30% DataStore Only 70% Multi-Product

The important shift is that VAST is no longer landing mainly as a storage vendor, it is increasingly getting bought as a full AI data stack. Roughly 30% of customers are now DataStore only, while about 70% use three or more components. That mix flipped from about 70% DataStore only two years earlier, driven by AI labs, neoclouds, and enterprises buying packaged workflows that combine ingestion, vector storage, orchestration, and access control.1 2

• The customer base breaks into three groups. Early adopters often began with storage only. AI labs and AI clouds more often started on the whole stack from day one, because they needed storage, database, and orchestration together for training and inference workloads.1
• In enterprises, the bundle can be hidden inside a finished product. A document can be ingested through DataEngine, turned into vectors in DataBase, and exposed through a role aware chatbot, so the buyer may think they purchased one AI solution rather than several separate infrastructure products.1
• This matters economically because VAST sells a unified software platform priced around deployed capacity, replacing separate storage, warehouse, ETL, and compute tools. More customers using three or more layers means larger wallet share per account and a bigger market than storage alone.2 3

Going forward, the mix should keep tilting toward multi product adoption as AI workloads move from raw storage into retrieval, orchestration, and governed enterprise agents. If VAST keeps turning storage deals into full stack deployments, it moves from a niche infrastructure layer toward the default operating layer for large scale AI data systems.1 2