Training AI models at scale requires a new foundation: The VAST AI Operating System. Designed for the demands of exabyte-scale data and massive GPU clusters, VAST unifies storage, database, and compute into a single, simplified layer. Powered by our DASE architecture, VAST eliminates complexity and provides the infrastructure intelligence needed for continuous AI development and deployment.
Servicing over 1 Million GPUs, VAST Data is the standard for the world's most demanding AI Cloud Service Providers
To train competitive AI models, you need to move massive volumes of data to thousands of GPUs continuously, without interruption, at consistently high throughput.
That sounds simple. But at exabyte scale, most infrastructure breaks down. Storage becomes the bottleneck. Traditional checkpoint approaches interrupt progress. Scaling performance means scaling everything, including what you don’t need. Tuning becomes constant. And every delay slows the path to your next model.
VAST AI Operating System is built upon the revolutionary Disaggregated Shared-Everything (DASE) architecture, purpose-built to solve these problems.
DASE decouples compute from capacity. As GPU clusters grow, you can scale storage performance on demand without over-provisioning capacity, rebalancing data, or interrupting live training. This lets model builders keep GPU utilization high throughout the training cycle, regardless of GPU cluster size, while also adding capacity independently as source, prep, and training data volumes grow.
What makes the VAST AI OS perfect for AI training is its ability to keep up: not just with data scale, but also with the pace of iteration. When infrastructure doesn’t get in the way you reach the next breakthrough faster.
AI training doesn’t begin or end with storage. Before training, you need to ingest, clean, organize, and label. After training, you need to evaluate, analyze, and serve. Every handoff, copy, ETL job, or silo slows progress and reduces effective GPU capacity utilization. Every delay in deploying infrastructure, tuning for performance, or recovery from failure adds complexity.
VAST removes these barriers by delivering a unified AI operating system that keeps your entire AI pipeline moving smoothly from start to finish.
Teams can access the same dataset simultaneously — whether writing from sensors, loading training data into GPUs, or serving models into production — via file or object protocols. No ETL, duplication or added complexity.
Allow streaming data to write directly into the VAST DataBase via a Kafka-compatible API, then query it in place — no external tools required. Embedded services provide instant visibility with full historical context.
Reduce operational overhead by consolidating core services into a single platform. Fewer systems to manage means faster model delivery, lower costs, and simpler scale-out.
Eliminate downtime spent tuning, scaling, and rebalancing. Our architecture lets infrastructure teams go from hardware delivery to active training in a fraction of the time.
Service providers can deliver multi-tenant GPU-as-a-service at scale, with over 99.999% availability and QoS to meet SLAs. Model builders benefit from built-in reliability, automation, and observability.
Built for AI service delivery. Offers secure multi-tenancy, customizable QoS for SLAs, and dedicated tenant level observability, ensuring stable, high-performing AI environments for every tenant.
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