We detected 95 companies using VAST Data. The most common industry is Software Development (9%) and the most common company size is 10,001+ employees (29%). We find new customers by discovering URLs with known URL patterns through web crawling or modifications to subprocessor lists.
Source: Analysis of Linkedin bios of 95 companies that use VAST Data
Company Characteristics
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Shows how much more likely VAST Data customers are to have each trait compared to all companies. For example, 2.0x means customers are twice as likely to have that characteristic.
Trait
Likelihood
Funding Stage: Post IPO debt
896.3x
Company Size: 10,001+
117.0x
Company Size: 1,001-5,000
33.8x
Company Size: 201-500
5.6x
Country: United States
5.3x
I noticed that VAST Data's customers are predominantly organizations dealing with massive computational workloads and data-intensive operations. These aren't your typical SaaS companies. They're financial services firms running quantitative trading algorithms, entertainment companies rendering visual effects for blockbuster films, biotechnology labs analyzing genomic data, telecommunications giants managing network infrastructure, and AI companies training large language models. What unites them is the need to process, store, and analyze enormous volumes of data at high speed.
These companies skew heavily toward mature, established enterprises rather than early-stage startups. My analysis shows that most have employee counts in the thousands or tens of thousands. Many are publicly traded (BlackRock, Visa, General Motors, Walmart) or have received substantial late-stage funding. Even the smaller organizations in the list tend to be well-funded (Cerebras at Series G with $1.1B, Anduril at Series G with $2.5B) or established players in their markets. The typical customer has been operating for years or decades and has the budget for premium infrastructure.
๐ง What other technologies do VAST Data customers also use?
Source: Analysis of tech stacks from 95 companies that use VAST Data
Commonly Paired Technologies
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Shows how much more likely VAST Data customers are to use each tool compared to the general population. For example, 287x means customers are 287 times more likely to use that tool.
I noticed that VAST Data customers share a distinct profile: they're enterprise-scale companies heavily invested in sophisticated customer experience management and enterprise-grade security infrastructure. The combination of tools like Qualtrics, Medallia, and Glean alongside Okta Advanced Server Access tells me these are large, mature organizations that need both massive data infrastructure and the management tools to govern it effectively.
The pairing of VAST Data with Medallia and Qualtrics is particularly revealing. These companies are collecting enormous volumes of customer feedback and experience data that require serious storage and processing capabilities. VAST's high-performance storage naturally complements the data-intensive nature of enterprise experience management platforms. Similarly, the presence of Glean, an enterprise search tool, suggests these organizations have massive internal knowledge bases and data repositories that employees need to navigate quickly. This makes perfect sense alongside VAST's infrastructure, which is designed to handle petabyte-scale data operations.
The Okta Advanced Server Access correlation is equally telling. Companies using this level of security tooling are managing complex, distributed infrastructures with strict compliance requirements. They're not startups experimenting with bleeding-edge tech, they're established enterprises with mature security postures and significant regulatory obligations.
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