A private AI workspace for medical labs

A lab result is somebody diagnosis in waiting, and pasting one into a public chatbot puts it on a server you will never see. The numbers look like text on a screen, but each line is a person waiting for an answer about their own body.

Your lab can use a capable AI for the daily grind, the explainers, the summaries, the drafting, without sending a single patient result to a third party. The whole question is where the model runs and who controls the platform around it.

Why a public cloud chatbot clashes with a diagnostics lab

A patient result is about as sensitive as data gets, and it is exactly the kind that is not meant to wander. A public chatbot copies it onto someone else machine the moment a value is pasted in, usually a US cloud you have no agreement with. For a lab, that breaks the one thing the referring clinician and the patient both count on: that the result stays between the people who ordered it.

Banning AI does not solve it. Tell staff not to use it and they still reach for the fastest tool on a busy shift, because nobody handed them a safe one. The traffic does not stop, it just goes somewhere you cannot see.

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 a named patient goes to your machine and stops there. There is no external API in the path, which means nothing about that result leaves the building. Most labs mix the two: a cloud model for general work like policy text or vendor emails, and a local model for anything that names a patient or carries a result.

A full workspace, not a chat box

Your team can build their own assistants in minutes with no code. One can draft plain-language result explainers, turning a panel of values into something a patient can actually read. Another can summarize a case for the ordering clinician, pulling the relevant findings into a tight note. Save these as reusable routines, so nobody rebuilds the same setup twice. Drop in a document and ask about it, pull a current cited answer from the web when you need one, and switch between the leading models in one click. It all 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 report templates and internal knowledge through a connector you control, instead of guessing from the open web. Your systems stay yours, and the AI reaches them on your terms.

You run it and you see everything

You decide who is in and which models they use, set a spending limit per person so the invoice holds no surprises, and watch real usage on a dashboard. Staff sign in once through single sign-on. It installs on Windows Server behind IIS, the same idea as a company-wide AI you host yourself, sits inside your network behind your firewall, and wears your own branding.

We help you put it in place

You do not have to handle the technical side alone. We set kral up with you, connect it to your systems, and advise on rolling AI out across the lab without the data leaving your side. Implementation consulting is part of what we offer.

Give your people a capable AI they can actually use, and keep every patient result on your side of the wall. See it running, then let us help you put it on your own server.

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