VAST Data

VAST Data builds an AI Operating System that natively unifies storage, database, and compute to power data-intensive applications and agentic AI workloads. The platform is designed for organizations managing petabyte-to-exabyte-scale data, offering all-flash performance at what the company describes as archive economics. VAST positions itself as eliminating the traditional tradeoff between storage performance and capacity through its DASE (Disaggregated and Shared Everything) architecture.

What It Is

VAST Data's AI Operating System is an enterprise-grade, scale-out data platform that consolidates what were previously separate infrastructure layers — file storage, object storage, a database, and a compute engine — into a single unified system. The platform is built around four core components: VAST DataStore (storage), VAST DataSpace (namespace and data management), VAST DataBase (a distributed database layer), and VAST DataEngine (compute and query execution). Together, these components are designed to let organizations run AI model training, inference, and agentic workloads directly on their data without moving it between systems.

Architecture: DASE and the AI OS

The platform's underlying architecture is called DASE — Disaggregated and Shared Everything — which separates compute from storage while keeping all data accessible to all nodes simultaneously. This design enables horizontal scaling without the storage tiering complexity typical of legacy HDD-based systems. VAST markets the AI OS as the first platform to natively orchestrate storage, database, and compute in a single system, and has published a white paper explaining the architecture in detail. A newer capability called Confidential AI adds an encrypted, isolated runtime environment for running AI models on sensitive data.

Industries and Use Cases

VAST targets a broad set of data-intensive verticals:

• Cloud Service Providers / NeoClouds — GPU-accelerated services for generative AI and LLMs
• Quantitative Trading — real-time backtesting and model training on large market datasets
• Life Sciences — bioinformatic applications requiring high-throughput concurrent flash access
• Animation & VFX — render pipelines with dedicated quality-of-service controls
• Media & Broadcast — consolidated production and archive with per-workflow QoS
• Public Sector — all-flash data lakes at petabyte-to-exabyte scale

Deployment and Consumption Model

VAST is deployed as an on-premises or co-located hardware-software appliance, not as a public cloud SaaS. The company offers a consumption model called Gemini, which allows organizations to pay based on actual usage rather than upfront capacity commitments. The platform supports a range of hardware configurations and is listed as available across multiple supported platforms. VAST also maintains a partner ecosystem and a Cosmos user community for peer support and knowledge sharing.

Support and Learning Resources

VAST provides a multi-channel support and enablement ecosystem:

• Documentation and Knowledge Base hosted at kb.vastdata.com
• Hands-on Demos & Labs for technical evaluation
• Training & Certification through self-paced and instructor-led courses
• Cosmos Community for user discussion and networking
• Direct support via a case management portal, email (hello@vastdata.com), and phone

Why It Matters for AI Infrastructure

As AI workloads shift toward agentic systems that require continuous, low-latency access to large datasets, the traditional separation of storage and compute creates bottlenecks. VAST's platform is designed to collapse that gap by making data immediately actionable at the infrastructure layer. The company's homepage lists customers including CoreWeave, ServiceNow, Adobe, CrowdStrike, and financial firms such as Jump Trading, Man Group, and Squarepoint Capital — though these are vendor-published references and should be understood as such.