An unpublished manuscript is an author trust in your hands, and a public chatbot would copy it to a cloud neither of you chose. The moment an editor pastes a draft chapter into a free tool to tighten a paragraph, that text leaves your house and lands on a server you do not control, under terms nobody at the press ever signed.
Your house can still use AI for jacket copy, synopses, editing and research without handing manuscripts to an outside cloud. It comes down to where the model runs and who runs everything around it. Here is how to keep both on your side.
Why a public cloud chatbot clashes with unpublished manuscripts
A public AI chatbot sends every word to a vendor cloud. For most companies that is a vague worry. For a publishing house it cuts against the one promise you make to every author: their work stays yours and theirs until you release it. You cannot guarantee a manuscript is unseen and then route it through a service you have no contract with and no sight into. Designs, code for your tools, and unreleased titles all carry the same risk once they leave the building.
Banning AI outright does not hold either. Your editors and marketers already use it on their phones and laptops. The real question is not whether they use it, but on whose machine.
Run the model in-house
With kral, the whole platform runs on your own server. You can add a local model on your own hardware, so a prompt about an unpublished manuscript goes to your machine and stops there. No external API in the path, nothing leaving the office. Most houses mix it: a strong cloud model for general work, a local model for anything tied to a manuscript that is not out yet.
A full workspace, not a chat box
It is more than a place to type questions. Your team can build their own assistants in minutes with no code. One assistant drafts catalog and jacket copy in your house voice. Another summarizes a full manuscript so an editor can size it up before the read. Save those setups as reusable routines, so nobody rebuilds the same thing twice. Drop a document in and ask questions about it. Pull a current, cited answer from the web when a title needs market context. Switch between the leading models in one click when one handles a task better. Every useful capability sits in one place, behind your login.
Connect your own systems
kral supports MCP, the open standard for connecting tools and data to an AI. The assistant can work with your own templates and internal knowledge through a connector you switch on and control, instead of guessing from the open web. Your systems stay yours.
You run it and you see everything
Manage who is in and which models each person may use. Set a spending limit per person so costs stay predictable, and watch real usage on a dashboard instead of guessing. Everyone signs in once through single sign-on. It installs on Windows Server behind IIS, the same approach as a company-wide AI you host yourself, and sits inside your network, behind your firewall, in your own branding.
We help you put it in place
You do not have to work this out alone. We set kral up with you, connect it to your systems, and advise on rolling AI out across the house without the data leaving your side. Implementation consulting is part of what we offer.
Give your editors and marketers a capable AI workspace and keep every unpublished manuscript on your side. See it running, then let us help you put it on your own server.
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