Private AI

You shouldn’t have to take anyone’s word for where your data is.

Every AI tool you can subscribe to answers that question with a contract. We think it should be answered by the architecture instead, so we build systems that run inside your own environment, on infrastructure you own, with no access kept by us. What you get is private AI for the document work that fills your people’s days.

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What you get back

The first year

Hours back, every week.

Independent research puts the gain at around 7.5 hours per person per week — roughly £14,000 of productivity per employee, per year. Drafting, summarising, searching across your own documents: the work that fills the day, done in a fraction of the time.

The gain isn’t automatic, though. People trained on it save closer to 11 hours a week; the ones left to work it out alone save half that. The system gives you the floor. Training reaches the ceiling.

→ Reach the ceiling

The next five years

A system you own, at a cost you can predict.

Public AI is a subscription you re-negotiate every renewal — priced per head, on terms set by someone else. Your own system holds its value instead. You fix the cost of your AI for years at a time: flat, regardless of how many people use it. Add fifty staff next year and the bill doesn’t move.

The system is yours. We build it and keep it running, but we hold no access to your data and no grip on your operation. If we disappeared tomorrow, it would keep working.

→ See what you’d own

Belief or Knowledge

Most AI companies ask you to trust that something won’t happen. Sovereign architecture lets you know it can’t.

Architectural guarantees

No external vendor to breach.
No external path in. The perimeter is closed.
No sub-processor chain. You contract the infrastructure directly.
No upstream API — inference runs on your own infrastructure.
No per-seat or usage-based pricing.
Your inference layer, hardened to your standard.
No vendor lock-in.
The model cannot train on your data.

No external vendor to breach.

No external path in. The perimeter is closed.

No sub-processor chain. You contract the infrastructure directly.

No upstream API — inference runs on your own infrastructure.

No per-seat or usage-based pricing.

Your inference layer, hardened to your standard.

No vendor lock-in.

The model cannot train on your data.

From first conversation to working system

The first conversation

We start with a conversation about your work, your data, and what your people actually need. No commitment — you leave it knowing whether this fits, and what it would look like for you.

Built around you

We design and deploy your system to match how your organisation works — sized to your team, your documents, your workflows. You don’t manage the build. We do.

Your private AI, running

Your people start working faster, inside your own environment. The system is yours. You hold the keys; we keep it running.

Discuss your needs →

Architectural Precedent

Your AI. Your infrastructure. Your data — full stop.

The productivity of public AI, on infrastructure you own. The pattern isn’t theoretical — and it isn’t industry-specific.

When Samsung’s semiconductor engineers needed AI they could trust with their most sensitive work, they moved off public tools to a self-hosted system — and hit 80% adoption in 30 days. Not a law firm, not a bank: engineers, with secrets worth more than most. The same approach works for any organisation whose data can’t leave its own walls.

Read the Samsung Case Study

Samsung Semiconductor Inc. — Sovereign AI Deployment

80%

Adoption in 30 Days

Days → HoursWorkflow Reduction

14 daysPilot Duration

100 analystsInitial Cohort

Open Source

The private AI platform, open source.

Fosnie is our self-hosted, open-core AI platform: the productised version of everything on this page. Run it on your own infrastructure, point it at any model, and keep your data inside your perimeter.

Free and open-source under Apache-2.0. Chat, agentic RAG, Deep Research, document work, agents and voice, all running where your data lives, with zero egress by default.

Visit fosnie.dev View on GitHub

Apache-2.0 licence
Self-hosted infrastructure
Any model, local or cloud
Zero-egress by default
Enterprise governance layer

Role-Specific Evaluation

One decision, three perspectives

Adopting AI in a data-sensitive organisation isn’t one person’s call. Here’s what matters to each of the people who’ll weigh in.

For Leadership

Your people move faster — and you can prove it.AI that your organisation owns means your staff get the productivity benefit without your most sensitive work ever leaving your control. The firms and organisations that adopt this well don't just work faster internally — they turn it into something they can show clients and stakeholders: we use AI, and we did it without putting your data anywhere we couldn't account for.

It's a position your competitors on public AI can't claim.Anyone can subscribe to a public AI tool. Very few can say the work was done on infrastructure they own, with data that never left their walls. In sectors where trust is the product, that distinction is increasingly what wins and keeps clients.

Why Private AI

For Risk & Compliance

A controller–processor relationship you can actually see.You hold the contracts directly. The data-processing terms are explicit, the processing is scoped, and there's no opaque chain of sub-processors changing behind the scenes. Your Article 28 obligations are simplified because the supply chain is short and transparent — not buried under layers you can't audit.

Defensible by design.Every action on the system is logged and independently verifiable. If you're ever asked to demonstrate where data sits, who can reach it, and on what basis — the answer is documented, not reconstructed after the fact.

Access Trust Centre

For IT & Infrastructure

You hold the keys — always.No standing access for anyone outside your team, us included. When maintenance is needed, your IT lead opens a gateway, the work happens under full session logging, and it closes again. No permanent credentials sit with a third party.

Nothing leaves unless you route it out.The system runs on dedicated, bare-metalA dedicated physical server, not shared with anyone else, not virtualised. hardware with no outbound network path — data egress is closed at the network level, not just discouraged by policy. No multi-tenant layer, no shared compute, no external API calls leaving the perimeter.

Inspect Architecture

For Leadership

Why Private AI

Own your AI. Control your data. Move faster.

Private AI builds AI systems for organisations that can’t put their data in someone else’s cloud — and don’t have to choose between the two. Whatever you’re trusted to protect stays inside your environment, while your people work at the speed everyone else is racing toward.

Let's talk it through