Right for the sealed material
What an owned AI is for.
The material you can never paste into a cloud tool.
LEGALPrivileged legal matters
Litigation records, sealed filings, discovery you cannot hand to a third party. Privilege stays intact because nothing leaves the building.
HEALTHMedical and patient records
Regulated records read under your confidentiality duty. The data never crosses your network boundary.
WEALTHFinancial holdings and positions
Trust instruments, private financials, live deal rooms. Read the exposures that matter without the corpus touching a vendor server.
RESEARCHUnpublished research
A trial dataset before publication or a manuscript under embargo. Query it and reason across it, on hardware you own.
PRIVATEPersonal journals
The pages that were never meant for anyone else. They stay on your machine, answering only to you.
Why owning the hardware
Confidentiality by architecture.
Not a policy page. A property of where the compute sits.
- Read on your machine. The model sits on the same hardware as the documents, inside your building.
- Never uploaded. No telemetry, no phone-home, no standing access after handover. You own it outright.
- Prove it offline. Pull the network cable and it still answers. If it works unplugged, the file was never leaving.
Design my Garnet →Family office and private builds from $250,000. Enterprise scoped on contact. A conversation, not a checkout.
The files you would never send to a cloud AI, a privileged legal brief, a set of patient records, private financial holdings and positions, an unpublished research dataset, a personal journal, are exactly the documents where AI would help most. The reason you hold back is the whole point: sending a document out of your control is the risk. The moment you upload a file to a cloud AI it travels to a vendor server where it can be logged, retained, sub-processed, or swept into a future model. A single upload can waive attorney-client privilege, move a deal price, or breach a regulatory duty you are personally accountable for. No settings toggle fully removes that exposure, because the risk is structural.
A Garnet build removes it by never letting the document leave. The private AI is installed on hardware you own, inside your building, so the model that does the reading sits on the same machine as the documents. There is nothing to upload and nowhere for a copy to go. There is no telemetry, no phone-home path, and no standing access for Garnet after handover. Garnet builds it, installs it, and leaves you owning it outright. Confidentiality holds because it is a property of where the compute sits, which is why it survives even with the network cable pulled. You can prove it yourself: disconnect the machine from the internet, put a sensitive document in front of it, and it answers exactly the same.
Family office and private builds start at $250,000. Enterprise and institutional builds are scoped on contact. Every build is bespoke, pairing hardware chosen for your setting with software tuned to your documents and workflow, delivered end to end so you own it outright. The first step is a scoping conversation with Garnet about what your confidentiality actually requires, not a sales call and not a checkout.