Aiconomy

On-Premise AI

Running AI models on locally owned and operated hardware within an organization's own facilities, rather than using cloud-based services, typically chosen for data sovereignty, security, or latency reasons.

On-premise AI is preferred by organizations in regulated industries (healthcare, finance, defense) where data cannot leave secure environments. The market for on-premise AI infrastructure grew 35% in 2024 as enterprises deploy private GPU clusters. NVIDIA's DGX systems ($200,000-500,000 each) are purpose-built for on-premise AI. Running AI on-premise requires significant upfront capex and specialized staff but eliminates recurring cloud costs and data transfer concerns. Approximately 15-20% of enterprise AI workloads run on-premise, with the share growing as organizations scale beyond proof-of-concept deployments.

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