Ask anything about this knowledge base…local GPU
A ChatGPT-class assistant over your contracts, policies, drawings, spreadsheets and scans, running on one GPU box inside your network or in your own EU tenant. Every answer cites the page it came from. No document, no question and no answer ever reaches a third-party API.
Illustrative conversation on fictional documents. The real assistant runs on your files in a two-week pilot.
A private assistant is not a chatbot on the website. It is the colleague who has read everything and always shows where the answer came from.
"Which agreements auto-renew this quarter?" "Where do we accept unlimited liability?" Terms, deadlines, risks and differences across your contract archive, with the clause on screen.
Leave, travel, procurement, safety. New employees ask the assistant instead of the three people who know. Answers stay consistent with the current version of the policy.
Thousands of scanned pages in two languages. "Torque for the M20 bolts on the kiln drive?" answered from the manual, with the page shown to the technician.
"Sales to Print Co in Q2 by product." The assistant reads the tables you already keep and answers with the numbers and the sheet they came from.
Reply to a tender, summarise a 90-page report, draft a clause in your house style. The model works from your documents, not from the internet.
Dictated inspection notes and meeting recordings transcribed locally and filed into the same searchable base.
The demo corpus for a call is small: two or three scenarios on your own files, an Excel table, a contract set, a scanned archive.
Book a demoCloud assistants promise not to train on your data. Ours cannot see it. The whole stack, from the model weights to the vector index, runs on hardware you own or in a tenant you control.
Four steps, about six weeks, on your documents. You judge the answers, not our slides.
Which knowledge bases, who may see what, where the documents live, which systems to connect. Hardware sizing and ordering.
Your real files: contracts, Excel, scans, voice material. Indexed on the box, on your premises or in your EU tenant.
Your people ask their real questions. We measure answer quality, citation correctness and speed together, and write it down.
Integrations, access groups, training for the team, monitoring handover. Support and model updates on a monthly basis.
This direction is a working prototype, not a product with a hundred installations. Here is what that means.
The stack runs end to end on our own GPU and has been evaluated on a real multi-hundred-page corpus. It has not yet run for months inside a client's network. We show it live and price the pilot accordingly.
One DGX Spark class machine, or an equivalent server, bought by you and owned by you. We specify it, you keep it. Without it the private guarantee does not exist.
Clean PDFs answer well. Faded scans and handwritten notes go through the Document AI pipeline first. We measure on your corpus in the pilot before promising anything.
The assistant answers from your archive. If the answer lives in someone's head, it says so instead of inventing one. That is the point of citations.
Those run in someone else's cloud under a contract that says they will not misuse your data. This runs on your hardware, so the question does not arise. You also choose and pin the model, and there is no per-seat or per-token bill.
Yes, in your own EU tenant on a GPU instance you control. The architecture is identical; the difference is who owns the metal.
Any language model can. This one must cite the passage it used, and it is told to say "not in the documents" when retrieval finds nothing relevant. Wrong answers become visible and are corrected in the pilot evaluation, not discovered in production.
The models and embeddings are multilingual; the corpus we evaluated on was not in English. Your languages are part of the pilot evaluation.
The GPU box is a one-off purchase you own. The pilot is fixed-scope. After that, a monthly fee for support and model updates, no per-token charges.
Thirty minutes. We show the assistant live, discuss which documents would go in first, and tell you honestly whether a private setup pays off for your size.
Book a call with Artem