VAST Data unveiled the VAST AI OS, a platform built to fuel the next wave of AI breakthroughs.
The launch is the result of nearly ten years of engineering toward creating an intelligent platform architecture that can harness the new generation of AI supercomputing machinery, unlocking the potential of AI at scale. It is built on VAST’s disaggregated shared-everything (DASE) architecture, a parallel, distributed system architecture that can completely parallelize AI and analytics workloads, federating clusters into a unified computing and data cloud before feeding new AI workloads with near-infinite amounts of data, from a fast tier of storage.
Today, DASE clusters support over a million GPUs around the world in many of the world’s most data intensive computing centers. The scope of the AI OS is broad and will consolidate disparate legacy IT technologies into one simple and modern offering designed to democratize AI computing.
“This isn’t a product release — it’s a milestone in the evolution of computing,” said Renen Hallak, VAST Data’s founder and CEO. “We’ve spent the past decade reimagining how data and intelligence converge. Today, we’re proud to unveil the AI Operating System for a world that is no longer built around applications — but around agents.”
The AI OS consists of every aspect of a distributed system to run AI at global scale:
- a kernel to run platform services on from private to public cloud
- a runtime with which to deploy AI agents
- eventing infrastructure for real-time event processing
- messaging infrastructure
- a distributed file and database storage system for real-time data capture and analytics
The AgentEngine features a new AI agent tool server that provides support for agents to invoke data, metadata, functions, web search or other agents using them as MCP-compatible tools.
AgentEngine allows agents to assume multiple personas with different purpose and security credentials, and provides secure, real-time access to different tools. The platform’s scheduler and fault-tolerant queuing mechanisms also ensure agent resilience against machine or service failure.
Finally, AgentEngine introduces massively-scalable agentic workflow observability, making it simple for developers to enjoy a unified and simple view into massively-scaled and complex agentic pipelines.
