On-prem AI, built by people who've run infrastructure for 25 years

Why an infrastructure company runs your AI

An on-premises LLM is mostly infrastructure and operations — GPUs, serving, quantization, monitoring, security, uptime — and only a little bit "model." That operations layer is exactly what we've done for a quarter of a century: keeping other companies' systems fast, secure, and online, around the clock.

So when we deploy an open-weight model inside your network, it isn't a science project. It's the same team that already runs production infrastructure — with 5-minute incident response and a 99.95% uptime SLA — now pointing that discipline at your AI. That's why we can stand a model up in 72 hours and still stand behind it afterwards.

A short history

• 2000 — two founders, the first machines.
• 2003–2010 — first businesses and our own hosting infrastructure.
• 2010s — full-scope IT outsourcing for enterprise clients.
• Today — 22 engineers across Cyprus and New Zealand, 24/7, and a dedicated on-prem-AI practice: LLMDeploy.

The proof is in the work: we cut a client's $10k/month cloud-AI bill by moving them on-prem (Nocodo), and stood up a 40-GPU inference cluster in 48 hours for a hackathon (Infiano).