Half your contracts come with an NDA, and a public chatbot is the fastest way to break one without realizing it. A drawing pasted into a browser tab, an OEM spec dropped into a prompt for a quick rewrite, a snippet of test data shared to debug a problem. Each of those leaves your building.
The work that makes you valuable to an OEM is exactly the work you cannot afford to leak. There is a way to give your team a capable AI and keep that work on your side of the wall. This is how.
Why a public cloud chatbot and your NDAs do not fit together
When someone on your team uses a public chatbot, the prompt travels to a vendor cloud, often in another country, on infrastructure you do not run. You cannot see where the text lands, how long it is kept, or who can read it. For a general question that is fine. For an unreleased design, a tolerance table, or the terms of an OEM contract, it is a quiet way to hand confidential material to a third party you never vetted.
Banning AI does not solve this. Your engineers already paste things into chatbots on their phones and personal laptops, because it saves them an hour. A ban just pushes that usage out of sight, which is worse. The honest move is to give people something better that you actually control.
Run the model in-house
With kral the platform runs on your own server. You can add a local model on your own hardware, so a prompt about an OEM specification goes to your machine and stops there. No external API sits in that path. The text never crosses your firewall.
Most teams mix the two. A cloud model handles general work, drafting an email, cleaning up a status report, where confidentiality is not the concern. A local model handles the sensitive cases: the new part, the contract under NDA, the test results you have not shared with anyone. Same workspace, your call on what goes where.
A full workspace, not a chat box
Your team can build their own assistants in minutes, with no code. One person sets up an assistant that drafts supplier documentation from a few notes, so the same paperwork stops eating an afternoon. Another builds an assistant that reads a tender and summarizes it into the key requirements, so nobody misses a clause buried on page forty.
Useful setups get saved as reusable routines, so nobody rebuilds the same thing twice. People can drop in a document and ask questions about it, pull a current answer from the web with sources cited, and switch between the leading models in one click when a job needs a different one.
Connect your own systems
kral supports MCP, the open standard for connecting tools and data to an AI. That means an assistant can work with your own templates and your internal knowledge through a connector you control, instead of guessing from whatever is on the open web. Answers come from your part numbers and your documents, not a generic best guess. Your systems stay yours.
You run it and you see everything
You manage who has access and which models each person can use. You set a spending limit per person, so costs never run away from you. A dashboard shows real usage as it happens. People sign in with your single sign-on. It installs on Windows Server behind IIS, sits inside your network behind your firewall, and wears your own branding. If you want the wider picture of a company-wide AI you host yourself, that side is covered too.
We help you put it in place
You do not have to figure this out alone. We set kral up with you, connect it to your systems, and advise on rolling AI out across the company without the data leaving your side. Implementation consulting is part of what we offer, so the thing is working and adopted, not just installed.
Your designs and your OEM contracts are the reason you win business. Keep them where you can see them, and give your team an AI that respects that.
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