White Paper

Race to the Top: The Case for Building an AI Cloud Your Customer Cannot Leave

Your GPU business is a commodity. Your data services don’t have to be. AI cloud providers competing on GPU supply alone are in a race to the bottom. This paper maps the full data service stack your customers are already paying hyperscalers for and shows how to capture it. Dive into this white paper to discover:

Where the real margin lives. Event Broker, Vector Store, and NFS High Performance services sit at 93–98% gross margin. Your customers are running them on AWS and Azure today because you don't offer them yet.

What model builders actually need. The full AI lifecycle requires KV cache offload, RAG vector search, streaming event brokers, and observability pipelines, none of which are GPU IaaS.

One platform, marginal cost. If you're already running VAST for object and file storage, the full service catalog is available on infrastructure already deployed with no new integration projects.

Enterprise multi-tenancy, solved. Per-tenant BYOK encryption, atomic permission propagation across file/object/table/vector, and disaggregated shared KV cache are the three requirements conventional stacks fail at scale.

Download the white paper today.

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