A confidential AI workspace for game studios

An unreleased game is your next year of revenue, and a public chatbot would happily copy the design doc off site. The moment a designer pastes a level concept or a programmer drops in a build script, that material leaves your studio and lands on a server you will never see, owned by a company in another country, kept for as long as they decide.

You do not have to choose between a capable AI and keeping your work in-house. You can give the studio a model that runs on your own machine, so the sensitive prompts about a game nobody has played yet stay on your side of the wall. That is what kral is built to do.

Why a public cloud chatbot clashes with unreleased game IP

Your edge is the thing players have not seen: the mechanic, the twist, the art direction, the systems design that took two years to tune. A consumer chatbot is the wrong place to put any of it. The prompt travels to an outside cloud, sits in logs you cannot inspect, and may feed future training. For a studio that lives or dies on a launch, that is a real leak.

The instinct is to ban the tools. That fails. Your writers, artists and engineers already use AI every day, because it makes them faster, and a policy memo will not change that. Block it officially and people just paste into a personal account on their phone, which is worse. The honest move is to give them something good that you control, so they never reach for the public option.

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 unreleased title goes to your machine and stops there, with no external API anywhere in the path. The text never leaves the building.

Most studios run a mix. A cloud model handles the everyday work where nothing is secret: rewriting a store description, drafting an email, cleaning up notes. The local model takes the sensitive cases: the design doc, the unannounced feature, the code for the system you are still hiding. Same interface, two destinations, and the team chooses without thinking about plumbing.

A full workspace, not a chat box

This is a place to work, not a single text field. The team can build their own assistants in minutes with no code. One person sets up an assistant that drafts design docs in your studio voice, so a rough idea comes back structured the way your docs always look. Another builds an assistant that summarizes playtest notes into a clean list of actions, so a folder of raw feedback turns into a tracked to-do list before the next standup.

You save reusable routines, so nobody rebuilds the same setup twice and good prompts become shared studio tools. You drop in a document and ask about it directly. You pull a current, cited answer from the web when you need real facts. And you switch between the leading models in one click, picking the right one for the task instead of being stuck with whatever a single vendor ships.

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 about your naming conventions, your pipeline docs, your house style, and the answer comes from your material, not a stranger's blog. Your systems stay yours, and nothing is wired through anyone else.

You run it and you see everything

You decide who is in and which models each person uses. You set a spending limit per person, so costs never surprise you. You watch real usage on a dashboard, by team or by individual. 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 studio branding. There is no outside admin and no shared tenant. If you want the longer technical picture, read about 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 first sensitive prompt runs on your hardware on day one, not after months of internal trial and error.

Your next game is worth protecting. Give your team a capable AI that lives on your server, keep the unreleased work where it belongs, and stop sending tomorrow's launch to someone else's cloud.

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