XPndAI builds private, on-premise, and air-gapped AI systems using open-source LLMs — ensuring your sensitive enterprise data never leaves your infrastructure.
End-to-end AI and software engineering with measurable enterprise outcomes.
Deploy open-source LLMs (Llama 3, Mistral, Qwen) on your own servers or private cloud — zero data egress, full control over the model.
Build RAG systems entirely on-premise with local vector databases and self-hosted embedding models — no third-party API calls, no data leakage.
Fully disconnected AI systems for government, defence, and highly regulated industries — all inference runs locally with no external connectivity.
End-to-end GPU server procurement, configuration, and optimized deployment of quantized LLMs for maximum performance within your budget.
Build complete agentic workflows using private LLMs — all data processing, reasoning, and output generation stays within your network boundary.
Usage dashboards, PII detection, output filtering, and audit logging for complete governance of your private AI deployment.
A financial regulatory body required an AI system with zero data egress. We deployed a fully air-gapped RAG system on their on-premise servers using Llama 3 and local vector storage — enabling staff to query 20 years of regulatory documents without any data ever leaving their network.
A defence technology contractor needed an AI coding assistant for classified development work. We deployed a fine-tuned Mistral model on their internal GPU server, integrated with their IDE — providing GPT-4-level coding assistance with complete data isolation from external APIs.
Talk directly to our lead engineers. We audit your requirements, propose the exact architecture, and give you a transparent roadmap — all in one call.