Regulated & privacy-critical
For a lot of organisations the AI conversation ends at compliance. The capability is obvious and the answer is still no, because the records cannot be sent to somebody else's service and nobody can promise otherwise.
Who: Healthcare-adjacent, legal, finance, insurance, government contractors. Anywhere client confidentiality or data residency rules out cloud AI.
A private-AI readiness assessment, then a pilot, then managed private AI.
Private AI
All the capability, none of the exposure: AI running on your own hardware, behind your firewall, answering only to your permissions. When the rules say the data can't leave, it doesn't.
For:legal, medical, finance, government, anywhere confidentiality is the law
Paperwork reader
Bills, forms, warranty claims, registrations: it reads them, pulls out what matters, files it where it belongs, and queues anything odd for a person to check. The stack on the desk stops being a stack.
For:offices drowning in documents
The Business Brain
Ask your business a question out loud: “what's my real margin this month, which quotes are stalling, who hasn't paid?” The answer comes back in seconds, from your own live data. Not a dashboard. A colleague.
For:every owner who's tired of pulling reports
Agents on watch
The stalled deal gets a nudge. The overdue invoice gets chased. The quiet account gets flagged. Around the clock, before anyone thought to look, and nothing reaches a customer without a person's OK.
For:any business with more moving parts than eyes
Most AI products work by sending your material somewhere else to be processed. For regulated work that is the end of the discussion, whatever the vendor's assurances say, because the obligation is about where data goes rather than about how carefully it is handled once it gets there.
That is a genuine constraint and not an excuse. The mistake is treating it as a reason to do nothing, when what it actually rules out is one architecture rather than the capability itself.
The models run on hardware you control, inside your own network. Documents, records and questions are processed there and stay there. Nothing is sent to an external service, which means the compliance question has a factual answer rather than a contractual one.
The capability is real: reading and summarising documents, answering questions across your own records, drafting, monitoring. What changes is the location, which is precisely the thing your obligations are about.
In regulated work it is not enough for a system to behave correctly. You have to be able to demonstrate what it did, when, on whose instruction, and what it had access to.
So the logging is part of the design rather than a feature: every query, every document touched, every action, retained where your own retention rules apply. When somebody asks what the system did in March, that is a question with an answer.
Ask your business anything
Questions
That the models run on hardware you control, inside your own network, and your data is processed there. It is not a cloud service with a privacy policy attached. Nothing is transmitted to an external provider, which is why the compliance answer is factual rather than contractual.
No on both counts. The model does not train on your material, and because it runs inside your environment there is nowhere for the data to be sent. That property is a consequence of the architecture rather than a setting somebody could change later by accident.
From the logs, which are designed for that purpose rather than for debugging. Every query, the documents it accessed, the action taken and the person who asked are recorded, retained under your own rules and exportable. The point is that the answer exists before anyone asks the question.
The constraint is real. It rules out one architecture, not the capability.
Built in Grand Rapids, Michigan, and put to work wherever your business is.