Private meets Intelligent
Danubian AI deploys private large language models on your own — or dedicated, single-tenant rented — hardware. Every prompt, every document, every answer stays inside your perimeter.
Frontier open-weight models — GLM · Mistral · Qwen · DeepSeek
Built for industries where confidentiality is non-negotiable
Why private AI
The value of an AI assistant collapses the moment your team has to think twice about what they type. Private deployment removes the hesitation — and the risk.
“Our associates finally have an AI they can brief like a colleague — every draft, every memo, every live case file — without a single word leaving the firm.”
Deployments
On-premise
Frontier models installed inside your own data centre or office. Nothing crosses your firewall — not prompts, not weights, not logs.
Explore on-premiseDedicated hosted
Dedicated GPU infrastructure leased in your name and locked to your keys. We deploy and operate it — you keep root.
Explore dedicated hostedModel catalogue
Benchmarked on your workflows before anything ships, and swappable as the frontier moves. The weights are yours to keep.
Flagship · Z.ai
Our default frontier deployment. GLM leads open-weight benchmarks in agentic work — tool use, long-horizon coding, document-heavy analysis — which is what an enterprise assistant actually does all day. Every deployment tracks the latest GLM release.
Reasoning specialist
Frontier-grade reasoning and mathematics at a fraction of frontier cost — the thinking model for analysis-heavy work.
671B MoE · 128K context · MIT
The generalist family
A model for every slot — from edge-scale to frontier MoE — with best-in-class multilingual coverage.
0.6B–235B · 128K context · Apache 2.0
Lean & fast
Dense, efficient and dependable. Runs serious utility on a single node — ideal for high-volume, latency-sensitive tasks.
24B dense · 128K context · Apache 2.0
The engagement
We map your workflows, data sensitivity and hardware, then select the models, sizes and guardrails that fit — starting with a fixed-fee pilot.
Our engineers install, tune and integrate the stack behind your existing access controls. Typical go-live: two to six weeks.
Monitoring, updates and optimisation for as long as you run it — with full documentation and handover the day you ask for it.
Security posture
Contracts and certifications are promises. Physics is a guarantee. We put the model where your data already lives — so confidentiality isn’t a policy, it’s a property of your infrastructure.
The best open-weight models available — GLM, Mistral, Qwen, DeepSeek and others — selected against your accuracy, latency and budget targets. You can run several side by side and swap as the frontier moves. You are never locked to one vendor's model.
No. Inference happens inside your perimeter, so prompts, documents and model responses never reach us. Where our engineers touch hardware at all, it is with your approval, under your supervision — and they still see none of your data.
It depends on your models and workload. A single multi-GPU server can serve a department; larger organisations run multi-node clusters. If you don't own hardware, we rent dedicated single-tenant GPUs in your name and your chosen region.
Yes. Fully offline deployments — including model and software updates delivered as signed offline bundles — are available for regulated and classified environments.
Those run on vendor clouds and rely on contracts and certifications. We move the model itself onto hardware you control, so confidentiality is a physical property of your infrastructure — and your costs are fixed, not metered per token.
A pilot typically goes live in two to six weeks: roughly one week to assess, one to three to deploy, and a parallel rollout with your team. Handover documentation is delivered from day one.
Get started
Whether you’re a law firm, a hospital group or a bank — if your data can’t leave the building, your AI shouldn’t either.