A confidential AI workspace for product design studios

An unreleased product lives or dies on staying secret until launch, and a public chatbot quietly undermines that. The design files, the naming directions, the screens nobody outside the studio has seen: all of it can end up in a vendor cloud you do not own, sitting on someone else's servers, the moment a designer pastes it into a chat to get help.

You do not have to choose between giving your team a capable AI and keeping unreleased work on your side. You can have both. The trick is where the model runs, and that is a decision you get to make instead of handing it to a US cloud by default.

Why a public cloud chatbot is a bad fit for a design studio

Product design studios trade on confidentiality. A client hands you a concept that does not exist yet, you push it through dozens of iterations, and the value sits entirely in nobody else having seen it. A public chatbot inverts that. Every prompt about a logo direction, every block of front-end code, every research note travels to a vendor cloud you do not control, gets processed there, and may be retained under terms you did not write.

Banning the tools does not solve it. Your designers already use AI to draft copy, name things, debug a component, and turn rough notes into something readable. Tell them to stop and they reach for a personal account on a phone instead, which is worse, because now the sensitive work is leaving on a channel you cannot see at all. The realistic move is to give them an AI that is genuinely useful and keep it on ground you control.

Run the model in-house

With kral the whole platform runs on your own server. You can also add a local model on your own hardware, so a prompt about an unreleased product goes to your machine and stops there. No external API sits in that path. The text never leaves the building.

Most studios run a mix. A cloud model handles the general, non-sensitive work where the best frontier quality matters and the content is harmless. A local model handles the cases that must not leave: the unannounced client project, the code for a product still under wraps, the internal strategy doc. Your team picks per conversation, and the sensitive ones stay home.

A full workspace, not a chat box

This is more than a single text field. Your team can build their own assistants in minutes with no code. One assistant drafts design rationale write-ups, so a designer turns scattered decisions into a clean explanation for the client. Another summarizes user research you provide, reading the raw session notes and handing back the patterns. Once an assistant exists, you save it as a reusable routine, and nobody on the team rebuilds the same setup from scratch.

From the same place, a designer can drop in a document and ask questions about it, pull a current answer from the web with citations when they need fresh information, and switch between the leading models in one click depending on the task. It is the working environment, not a toy.

Connect your own systems

kral supports MCP, the open standard for connecting tools and data to an AI. That means the assistant can work with your own templates and internal knowledge through a connector you control, instead of guessing from the open web. Ask it to follow your studio's writing voice or reference a past project, and it draws on your material rather than something generic. Your systems stay yours, and you decide what the connector can reach.

You run it and you see everything

You stay in charge of the whole thing. Manage who is in and which models each person can use. Set a spending limit per person so costs never run away. Watch real usage on a dashboard. Sign in with single sign-on. It installs on Windows Server behind IIS, sits inside your network behind your firewall, and wears your own branding so it feels like a studio tool rather than someone else's product. If you want the broader picture of running this kind of thing yourself, here is company-wide AI you host yourself.

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 studio without the data leaving your side. Implementation consulting is part of what we offer, so the move from a public chatbot to something you control is a guided one, not a weekend project you take on by yourself.

Your unreleased work is the studio's whole edge. Keep it on your own server, give your team an AI that actually helps, and stop sending the next launch to a cloud you cannot see into.

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