AI Agents · Sovereign AI · Build & Leadership

AI agents that actually work

We put them into production inside your company — entirely on your own infrastructure if that is what you need — and guide the build-up until your team can carry it.

Where you are today

Plenty of separate tools. No coherent picture.

"We know AI matters. But where do we start — and how does this become more than a handful of subscriptions?" Almost every company is asking this right now.

Knowledge scattered everywhere

Information sits in SharePoint, on file shares, in mailboxes, in the ERP, in the CRM — and in the heads of individual people.

Unmanaged usage

Your people already use public AI tools. Usually without clear rules, and without anyone knowing which data leaves the building in the process.

IT's concerns are valid

Data protection, permissions, traceability, operations. These are the right questions — they just need an answer other than "later".

Pressure to show results

Management wants measurable value. Not a multi-year programme with an open end and an invoice arriving before the outcome does.

How we work together

Step by step. No big bang.

Every step produces a result that stands on its own. After each one you decide again how far to go — and whether to go there with us.

  1. 01

    Workshop

    One day at your site. A live demonstration, an honest look at where you are, a scored map of your use cases and a first plan.

  2. 02

    Assessment & roadmap

    We examine your data landscape and settle the fundamental questions: build or buy, cloud or local, which architecture holds up. The result is a plan covering the next six to twelve months.

  3. 03

    The first agent

    An agent running on your real data that your team uses daily, with a proper data and permissions model. Small enough to arrive quickly, substantial enough to change something.

  4. 04

    Sovereign infrastructure

    Where data cannot leave the building, we build the foundation for it: local models, your own hardware, a hybrid architecture. Often in parallel with the first agent.

  5. 05

    Enabling your team

    We train the people who will look after your agents. The goal is that you no longer need us for everyday work — only for the hard cases.

  6. 06

    Build & AI leadership

    It keeps going: new use cases, the next agent, the roadmap for the year ahead — and the decisions that come with them. For as long as you need it.

Agent packages

Use what works instead of starting over

We have built a sales agent. And a service agent. And a knowledge agent. What differs in your company are the data sources, the vocabulary and the approval rules — not the foundations. That shortens the path to a working result considerably.

See all agents
  • Sales agent

    4–6 weeks

  • Service agent

    4–6 weeks

  • Knowledge agent

    3–5 weeks

  • Proposal agent

    3–5 weeks

  • Management assistant

    3–4 weeks

  • Custom agents

    scope dependent

The difference

Why Rüb Studio

We build, we do not just advise

A project ends with an agent that runs and gets used, not with a slide deck. We come from engineering, not from presenting.

Your data stays where you want it

We can build the entire AI infrastructure inside your company — local models on your own hardware. No dependency on a single vendor, no data leaving by accident.

We make ourselves unnecessary

We build up your internal AI people alongside the systems. A dependency that exists only because the client was kept in the dark is not a business model we want.

You decide after every step

No two-year framework agreement. Every step has a result you can judge before committing to the next one.

Let us start with a single day.

In the workshop you see, using a real example, what is possible in your company — and what is not yet. Afterwards you know where to start. Even if you continue without us.