hired its first chief financial officer, a veteran executive with public market experience. While the company has made no formal announcement regarding IPO plans, the addition of financial leadership with a track record of managing public-company transitions has fueled speculation that a listing could be on the horizon within the next 12 to 24 months.
Nvidia and CapitalG: Strategic Alignment
The participation of Nvidia and CapitalG in the upcoming funding round is notable not just for the capital involved but for the strategic implications. Nvidia, which dominates the GPU market, has steadily expanded its investments in complementary infrastructure to secure its position at the center of the AI value chain. Supporting Vast Data aligns with Nvidia’s ongoing efforts to ensure that the broader AI ecosystem — from networking to storage — is optimized to unlock the full potential of its hardware.
For CapitalG, the move underscores Alphabet’s deepening commitment to the infrastructure layer of artificial intelligence. While Alphabet has its own AI-focused projects through Google DeepMind and Google Cloud, investing in foundational platforms like Vast allows the tech giant to gain exposure to broader industry shifts, including enterprise and third-party AI deployment at massive scale.
The combination of Nvidia’s technological backing and CapitalG’s platform reach could provide Vast with more than just capital. It offers validation and acceleration, opening doors to new markets, partnerships, and technical integrations.
Competitive Landscape and Strategic Positioning
Vast Data operates in a fiercely competitive sector, where rivals such as WekaIO, DDN, and traditional enterprise storage vendors continue to fight for market share. But Vast’s focus on AI-specific infrastructure, combined with its scalable architecture and early partnerships with major AI compute providers, has helped it carve out a unique position.
The company already counts several high-profile AI developers and data center operators among its customers. Industry observers have noted that Vast’s systems are being used by some of the most compute-intensive AI projects in the world — including national research labs, defense agencies, and large-scale AI startups building foundational models.
In many cases, Vast’s systems are being paired directly with GPU clusters from Nvidia, creating a tightly coupled solution that eliminates data bottlenecks and maximizes compute efficiency. That level of integration is likely a major reason Nvidia is doubling down on its support for the company.
Looking Ahead
Should the current round of funding close at the upper end of expectations, Vast Data would not only become one of the most richly valued private AI infrastructure startups, but also a prime candidate for a blockbuster IPO.
In an industry defined by fast change and fierce competition, Vast has managed to scale quickly, remain profitable, and win over some of the most powerful names in tech. With AI infrastructure spending expected to surge over the next decade, Vast Data is now poised to play a foundational role in how large-scale artificial intelligence systems are built and deployed — from research labs to the cloud, and everywhere in between.
