Artificial Intelligence (AI) infrastructure seems to be extremely lucrative right now. AI infrastructure provider VAST Data said on Wednesday that it was valued at $30 billion in its latest funding round, which included primary and secondary capital of about $1 billion.
As per Reuters, the round, series F, was led by Drive Capital, with Access Industries acting as co-lead, and included participation from existing investors including Fidelity Management & Research Company, NEA, and Nvidia.
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“The scale and speed of AI adoption are creating a new class of infrastructure company,” said Chris Olsen, co-founder and partner at Drive Capital. “VAST is emerging as the clear leader in this category.”
What is VAST Data?
VAST Data is an AI infrastructure and data platform company founded in 2016 by Renen Hallak (CEO), Jeff Denworth, Shachar Fienblit, and Alon Horev. Hallak previously worked in high-performance storage engineering at Dell EMC, which influenced the company’s approach to rethinking enterprise storage systems. The company is headquartered in New York, USA, and also maintains significant engineering and operational presence in Israel and other global locations.
VAST Data emerged from stealth around 2019 after developing a new storage architecture called DASE (Disaggregated and Shared Everything). Its core idea is to eliminate traditional storage tiering (hot, warm, cold data layers) and instead provide a single unified platform combining storage, database, and compute capabilities for large-scale data environments.
The platform is designed for AI and analytics workloads, where massive datasets must be accessed at high speed by GPU clusters for training and inference. This positioning makes VAST part of the broader AI infrastructure stack rather than an AI model developer.
What VAST Data’s trajectory really highlights is a broader structural shift happening in the technology industry: AI is no longer just about models, but about the infrastructure that makes those models possible at scale. As enterprises and hyperscalers race to deploy increasingly large and complex AI systems, the bottlenecks are no longer limited to algorithms or compute power alone. Instead, data movement, storage efficiency, and real-time accessibility have become equally critical constraints.
Rather than competing in the highly visible race to build foundation models, they are embedding themselves deeper in the technology stack, enabling others to build and train those models more efficiently. This position often translates into strong demand resilience, since nearly every major AI initiative depends on robust data infrastructure underneath it.
The scale of recent funding activity and reported valuations also reflects investor belief that AI infrastructure could evolve into a foundational layer of the global digital economy, similar to how cloud computing reshaped enterprise IT over the past decade. However, it also signals intensifying competition, as both startups and established tech giants are investing heavily in similar capabilities.
The significance of VAST Data lies less in any single product and more in what it represents: the emergence of a new category of infrastructure companies purpose-built for AI-first computing. If AI continues along its current trajectory, the importance of this underlying layer will likely grow in parallel with the models it supports, making it one of the most strategically important segments in the technology ecosystem.