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Let's work together
AI transformation for companies

Does your company feel slow?

You bought AI licences and someone in the company even works with them, yet a quote, an order or a meeting takes as long as it always did. The problem usually isn't the tool itself. We help companies find where things get stuck, so that AI actually makes them faster.

Adoption
we help your managers earn their “AI driving licence”
AI transformation
your processes get faster and less manual
Data and systems
all the data and the systems we build are yours
What we do

For AI to speed a company up, people and data have to meet

As long as AI can't see into your systems, it writes nicely, but it won't create an order or compare the numbers from your accounting. And even when it can see into them, people soon put it aside if nobody shows them what to do with it in their own work. One doesn't work without the other, so we do both at once: we work with managers on what they are dealing with right now and give AI secure access to your data.

01
Step 1

Working with people

We bring AI into the everyday work of department managers, so that over time they set up further routines themselves.

02
Step 2

Infrastructure

We connect AI to your company's email, systems and data through MCP, an open standard that is to AI what USB is to a computer. You decide who sees what in the connected data.

03
Step 3

Company brain

The questions you now chase colleagues for are answered by Claude, because it can see into your documents, email and systems.

04
Step 4

Custom system

You get software that follows your processes and hands work from one department to the next.

Working together

Who does what and when

STAGE 01

At the start: the managing director

They tell us where the company is held up the most and, based on that, choose the managers we start with. So that the work does not stay on paper, they give those managers time for it in their calendars.

STAGE 02

First months: selected managers and us

We work hands-on with the selected managers and teach them how to use AI to save time in their daily work and also to run processes and lead their people. We connect missing data as we go.

STAGE 03

Then: the manager alone

They set up further routines without us and hand them on to their team. Meanwhile we make sure they have the architecture support they need to build their own custom system and roll it out to their colleagues.

STAGE 04

Ongoing: the managing director

After each step they decide whether and where to continue.

What we build on
We work with the AI Claude from Anthropic. It understands Czech, and once we connect it to your company data, it works with that data securely.
In practice

Claude watches the processes

A company also loses a lot of time where people keep checking whether work went the way it should. We show it on two typical situations, once without AI Stack, once with it. The people stay in the company and do the work that takes judgement. Claude can do the checking for them.

Example 01
S
Sales
Salespeople and a new price list
Presentations · customer system
What changes
When the company changes its price list, the new prices have to be in every presentation and salespeople have to record them correctly in the customer system.
BEFOREwithout AI Stack
  • 01You have to train the salespeople on the new price list.
  • 02Then someone goes through every presentation to check it has the new prices.
  • 03And finally someone checks the records in the system and chases what is missing.
Training, checks, reminders
AFTERwith AI Stack
C
With Claude· New price list
You tell Claude.

Claude updates the prices in the presentations to match the new price list. And if a salesperson leaves a field empty in the customer system, Claude asks them and completes the record.

One instruction
Example 02
M
Management
Monday meeting
Customer system · spreadsheets · accounting
What changes
At the meeting everyone should talk about the same numbers.
BEFOREwithout AI Stack
  • 01Sales brings numbers from the customer system, production from a spreadsheet and finance from accounting.
  • 02The meeting mostly revolves around which of them are right.
  • 03In the end the decision is put off until someone looks it up.
Three versions of the numbers
AFTERwith AI Stack
C
With Claude· Department overview
Everyone sees the same numbers.

Claude takes the numbers straight from all three sources and shows where each number comes from. The meeting can then focus on what to do with them.

One version of the numbers
About us

Bottom-up it didn't work

Czech companyWe run companies ourselvesCooperation in steps

Over the years we have built eight companies, from purely Czech businesses to global ones. At first we naively thought AI would spread through a company from the bottom up: enthusiasts appear and the rest catch up. Instead, the company split into two camps: some sped up their work with AI, others kept working the old way, and handing work between them got harder and harder. Paradoxically, we sometimes did ourselves more harm than good.

What inspired us is how companies in the USA do it: from the top. Every head of department has their own tools and dashboards in Claude and is responsible for them. The routines they set up apply to their whole team, so AI becomes an ordinary part of work across the whole company, not just for a few enthusiasts. We tried this approach in our own companies. It works and it can be repeated, which is why we offer it to others too.

We are a small team and invest in selected high-potential companies in and around Brno.

The people behind AI Stack
Getting started

We choose
who we work with.

We go into a partnership with something at stake, financially too, so we work with only a few companies at a time. But we'll do a free analysis of where AI could help you specifically.

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Built on Claude by Anthropic.

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