Vast Data: Category Creator in Unified AI Infrastructure Stack

Summary

Modern enterprises are under mounting pressure to capitalize on the AI revolution, with business leaders demanding immediate returns through enhanced speed, agility, and efficiency. While vendors and analysts promote the transformative potential of generative and agentic AI, most enterprise IT teams remain mired in pilots and proof of concepts. Scaling AI presents two fundamental challenges: the complexity of building, deploying, and refining AI pipelines, which are resource-intensive and time-consuming; and second a tooling gap, as the software infrastructure needed to operationalize advanced AI is still in its early stages. Vast Data addresses these challenges by its proprietary AI operating system, a new enterprise software category. This OS is built on its proprietary DASE (Disaggregated and Shared Everything) architecture, which unifies storage, compute, and databases into a single, globally consistent platform. Unlike the fragmented, multi-vendor stacks typical of public clouds, DASE enables real-time analytics, recursive computation, and hybrid-cloud deployment, delivering up to 50% lower total cost of ownership for AI workloads. Purpose-built to support over 100,000 GPU clusters with terabytes-per-second throughput, Vast Data’s platform transforms Nvidia’s raw compute into a fully orchestrated, scalable software infrastructure layer, already validated at scale by customers such as xAI and ServiceNow, among others. Vast Data reported 5x YoY revenue growth in 1Q25, 90% gross margins in 2023, as well as over 300% net revenue retention in 2022, performance metrics that surpass most public software infrastructure peers. The latest funding round ($118M Series E) valued the company at $9.1B, a 146% markup from its valuation of $3.7B post-Series D in May 2021. Manhattan Venture Research (MVR) projects its 2025 revenue between $540M and $700M, with a trajectory toward $2,493M - $3,346M by 2030.

Methodology

Our views on Vast Data are derived from our rigorous research process, involving proprietary channel checks with users, competitors, and industry experts, and synthesizing publicly available information from the company and other reliable sources.

Key Points

Category Creator of AI Operating System for Enterprises: Vast Data is a category creator with its flagship AI operating system for enterprise. This offering solves a fundamental problem faced by enterprises, which is the complexity associated with AI integration. Vast Data is building the infrastructure backbone for autonomous AI, backed by rapid market adoption, deep partnerships, and a unified, technically advanced platform. Its AI operating system model aligns directly with the accelerating pace and requirements of real-world AI deployments.

Strong Moat – High Technological Barrier: Vast Data’s competitive moat is the company’s core intellectual property, purpose-built for an AI-native world. The advantage lies not only in performance but in strong defensibility. Its patented DASE architecture establishes a significant technical moat. As the demand for AI chips stabilizes, the strategic opportunity will move to infrastructure orchestration, a space where Vast Data is well-positioned to lead.

A Broad Customer Roster Affirms its Credibility: A diversified customer base, including Commvault, Dremio, Nvidia, Rubrik, Spark, Splunk, Starburst, Veeam, Vertica, and others, has realized significant value from adopting Vast Data, reinforcing the platform’s credibility. Vast simplifies data management on any scale, offering a unified space for capacity and performance, with centralized access to all backups and restores, even at exabyte scale.

Strategic Partnerships Throughout the Value Chain: A diversified range of system partners, such as Nvidia, Lenovo, and Cisco, among others; cloud partners, such as AWS, Coreweave, and Lambda, among others; and software partners, such as Cohesity, Run: ai, and Rubrik, among others, bolsters the technological prowess of the company.

Promising Financials: At the time of the latest series E funding round, Vast reported a 3.3x year-over-year revenue growth rate, positive cash flow sustained over 12 consecutive quarters, and gross margins approaching 90%.

Key Challenges: Organizational Inertia & Intensifying Competition: Enterprises remain cautious, often locked into protracted proof-of-concept cycles as they struggle with number of factors including organizational inertia, data privacy, legacy dependencies, and the challenges of fully integrating AI into complex business workflows, creating a hurdle for mass adoption of Vast Data’s offerings. Additionally, new open-source alternatives or vertical-specific vendors could erode Vast Data’s margins or trigger price wars.

Valuation: The latest funding round ($118M Series E) valued the company at $9.1B, a 146% markup from its valuation of $3.7B post-Series D in May 2021. Manhattan Venture Research (MVR) projects its 2025 revenue between $540M and $700M, with a trajectory toward $2,493M - $3,346M by 2030.

Executive Summary

Vast Data is an AI infrastructure startup that has redefined itself as an “AI Operating System for the Thinking Machine.” Its unified data platform integrates storage, compute, database, and orchestration, powering next-generation AI deployments. Vast Data’s recent growth, technological moat, and marquee investors have positioned it as a key player in the global AI infrastructure ecosystem.

Founded in 2016, Vast Data has evolved from a high-performance storage company to an AI operating system pioneer, building a unified, parallel software stack that underpins some of the world’s most ambitious AI workloads. The platform enables real-time data ingestion, contextualization, and delivery to AI agents, featuring modules like DataStore (for file and object storage), DataBase (vector-based indexing), DataEngine (runtime/task scheduling), and AgentEngine (agent orchestration). Trusted by roughly 25% of the Fortune 100, per Futuriom, Vast Data augments its technical edge through integration with major cloud providers and hardware partners. Vast Data ranked in the Forbes AI 50 and CNBC Disruptor 50 lists in 2025, underscoring industry impact.

Why Now?

AI adoption and generative agentic workflows require real-time, scalable data platforms, areas where legacy data infrastructure often fails due to fragmentation and network bottlenecks. Vast Data’s operating system model creates a seamless bridge between hyperscale GPU/AI compute and high-quality, well-organized data, a key enabler for the next wave of AI labs, cloud providers, and enterprises.

Customers such as Pixar and Verizon, as well as leading neoclouds (cloud providers for AI workflows), have embraced Vast Data’s ability to handle mission-critical, data-intensive workloads. Its latest software, Version 5.2, features innovations such as the EBox (Everything Box) architecture, a hardware and virtualization solution that enhances write performance, resilience, and deployment flexibility for public cloud and hybrid scenarios. Expanded automation, namespace management, and global control further reduce operational complexity.

Company Overview

Vast Data is a company that builds next-generation data infrastructure, the tools and systems that help other companies store, manage, and use massive amounts of data, especially for AI workloads. It is not just improving old storage tech; it has reimagined it from the ground up to meet the demands of AI.

DASE: This is Vast Data’s core system. It combines what used to be separate systems for data storage, computing, and processing into one unified platform. Traditional systems store data in one place and process it in another. These back-and-forths waste time and energy. Vast’s DASE puts everything in one place so AI applications can access and process data faster, cheaper, and at a massive scale.

AI Operating System for Enterprises: This is the next layer on top of DASE. It helps manage all the hardware and software needed for AI workloads. It helps customers run AI and data workloads efficiently across huge amounts of computing power, whether in their own data centers or in the cloud. It's like the "brain" that coordinates all the parts needed to run an AI factory.

Vast is targeting the AI infrastructure market, which is exploding right now. Their customers include:

• Large enterprises doing AI R&D (like life sciences, autonomous vehicles, financial services, etc.)

• Government agencies handling massive datasets

• AI companies that need faster, more efficient access to data

• Traditional enterprises undergoing digital transformation and adopting AI

These organizations are all looking for high-performance, scalable, and affordable infrastructure that can handle enormous volumes of data, especially unstructured data (like images, videos, documents, and sensor data).

Vast Data’s AI operating system is adopted by a diverse mix of hyperscalers, cloud AI providers, and large enterprises. Designed for performance, resilience, and flexibility, the platform enables advanced AI application development, including real-time agentic AI, data-driven discovery, and analytics, with secure, automated management.

Key features include:

• DataStore: High-performance, scalable, disaggregated file and object storage.

• DataBase: Vector-enabled database for rapid, contextual AI querying.

• DataEngine: Real-time compute and agent scheduling runtime, automation, and event-driven orchestration.

• AgentEngine: Native orchestration engine for agent-based, generative AI pipelines.

Vast’s EBox architecture ensures seamless data access and resilience in hybrid and cloud environments, while its globally distributed namespace enables unified management across geographies.

In summary, Vast Data is building the infrastructure backbone for the age of autonomous AI, backed by rapid market adoption, deep partnerships, and a unified, technically advanced platform. Its AI operating system model aligns directly with the accelerating pace and requirements of real-world AI deployments.

Competitive Benchmarking

Vast Data stands out in enterprise data storage, with exceptional customer satisfaction metrics. This strong foundation positions the company well for its strategic pivot in AI infrastructure, a move that could significantly amplify its value in the years to come.

Vast Data – Strong Competitive Position

Vast Data is uniquely positioned in the enterprise AI infrastructure market, leveraging its proprietary architecture and unified platform to establish a strong technological moat that sets high barriers for would-be entrants. Powerful ecosystem partnerships, superior performance, and rapid adoption by industry leaders have reduced the bargaining power of both suppliers and buyers relative to rivals. With its integrated, AI-native approach effectively addressing industry fragmentation and complexity, Vast Data faces limited credible substitutes, enabling robust, defensible growth and an attractive profile for venture investment.

Key Positives

Category Creator of AI Operating System for Enterprises

Historically, every major hardware shift, such as the advent of personal computers (PC), smartphones, and wearables, among others, has triggered significant market transformations. But it's not just the hardware that reshapes industries; it's the operating system that enables new ecosystems to form and scale.

Considering the smartphone era, as mobile devices became mainstream, now reaching 81.6% penetration in the US (Exploding Topics), it wasn’t just the device that changed the game. It was Android, a mobile-first operating system, that overtook PC-based incumbents in 2017 and now commands the largest share of the global operating systems market at ~43% (StatCounter, as of September 2025). A purpose-built operating system became the catalyst for a new platform economy.

Today, we’re at a similar inflection point, this time driven by AI. But unlike previous waves, current operating systems weren’t designed with AI at their core. They struggle to support the scale, performance, and architecture required by AI-native applications.

That’s where Vast Data enters the picture. Vast isn’t just building infrastructure; it’s offering a purpose-built operating system designed specifically for AI workloads of enterprises. With a focus on scale, speed, and architectural efficiency, Vast is positioning itself to become the enterprise foundational platform for the AI-native era, much like Android was for mobile use by the general population.

For investors, this represents a familiar but rare opportunity: a platform shift that opens the door for outsized returns and long-term ecosystem dominance

Legacy cloud-era infrastructure is not equipped to support modern AI. It falls short in terms of scale, performance, and data handling required for GPU-driven workloads, causing AI initiatives to stall before they even begin. Teams are forced to manually integrate fragmented tools and systems, leading to bottlenecks and siloed architecture. This complexity stifles innovation before it can take root.

Built on Vast Data’s revolutionary DASE architecture, this operating system is engineered to break critical barriers to scale, performance, and security, ultimately driving real business outcomes from your most demanding AI workloads. The power of the Vast AI operating system is realized through its core, integrated components.

Vast Data is Orchestrating the AI Ecosystem: The Vast InsightEngine removes architectural bottlenecks, enabling real-time, event-driven AI decision-making. Powered by AgentEngine and DataEngine, autonomous agents can instantly process and act on live data.

Use cases include:

• Real-time fraud detection in financial services

• Instant cybersecurity responses

• Predictive maintenance in industrial settings

• Automated content tagging in media workflows

With real-time vector retrieval and event-driven inference, applications access the freshest data continuously, maximizing responsiveness and accuracy.

“Generative AI with RAG capabilities has transformed how enterprises can use their data. Integrating NVIDIA NIM into Vast InsightEngine with NVIDIA helps enterprises more securely and efficiently access data at any scale to quickly convert it into actionable insights.”

- Justin Boitano Vice President, Enterprise AI, NVIDIA

Core Components of the Vast Data AI Operating System:

Real-Time Actions: A containerized compute engine acting as AI’s central nervous system, processing signals instantly and dispatching real-time instructions.

AI’s Knowledge Base: A global database indexing all structured and unstructured data. Enables millisecond-scale search across trillions of vectors and metadata for reasoning and decision-making.

AI’s Infinite Long-Term Memory: Stores every raw data point—images, videos, text, events—at exabyte scale using all-flash storage. This is the foundation for continuous AI learning and insights.

Unified & Global Architecture: Unites all components into a cohesive, secure AI brain—spanning edge to cloud. All data and compute operate within a unified namespace, with consistent APIs and security policies.

Vast Data is Helping Overcome AI’s Core Challenge: Scaling Data Infrastructure: Enterprises are beginning to implement structural changes to unlock long-term value from generative AI, with large organizations leading the shift. According to McKinsey’s latest Global AI Survey, businesses are actively pursuing initiatives that drive measurable impact, redesigning workflows to integrate generative AI and appointing senior leaders to oversee critical areas such as AI governance. Simultaneously, companies are addressing an expanding range of generative AI-related risks, hiring for new AI-centric roles, and retraining employees to support AI deployments. Notably, firms with annual revenues exceeding $500 million are advancing more rapidly than smaller counterparts. Overall, AI adoption, spanning both generative AI and traditional analytical AI, continues to accelerate, with over 78% of organizations now using AI in at least one business function, up from 72% in 2024, per McKinsey’s survey. Adoption of generative AI specifically is growing at an even faster pace.

The generative AI market is forecasted to surge from $71.4 billion in 2025 to $890.6 billion by 2032, reflecting a CAGR of 43.4% (MarketsandMarkets). According to Exploding Topics, 83% of companies now cite AI as a strategic priority. Netflix, for instance, generates $1 billion annually through AI-driven personalized recommendations. Moreover, 48% of businesses leverage AI to harness big data, and 38% of healthcare providers use AI-assisted diagnostic tools. These indicators underscore the rapid enterprise uptake of AI, which in turn requires massive, scalable data infrastructure. Enters Vast Data, tackling the issue head-on with its AI operating system.

AI Innovation Demands Unified, Scalable Infrastructure: Traditional, siloed AI data pipelines and agent workflows constrain innovation. Vast’s AI Operating System addresses this by unifying storage, databases, and application runtimes, creating a single, global operating environment where AI agents can sense, learn, reason, and act.

Agentic AI Requires Unprecedented Scale and Speed: Vast’s DASE architecture delivers breakthrough parallelism to support limitless scalability and real-time performance. Capable of feeding GPU clusters with 100,000+ nodes at terabytes per second, it removes data bottlenecks across large-scale AI deployments.

Enterprise AI at Scale Demands Rock-Solid Reliability: Vast’s DASE architecture ensures enterprise-grade reliability, resiliency, and security—featuring multi-tenancy, fine-grained access controls, automated operations, and real-time auditability to support mission-critical AI agents and extensive GPU infrastructure.

Scaling AI Without Breaking the Budget: Scaling AI doesn’t have to come with runaway costs. Vast’s AI operating system, powered by DASE, delivers radical efficiency, cutting total cost of ownership by over 50% for the most demanding, data-intensive AI workloads.

Strong Moat – High Technological Barrier

Vast Data’s competitive moat is anchored by formidable technological barriers that go far beyond incremental product improvements. This is foundational intellectual property engineered to serve an AI-native world. The heart of this defensibility resides in its DASE architecture, a radical departure from legacy storage and compute paradigms. Unlike typical solutions that bind compute tightly to storage, DASE completely decouples these components and leverages stateless servers and high-speed fabrics, enabling any CPU to access any storage device in the cluster. This enables scalability to tens of thousands of compute nodes and exabytes of flash storage, outpacing competitors still reliant on inflexible, fixed-architecture designs that simply cannot scale for modern, GPU-driven AI workloads.

This architectural advantage is protected by a robust patent portfolio. As of October 2025, Vast Data has 43 global patents (with 93% still active), per GreyB, and a US grant rate of 94.7%, signaling the technical novelty and enforceability of its approach. Importantly, these patents cover foundational techniques like erasure coding, distributed scalable storage, global metadata management, and more, core layers that competitors cannot easily work around without licensing or designing entirely new systems from scratch. The company's heavy US patent footprint further shelters its advances from domestic upstarts, providing the kind of exclusivity VCs seek for long-term returns.

Beyond patents, DASE architecture unifies capacity and performance in a manner that profoundly lowers total cost of ownership, over 50% cheaper for high-scale AI workloads, by eliminating overprovisioning and enabling on-demand scaling of both storage and compute resources. Moreover, the moat is fortified by the complexity and capital intensity required to replicate what Vast Data has built. To match Vast’s exabyte-scale global namespace, high-availability multi-protocol access, and millisecond-scale search across trillions of vectors demands not just copying features, but orchestrating decades of distributed systems research, custom hardware-software integration, and a relentless go-to-market engine. Even large, entrenched vendors are only now talking about similar integrated architectures, lacking proven products in the market. These technical and operational barriers naturally enforce “default vendor” status for Vast Dat in AI projects, an enviable position that new entrants will find challenging to disrupt.

Finally, tight partnerships with technology powerhouses such as NVIDIA, Cisco, and Equinix are embedding Vast Data’s platform deeper into the world’s largest AI deployments. These alliances don't just boost go-to-market velocity; they ensure early access to next-gen hardware capabilities (e.g., NVIDIA’s latest GPUs) and global reach via Equinix’s data center footprint, making the switching cost for customers even higher. For US venture investors, the story is clear: the technological moat at Vast Data is built on a layer of system-level innovation, robust intellectual property, and a network of deep partnerships, all combining to shut out fast followers and position the company as a core long-term winner in the multibillion-dollar AI infrastructure market.

Proprietary DASE Platform Provides Strong Moat: Vast Data’s strategy centers on its proprietary DASE architecture, an innovation that unifies storage, compute, and databases into a single, globally consistent platform. Unlike the fragmented, multi-vendor stacks typical of public clouds, DASE enables real-time analytics, recursive computation, and hybrid-cloud deployment, driving a lower total cost of ownership for AI workloads.

Designed to support 100,000+ GPU clusters with terabytes-per-second throughput, Vast Data’s AI operating system transforms Nvidia’s raw compute into a fully orchestrated, scalable software infrastructure layer. Customers like xAI and ServiceNow have already validated the platform at scale. Vast Data reported 5x YoY revenue growth in 1Q25, 90% gross margins in 2023, as well as over 300% net revenue retention in 2022, performance metrics that surpass most public software infrastructure peers.

While giants like Microsoft and Alphabet span broad technology portfolios, Vast Data focuses narrowly but powerfully on three pillars: AI infrastructure, enterprise storage, and agentic services. This focus enables faster innovation cycles and stronger product-market fit. Its InsightEngine, co-developed with Nvidia, is already powering real-time retrieval-augmented generation use cases across latency-sensitive sectors like finance and autonomous logistics.

Vast Data’s advantage is more than performance; it’s defensibility. Its DASE architecture is protected by patents and creates a meaningful technical moat. As Nvidia’s dominance in AI chips matures, the real opportunity shifts to infrastructure orchestration, where Vast Data is positioned to lead.

With 99.9995% uptime*, a Net Promoter Score of 84, and rapid growth in both bookings and customer expansion, Vast Data offers a compelling ROI-driven enterprise story. As AI moves from hype to mission-critical infrastructure, Vast stands out as a high-growth enabler of this transition. Its breakthrough architecture, best-in-class partnerships, and strong execution make it a frontrunner in the next phase of enterprise AI, where software infrastructure, not just models, defines the winners.

*Note - Each additional 9 represents a 10-fold increase in reliability, and therefore 1/10th the allowed downtime as reliability asymptotically approaches 100%.

A Broad Customer Roster Affirms its Credibility

“With Vast, you have an incredibly performant platform that will take the deduplication, encryption, and compression provided by Commvault further with its similarity-based data reduction, helping further reduce your data footprint with an all-flash platform. Vast's Data Platform is what makes massive, high-speed, instant ransomware recovery possible.”

- Kevin Zawodzinski, Vice President of Sales Engineering, Commvault

“Dremio and Vast Data's partnership embodies our unwavering commitment to revolutionizing the AI landscape and unlocking the full potential of data for organizations,” said Roger Frey, vice president of alliances at Dremio. “This collaboration brings together Dremio's lightning-fast data processing capabilities and the scalability of the Vast Data Platform, empowering our joint customers to extract invaluable insights and make informed decisions at an unprecedented scale. Together, we look forward to shaping a future where AI transforms industries across the globe, driving innovation and pushing the boundaries of what's possible.”

- Roger Frey, VP, Alliances, Dremio

“We’ve created this entire ecosystem that makes it possible for every enterprise to engage AI, transform their data into their own digital intelligence, and connect it into a flywheel that sits on top of Vast and NVIDIA.”

- Jensen Huang, Founder & CEO, NVIDIA

A diversified customer base, including Commvault, Dremio, Nvidia, Rubrik, Spark, Splunk, Starburst, Veeam, Vertica, and others, has realized significant value from adopting Vast Data, reinforcing the platform’s credibility. Demonstrated client benefits include:

Strategic Partnerships Throughout the Value Chain

Vast collaborates with leading technology vendors to deliver high-performance, reliable solutions that drive business value and reduce deployment risk. Its strong ecosystem includes a diverse range of system partners, such as Nvidia, Lenovo, and Cisco, among others; cloud partners, including AWS, CoreWeave, and Lambda, among others; and software partners, such as Cohesity, Run: ai, and Rubrik, among others, enhancing the company’s technological capabilities.

Promising Financials

Vast Data is reportedly seeking to raise several billion dollars in new funding, targeting a valuation between $25 billion and $30 billion. Potential investors include Alphabet, through its independent growth fund CapitalG, and Nvidia, among others. This funding is attracted due to robust financial performance, as the ARR went from $200 million in January 2025 to a projected $600 million ARR by 2026.

At the time of the latest series E funding round, Vast reported a 3.3x year-over-year revenue growth rate, positive cash flow sustained over 12 consecutive quarters, and gross margins approaching 90%. Additionally, co-founder Jeff Denworth framed the Series E raise as a strategic signal rather than a funding necessity. He noted that the capital from multiple rounds remains largely unspent and continues to accrue interest. According to Denworth, “This funding is simply being used to raise awareness of Vast.”

This raises the question of why Vast is pursuing an additional capital raise at this time. One explanation may be strategic signaling. A valuation in the $25–30 billion range could serve as a defensive benchmark against acquisition attempts or as a strong foundation for a potential IPO. It also reinforces investor enthusiasm, helps attract high-caliber talent, and reassures enterprise customers of Vast’s long-term viability. From a competitive standpoint, such a valuation allows Vast to position itself against public storage companies like Pure Storage, which currently has a market capitalization of $17.8 billion, and NetApp at $20.2 billion. However, Vast views itself as a broader AI infrastructure platform rather than a traditional storage vendor and may seek to align more closely with companies like Snowflake, capitalized at $68.4 billion, and Databricks, privately valued at around $62 billion.

Beyond valuation signaling, the new capital could serve multiple operational purposes. While Vast has historically focused on proprietary, in-house software development, the company may now consider selective acquisitions. Funding could also support accelerated R&D initiatives, particularly around high-speed data movement across hybrid environments—connecting customers’ on-premises data centers with public cloud infrastructure. Additionally, Vast may invest in technology partners to strengthen its ecosystem. This includes enabling broader visibility and access to customers’ data estates across storage platforms. Companies such as Arcitecta, Datadobi, Hammerspace, and Komprise provide data mapping and movement capabilities that could integrate with or enhance Vast’s platform. Similarly, data platforms like Databricks and Snowflake manage extensive datasets that Vast’s infrastructure could support more effectively through partnership or deeper integration.

At present, Vast offers a robust data storage and management infrastructure tailored to AI workloads. This differentiates it from data lake and analytics providers such as Snowflake and Databricks, which focus on data processing, analytics, and warehousing. There is a degree of functional overlap, and if Vast views these companies as competitors, it may choose to expand its software stack vertically into adjacent layers of the data and AI stack. However, an alternative approach would be to maintain these firms as partners, consistent with Vast’s existing agreement with Dremio, which pre-dates the current AI wave and supports open data lakehouse architecture.

Key Concerns

Organizational Inertia Slowing Enterprise Adoption

Despite strong top-line growth, Vast Data’s near-term revenue trajectory is tightly linked to the unpredictable pace at which traditional enterprises operationalize AI. Many customers remain cautious, often locked into protracted proof-of-concept cycles as they struggle with organizational inertia, data privacy, legacy dependencies, and the challenges of fully integrating AI into complex business workflows. This inertia is exacerbated in heavily regulated industries or those lacking technical fluency, potentially capping short- and medium-term market penetration. The company’s revenue profile could become lumpy or growth could decelerate if major client rollouts stall or if industry-wide AI adoption fails to reach escape velocity as quickly as investor models predict.

However, Vast Data is differentiated by its established traction among advanced adopters and strong anchor clients like Nvidia and xAI. As a first-mover with deep partnerships, it is uniquely positioned to set de facto enterprise infrastructure standards. When the broader wave of enterprise AI deployment inevitably accelerates, driven by competitive pressure and proven use cases, Vast Data’s platform could become an industry default, poised to capture disproportionate share as laggards move to catch up.

Growing Competitive Landscape

Vast Data’s go-to-market thesis hinges on maintaining a step-function technology lead via ongoing, capital-intensive R&D, a notable risk as hyperscalers (AWS, Azure, Google Cloud) and well-financed startups race to commoditize specialized infrastructure software. There’s a persistent threat that advances in distributed AI compute, new open-source alternatives, or vertical-specific vendors could erode Vast’s margins or trigger price wars, particularly as the vendor ecosystem converges around open interfaces and standards. Without relentless innovation and sharp execution, what is a patent-backed competitive moat today could become porous, diluting pricing power and challenging long-term profitability. The market will scrutinize evidence of sustainable differentiation closely as the category matures.

That said, Vast Data has already demonstrated the ability to sustain high gross margins and positive cash flow even at scale, rare among deep infrastructure startups. Its DASE architecture, defensible IP portfolio, and tightly integrated ecosystem partnerships provide a robust multi-year head start. If management continues to balance ambitious innovation with operational discipline, Vast Data is well-equipped to pull further ahead, making it a category leader.

Industry Overview

Vast Data’s platform eliminates traditional data silos by enabling seamless access and management of both structured and unstructured data across environments—cloud, on-premises, and hybrid. This unification not only reduces operational headaches but also allows instant querying and integration of datasets for AI, analytics, and business operations. For example, AI workflows that once required juggling multiple disconnected systems can now be managed within a single architecture, significantly speeding up development and reducing errors.

With digitalization propelling data growth at unprecedented rates (the global volume is projected to hit 200 zettabytes by 2025, per Cybercrime Magazine), scalability is crucial. Vast Data enables real-time, high-performance processing of massive data sets without incurring the usual overhead and costs associated with legacy storage.

Increasing digitalization raises the stakes for data privacy, compliance, and auditability, especially in regulated sectors. Vast Data’s multi-tenancy architecture provides secure “virtual air gaps” between workloads, guaranteeing clients true isolation, even from system administrators, thus simplifying compliance and building trust. Its efficiency also translates to environmental and infrastructure benefits, with all-flash distributed architectures reducing power and cooling needs for data centers.

The widespread trend toward digitalization drives exponential data growth and demand for advanced AI analytics. Vast Data’s innovative architecture, AI-native integration, secure multi-tenancy, and scalable efficiency make it uniquely qualified to help modern enterprises harness these trends for strategic advantage.

Vast Data operates across three high-growth sectors: the enterprise storage market, the AI operating systems market, and the emerging agentic AI market. With its proprietary technology and a proven product-market fit, Vast Data is well-equipped to expand its presence and deepen its penetration across these domains.

According to The Business Research Company, the global enterprise storage market has demonstrated strong growth, increasing from $146.4 billion in 2024 to $157.3 billion in 2025, representing a CAGR of 7.5%. This momentum is largely driven by the rise of hybrid cloud adoption, the increasing need to manage and store large volumes of data, the proliferation of Internet of Things (IoT) devices, the expansion of big data analytics, and heightened demand for data protection. Looking ahead, the market is projected to grow to $209.2 billion by 2029, maintaining a CAGR of 7.4%. Growth in the forecast period will be supported by the rising need for scalable storage solutions within enterprises, increasing adoption of cloud-based storage, expanding data generation, and overall enterprise IT demand. Major market trends include rapid technological innovation, greater integration of artificial intelligence and machine learning, the evolution of flash storage, and a shift towards software-defined and hybrid cloud storage architectures.

However, macroeconomic disruptions such as the sharp escalation of the US tariffs in the spring of 2025 have significantly impacted the IT sector, particularly hardware manufacturing, data infrastructure, and software deployment. Increased duties on imported semiconductors, circuit boards, and networking equipment have raised production and operational costs for technology firms, cloud service providers, and data centers. Companies that rely on globally sourced components for laptops, servers, and consumer electronics are facing longer lead times and intensified pricing pressures. Concurrently, tariffs on specialized software and retaliatory trade measures from key international markets have disrupted global supply chains and reduced overseas demand for US-developed technologies. In response, the sector is accelerating investments in domestic semiconductor fabrication, diversifying supplier networks, and implementing AI-driven automation to strengthen operational resilience and cost efficiency.

The operating systems market has also shown consistent growth. According to Research and Markets, the market is expected to grow from $47.5 billion in 2024 to $48.6 billion in 2025 at a CAGR of 2.2%. This growth has been fueled by the widespread adoption of personal computing, increased enterprise use of IT systems, evolving software licensing models, and the continuous need for system upgrades. By 2029, the market is projected to reach $52.6 billion, with a CAGR of 2%. Future growth will be driven by continued adoption of cloud computing, the expansion of remote and hybrid work models, the proliferation of mobile devices, growing concerns around data privacy and security, and a focus on sustainable computing practices. Vast Data will capture the enterprise segment of this market.

In parallel, the global agentic AI market is on a steep growth trajectory. According to MarketsandMarkets, the market is expected to expand from $7.1 billion in 2025 to $93.2 billion by 2032, reflecting a CAGR of 44.6%. This growth is being driven by the increasing adoption of agentic AI technologies across industries, as organizations recognize their ability to automate complex tasks, make autonomous decisions, and adapt dynamically to changing environments. These capabilities are unlocking new efficiencies and competitive advantages, positioning agentic AI as a transformative force in enterprise technology.

Vast Data is strategically aligned with the growth vectors of these three markets. With its differentiated technology stack, proven market fit, and operational resilience, the company is well-positioned to capitalize on the accelerating demand across enterprise storage, operating systems, and agentic AI. As these markets continue to evolve, Vast is equipped to scale and lead in delivering next-generation data infrastructure and intelligent systems.

Financials

Vast Data’s Revenue Estimates – MVR Analysis

Disclaimer: Vast Data has not released audited financials and is not expected to do so until it files for IPO. The revenue model and the implied valuation are preliminary and are based on Manhattan Venture Research’s internal assumptions and will be adjusted to reflect any incremental information.

Vast Data is positioned to scale rapidly by leveraging four high-growth markets: AI operating systems, enterprise storage, legacy operating systems, and agentic AI, where even small penetration yields huge revenue potential. The AI operating systems market is projected to expand from $14.9 billion in 2025 to $35.7 billion by 2030, with a 19.7% CAGR. Vast Data at a 3–4% share could generate $1.1–1.4 billion in revenue by 2030, capturing the enterprise segment of this market. The legacy operating systems market grows modestly from $48.6 billion to $53.6 billion in the same period. Even a 0.03–0.05% share contributes another $20–30 million by 2030. The enterprise data storage market increases from $157.3 billion to $224.9 billion. Vast Data’s hypothetical 0.03–0.05% penetration translates into $70–110 million by 2030. The agentic AI market surges from $7.1 billion to $44.6 billion. With just a 3–4% share, Vast Data can capture $1.3–1.8 billion by 2030.

While enterprise storage and legacy operating systems provide stable but modest contributions, Vast Data’s real inflection point comes from AI-driven opportunities (AI operating system for enterprises and Agentic AI). By anchoring in the AI operating system ecosystem for enterprises and scaling into AI agentic services, Vast Data is poised to capture a disproportionate share of growth by 2030, as shown in the table below.

Vast Data has demonstrated an exceptional trajectory in ARR, with a marked acceleration from $1 million in 2021 to $40 million in 2022, followed by a further surge to $100 million in 2023. According to company-reported figures, ARR experienced a 3.6x increase between 2024 and 2025. For this analysis, we assume that ARR is sustained uniformly over the course of each year and that corresponding revenues are realized on a full-year basis.

Building on this foundation, we project revenue growth through 2030 using a progressively moderating year-over-year growth model. Specifically, we apply a growth range of 35–40% in 2026, tapering sequentially to 33–38% in 2027, 31–35% in 2028, 29–34% in 2029, and 27–32% in 2030. Under these modeled assumptions, Vast Data’s revenue by the end of 2030 is estimated to fall within a range of $2,081 million to $3,346 million.

Implied Private Market Valuation

Vast Data is a category creator in the AI operating system for enterprises. While the company currently lacks direct public market comparable, parallels can be drawn from legacy operating system providers, enterprise storage solutions providers, and established enterprise AI firms that have accessed public capital markets.

Among the most relevant comparable are Alphabet, Microsoft, Apple, Pure Storage, Nutanix, C3.ai, LivePerson, and ServiceNow. Alphabet offers Android OS and Chrome OS, Microsoft offers DOS (discontinued) and the Windows line, and Apple has iOS. Pure Storage and Nutanix are enterprise data storage companies. In the enterprise AI comps, C3.ai offers a platform for developing and deploying AI solutions across various industrial sectors, including oil and gas, manufacturing, and retail. LivePerson specializes in conversational AI and commerce software, while ServiceNow offers a natively integrated AI platform tailored for rapid deployment within enterprise workflows.

At the time of their respective initial public offerings (IPOs), these companies were valued at $23 billion (Alphabet), $0.8 billion (Microsoft), $1.7 billion (Apple), $3.1 billion (Pure Storage), $2.2 billion (Nutanix), $4.0 billion (C3.ai), $0.2 billion (LivePerson), and $3.0 billion (ServiceNow). Their annual revenues at that time were roughly $3.2 billion, $197 million, $117 million, $174 million, $49 million, $157 million, $10 million, and $90 million, respectively. These figures yield EV/Revenue multiples of 7.2x, 3.9x, 14.5x, 17.8x, 4.4x, 25.8x, 37.3x, and 32.0x. Averaging across these eight data points produces an implied EV/Revenue multiple of approximately 17.9x.

Applying this to Vast Data’s revenue projections (MVR estimates), a valuation range of $45 billion to $60 billion is achieved for 2030. In this context, an investment in Vast Data today could be 5x-7x by 2030, based on the current valuation of $9.1 billion.

Funding Rounds & Private Valuations

Vast Data has secured around $381 million in funding across five funding rounds. Vast Data’s first mover in AI-powered operating systems for enterprises has led to significant investor interest since 2020. Notably, the company raised $100 million in April 2020, followed by an $83 million series D round in May 2021. The company's ability to attract investment has continued to grow, with its latest funding round – a $118 million Series E in December 2023, with investors including Fidelity Investments, Bond, Drive Capital, and New Enterprise Associates. The latest funding round valued the company at $9.1 billion, a 146% markup from its valuation of $3 billion post-series D in February 2025.

Comparative Public Multiples

The following table shows the public peer multiples of enterprise data storage, enterprise AI, and legacy operating system provider companies. These multiples provide a useful reference for valuing Vast Data. Given the first-mover advantage of Vast Data in the AI operating system for enterprises, we believe the startup’s valuation multiple should command a premium over its public peers.

About Manhattan Venture Partners

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About the Analyst

antosh Rao has over 25 years of experience in equity research with a primary focus on the technology and telecom sectors. He started his equity research career at Prudential Securities and later moved to Dresdner Kleinwort Wasserstein, Gleacher & Co, and Evercore Partners, where he followed Telecom and Data Services. Prior to joining Manhattan Venture Partners, he was the Managing Director and Head of Research at Greencrest Capital, focusing on private market TMT research. Santosh has an undergraduate degree in Accounting and Economics, and an MBA in Finance from Rutgers Graduate Business School. While at Gleacher & Co he was ranked leading telecom equipment analyst by Starmine/Financial Times

Disclaimer

I, Santosh Rao, Head of Research, certify that the views expressed in this report accurately reflect my personal views about the subject, securities, instruments, or issuers, and that no part of my compensation was, is, or will be directly or indirectly related to the specific views or recommendations contained herein.

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