One Data Foundation for Every Stage of AI
Run data preparation, model training, retrieval, inference, and AI pipelines on one governed platform that scales from enterprise AI to GPU clouds and hyperscalers, keeping GPUs productive and data continuously available from edge to cloud.
Trusted by the World’s Leading Artificial Intelligence Organizations
“The VAST AI Operating System underpins key aspects of how we design and deliver our AI cloud. This partnership enables us to deliver AI infrastructure that is the most performant, scalable, and cost-efficient in the market, while reinforcing the trust and reliability of a data platform that our customers depend on for their most demanding workloads.”
AI Infrastructure Must Support the Entire Intelligence Loop
AI has evolved from isolated training jobs into a continuous loop of data preparation, training, retrieval, inference, and automation. Infrastructure built for separate stages cannot keep pace.
Centralized Model Training
AI Inference
Continuous AI Workloads
Unified AI Infrastructure
One Platform for Every AI Workload
The VAST AI Operating System unifies data, database services, event-driven compute, and global access on one DASE foundation.
Consolidate
Serve training, retrieval, inference, and AI pipelines from one unified, governed data foundation.
Accelerate
Power real-time AI pipelines with continuously refreshed data, low-latency retrieval, and event-driven automation.
Activate
Run data preparation, vectorization, inference, and automation directly where data lives.
Scale
VAST's DASE architecture delivers exabyte-scale AI infrastructure from enterprise deployments to hyperscale GPU clouds.
Explore Artificial Intelligence Use Cases
Choose the architecture that matches your AI strategy: build enterprise AI, serve inference at hyperscale, or train models across massive GPU environments.
Go Deeper on VAST AI Infrastructure
Understanding VAST AI Infrastructure
What is the VAST AI Operating System
What is the VAST AI Operating System
The VAST AI Operating System is a unified platform for building, deploying, and operating AI at enterprise and hyperscale. It combines high-performance data services, databases, event-driven compute, and global data access to support the entire AI lifecycle—from data preparation and model training to retrieval, inference, and continuous AI pipelines—on one governed architecture.
How is VAST different from traditional AI storage?
How is VAST different from traditional AI storage?
VAST is more than a storage system because it combines high-performance data services with database, vector, streaming, and compute capabilities. VAST DataStore feeds training and inference workloads, VAST DataBase supports analytics and vector retrieval, DataEngine executes pipelines, and DataSpace extends governed access across locations. All services operate on a common DASE foundation.
How does VAST keep enterprise AI data current and governed?
How does VAST keep enterprise AI data current and governed?
VAST keeps data, metadata, vectors, and event-driven pipelines within a unified governance model. New data can be ingested, transformed, vectorized, and made available to retrieval and inference workflows without copying it into separate databases. Consistent identity, security, and access policies apply across structured, unstructured, streaming, and vector data.
How does VAST support vector databases and RAG?
How does VAST support vector databases and RAG?
VAST DataBase provides a native vector store that combines structured data, files, objects, vectors, and metadata on one platform. Rather than synchronizing embeddings into a separate vector database, organizations can continuously ingest, update, and retrieve vectors alongside enterprise data. Native hybrid SQL and vector search enables RAG applications to work with fresh, governed context without maintaining duplicate infrastructure.
How does VAST support AI training and inference on one platform?
How does VAST support AI training and inference on one platform?
The VAST AI Operating System supports both large sequential workloads, such as distributed model training and checkpointing, and the low-latency random-access patterns required for retrieval and inference. Built on DASE architecture, compute and storage scale independently, allowing enterprises, neoclouds, and hyperscalers to consolidate AI workloads that traditionally require separate infrastructure.
Bring Us Your Hardest AI Infrastructure Challenge
Whether you are training frontier models, operating a GPU cloud, or building enterprise AI, VAST experts can help map your workload, data path, and scaling requirements to the right architecture.