Give your whole team a private AI assistant. Like ChatGPT, but running entirely on your own hardware. Your conversations, documents, and queries never leave your building.
No cloud accounts. No API keys. No data processing agreements with third parties. Just capable AI running on hardware you control.
We deploy open-source models including Llama, Phi, and Qwen, running locally on your hardware. No API calls out. No tokens billed to a third party.
A clean, browser-based chat interface your team will recognise from day one. Minimal training required. Works like the tools they already use - without routinely sending data externally.
Upload contracts, reports, and internal documents and ask questions against them. All processing happens on your hardware. Client files can remain under your control.
One fixed monthly cost covers your entire organisation. No per-seat pricing. No usage caps. Add team members without adding to your bill.
We handle model updates, security patches, and platform monitoring. You get AI capability without needing an ML engineer on staff.
Private AI integrates with n8n and Dify if you run them. Use your local models as the AI brain inside your workflows and applications and entirely within your infrastructure.
Cloud AI tools call themselves private. They're not. Here's the structural problem.
When you use ChatGPT, Copilot, or Gemini, your prompts and documents are processed on US-owned infrastructure. Subject to US law. Accessible to US federal authorities under the CLOUD Act and FISA Section 702: regardless of where the servers are located.
Legal practices, healthcare providers, and financial services firms operate under obligations (NDAs, GDPR Article 9, FCA SM&CR, SRA COLP) that cloud AI tools make extremely difficult to satisfy. In-house counsel is increasingly advising against them.
Per-seat and usage-based models mean cloud AI costs scale directly with headcount. For organisations with 20 or more staff using AI regularly, on-premise becomes cost-competitive and delivers sovereignty as a permanent dividend.
No extended IT projects. No internal resource requirements. We handle the entire deployment.
We spec and configure the right hardware for your team size and workload. Mini Server for teams up to 10, Compact Server for 10–50 concurrent users. Ships pre-configured.
Remote installation typically takes one day. We deploy the models, configure the chat interface, set up user access, and connect to any existing n8n or Dify infrastructure you run.
Your team gets access on day one. We handle ongoing monitoring, model updates, and support. No dedicated AI team required.
If you're evaluating on-premise AI, you probably recognise at least one of these situations.
If your work involves NDAs, privileged communications, or sensitive client information, cloud AI can create legal exposure. On-premise materially reduces it.
GDPR, FCA, CQC, SRA: regulatory frameworks that make cloud AI difficult to justify. On-premise gives your compliance team something they can actually sign off on.
Once your team reaches 20+ regular AI users, on-premise becomes cost-competitive with per-seat cloud subscriptions and delivers data sovereignty as a permanent benefit.
You want to give your organisation AI capability but don't have the engineering resource to build and run it. We provide the infrastructure, the models, and the ongoing management.
Direct answers. No sales language.
Configure your setup online. Tell us what you need and we will send a tailored quote. No sales call required.
Delivered in under four weeks. Supported every day after that.