On-Premise Inference

On-Premise Inference runs AI models entirely inside an organization's own datacenters or private cloud — keeping data, prompts, and outputs behind the corporate firewall. The approach is essential for highly regulated industries (healthcare with HIPAA, financial services, defense, government with FedRAMP High) and for sensitive use cases involving trade secrets or large volumes of personal data. Hardware options range from NVIDIA H100/H200 GPUs in racks to AMD MI300X clusters to Intel Gaudi 3 systems. Software stacks include vLLM, llama.cpp, NVIDIA Triton, Hugging Face TGI, and enterprise platforms like Red Hat OpenShift AI. Open-weight models like Llama 4, Mistral, Qwen 3, Phi-4, and DeepSeek V3 make competitive on-premise inference practical. AI governance, AI compliance, and AI risk management programs treat on-premise inference as the gold standard for sensitive workloads — supporting responsible AI through full data sovereignty in regulated enterprise AI deployments worldwide.

Centralpoint Is On-Premise AI Governance by Design: Oxcyon's Centralpoint AI Governance Platform installs inside your perimeter — supporting on-prem Llama, Mistral, and other embedded models alongside cloud APIs (OpenAI, Gemini) when you choose. Centralpoint meters every LLM call, keeps prompts and skills strictly on-premise, and embeds chatbots into your portals via one JavaScript line.


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