Private AI assistants
A sanctioned alternative to ChatGPT for your team. Your staff are already pasting company data into public AI tools. Give them one that runs inside your network instead.
On-premise AI for business
Your own AI. On your servers. Your data never leaves.
LocalHostAI is an on-premise AI solutions agency. We build private AI assistants and fine-tuned language models that run entirely on your company’s own hardware, so customer data, documents, and know-how never touch a third-party cloud. You own the model. We make it work.
your-server · localhostai
$ localhostai status
modelllama-3.3-70brunning on your hardware
location127.0.0.1your server room
data sent to third partiesnone
per-token API fees€0
$
- Runs on your infrastructure
- Nothing sent to third parties
- No per-token fees
- You own everything we build
Services
What can a private AI do for your business?
On-premise AI deployment
We install and run open-source models on a server in your rack or in your private cloud. Works fully offline where it has to, including air-gapped environments.
Models trained on your data
Fine-tuned on your documents, tickets, and contracts, so the model speaks your business, without your data ever training someone else's model.
How it works
From assessment to a model you own.
- 01
Assessment
We map where AI actually helps in your business and what data it needs. You get a written plan with real costs before anything gets built.
- 02
Build
We fine-tune and test the model on your data, under NDA, on your infrastructure or on isolated hardware that is wiped after handover.
- 03
Deploy & hand over
It runs on your hardware. We train your team, then support it for as long as you want, but you own it either way.
Why on-premise
Why run AI on your own servers?
Control
If you can't audit where a prompt goes, you can't promise a customer where their data went. A model on your own servers gives you one honest answer: nowhere. Every prompt, every document, every log stays inside your network.
Cost
API bills scale with every prompt, forever. That's rent, and it grows with usage. Hardware you own amortises. The heavier your AI use, the sooner owning beats renting; the assessment puts real numbers on your case instead of a generic promise.
Compliance
EU AI Act Article 50 transparency obligations have applied since 2 August 2026. High-risk obligations were deferred to 2 December 2027, so you have time to do this properly instead of in a panic. When AI runs on your own servers, the where-is-our-data question has a one-word answer. Here is the full AI Act timeline and what self-hosting changes.
On-premise isn’t for everyone. If you have no compliance driver and a small API bill, the cloud is fine. We’ll tell you that in the assessment.
FAQ
Questions businesses actually ask.
Is it safe to put my company's data into ChatGPT?
It depends on the tier, and on how much you trust a policy you can't verify. Consumer tools may retain your inputs and can use them for training; enterprise tiers promise otherwise, but you're trusting a document, not something you can audit. A model running on your own hardware removes the question entirely: there is no third party to trust.
What does on-premise AI cost?
Every build is scoped and quoted individually. Model size, hardware, and how deeply it integrates with your systems drive the cost; two businesses rarely land on the same number. The comparison that matters is against your monthly API spend, which never stops. Get a quote and we'll put real figures on your specific case.
Is a private AI worth it for a small business?
Not always. If you have no compliance driver and a small API bill, staying on the cloud is the sensible choice, and we’ll say so in the assessment. It becomes worth it when your data is sensitive, your usage is heavy, or a regulator or auditor is asking questions about where that data goes. We wrote down the criteria we use: when not to self-host an LLM.
Can AI run without an internet connection?
Yes. Open-source models run fully offline once installed on your hardware. For environments that require it, we deliver air-gapped deployments with no connection in or out.
Are open-source models as good as ChatGPT?
For scoped business tasks like answering from your documents, drafting in your formats, or sorting your tickets, a fine-tuned open model is competitive. For open-ended frontier work, no, not yet. Most business use is scoped, which is why this works.
What happens to our data during the build?
We work under NDA and a data processing agreement. Training happens on your infrastructure, or on isolated hardware that is wiped after handover. Your data never trains anyone else's model.
Do we need our own IT team to run it?
No. We support what we build, or hand over runbooks to whoever already runs your servers. If a model needs a team of engineers to keep it alive, we built it wrong.