Local AI Setup
Your documents never leave your office
We configure AI on your own hardware — a setup service for law firms, clinics, accounting practices, and any business that handles data it cannot send to the cloud. Estonia and Finland.
The problem
Tools like ChatGPT are useful, but every document you paste into them travels to a server you do not control. For client files, patient records, and payroll data, that is often not an option — by contract, by professional rules, or simply by common sense. The result is that the firms with the most paperwork are the ones least able to use AI on it. There is a practical alternative: run the AI model on a computer inside your own office, so the documents stay where they already are.
How it works
The document stays on your machine at every step
01
Your document
A contract, a medical record, an invoice — whatever you work with. It stays in your office, on your storage.
02
Your computer
A language model (an LLM — software that reads and drafts text) runs on hardware you own. We select and configure it; the software is open and widely used, we do not sell it.
03
Your result
A summary, extracted fields, a draft — produced on the same machine. Reviewed by your staff before it is used.
Notice what the diagram does not have: an arrow leaving the building. Nothing is uploaded, and the setup keeps working with the network cable unplugged.
Packages
01
Audit and assessment
€1,200
fixed · Written report
- Can your current hardware run a local model — and which one
- Which of your documents are sensitive and which workflows can move to local AI
- Whether you need this at all — a fair share of audits end with us recommending against it
- Written report with a concrete recommendation you can act on with or without us
- The fee is credited in full if you proceed to setup
02
Setup
€3,900
fixed · 2–4 weeks
- Model selection matched to your specific hardware — not to a leaderboard
- Installation and configuration on your equipment, in your office
- Speed measured on your machines and accuracy tested on your real documents
- Written documentation: what works, where it makes mistakes, how to check its output
- Staff training — your team learns to use it and to verify it
03
Ongoing care
€390
per month · Cancel anytime
- Model updates — better versions are released every 6–10 weeks, we test and install them
- Consultations for your team when questions come up
- Troubleshooting when something breaks or slows down
- New use cases set up as your needs grow
Why us
Installing a local model takes an afternoon. Knowing where it breaks takes months.
01
Leaderboards do not predict your hardware
A model that topped the public benchmarks for our working language ran four times slower than acceptable on the specific machine we tested it on. Nothing in the rankings tells you this — only a measurement on the actual hardware does. That measurement is part of every setup we do.
02
One setting: 7 seconds instead of 2.5 minutes
On the same task, on the same machine, a single configuration parameter made the difference between two and a half minutes and seven seconds. Defaults are rarely right for a given machine, and finding this out is exactly the kind of work you are paying for.
03
Some free tools only pretend to work
A popular free program we evaluated displayed convincing file edits on screen while writing nothing to disk. It looked finished; it wasn't. We test what actually landed in the files, not what the interface reports.
04
Finnish name forms trip models up
Finnish inflects names, and models misread the inflected forms — turning one person's name into a different name entirely. In a legal document that is not a cosmetic error. We test for it and document a verification step for names and dates.
We run this setup ourselves, on our own paperwork. A recent example: a decision letter from the migration authority, parsed on a local machine in 7 seconds — every relevant field extracted, including the appeal deadline computed from the dates in the document. Then checked by a person, which is how we teach every client to use it.
Honest limitations
What local AI does not do well
01
It is slower than cloud services. Cloud providers run data centres; you run one machine. For document work the difference is workable, but it is real.
02
It is noticeably weaker for programming — roughly 25 points behind leading cloud models on independent agentic-coding benchmarks. If code is your main use case, local is the wrong tool.
03
Names, dates, and figures must be checked by a person before use. We document where errors occur and train your staff to verify — we do not promise accuracy no model can guarantee.
04
It needs suitable hardware. Some offices already have it; some need a purchase of roughly €1,500–3,000. The audit answers this before you spend anything.
Frequently asked questions