Refineries, PSUs, defence-linked manufacturing units and government offices generate a lot of routine but sensitive knowledge work. Approval notes, board presentations, engineering calculations, code for internal tools, review of scanned drawings and inspection reports. None of this can go through cloud AI assistants like Claude or Codex because the underlying data is confidential: Piping & Instrument Diagrams, financials, vendor negotiations, unreleased designs, internal correspondence, confide
The idea is a self-hosted, air gapped AI workbench running entirely on the organization's own GPU server.
Refineries, PSUs, defence-linked manufacturing units and government offices generate a lot of routine but sensitive knowledge work Approval notes, board presentations, engineering calculations, code for internal tools, review of scanned drawings and inspection reports None of this can go through cloud AI assistants like Claude or Codex because the underlying data is confidential: Piping & Instrument Diagrams, financials, vendor negotiations, unreleased designs,...
The idea is a self-hosted, air gapped AI workbench running entirely on the organization's own GPU server. Nothing leaves the premises. The backend should not be locked to one model. It needs to support multiple open weight models at once and automatically pick the right one for a given task based on what that task needs, a coding request handled differently from a document summary request. New open weight models should be addable later without redesigning the system, since this space is moving fast. The assistant also needs to actually act like an agent. Plan out multi step work, call local tools such as file read and write, code execution in a sandbox, spreadsheet work, internal document search, and iterate on a task instead of answering once and stopping. It needs to handle more than tex