What happens in the first call?

30 minutes. You explain your situation, I ask questions. No pitch, no pressure. If we're not a fit, I'll tell you.

What does a project cost?

Projects start from €10,000. For more complex projects, we begin with an analysis phase (from €2,500), which is credited toward the project. This gives you a binding price and me a clear picture. Consulting is billed on a daily basis (€1,800/day).

How long does a project take?

4-8 weeks typically. Complex platforms: 2-3 months. Realistic timeline upfront, delivered.

What if the project doesn't work out?

Fixed price means: the risk is on me. You pay for results, not my time. If something doesn't work, we fix it.

Can you maintain the software afterwards?

Yes. Many clients keep me for ongoing maintenance. Or I hand over everything documented to your team.

What if we're not a fit?

The first call is free. If I'm not the right person, I'll tell you and recommend someone who might be.

Who owns the code in the end?

You. 100%. You receive the full source code and all associated rights. No monthly license fees, no vendor lock-in. You stay legally and technically independent.

What about data security?

I develop using 'Privacy by Design' principles. Hosting is in Germany (Hetzner Cloud), fully GDPR-compliant. During system integration, I prioritize encrypted interfaces and minimal data retention.

Why AI won't solve your Excel problem

"Can't we just use ChatGPT to automate this?"

Every business leader is currently thinking about Artificial Intelligence. And they should. But for many mid-sized companies, starting with AI is like putting a Ferrari engine into a carriage with wooden wheels. It might go fast for a second, but it will eventually fall apart.

Here is why your "AI project" should probably be a "Digitalization project" first.

1. AI needs data, not chaos

Imagine you have 47 Excel files, each with different formats, typos, and "notes" in random cells. If you feed this into an AI, you will get automated chaos.

AI is excellent at recognizing patterns. But if your pattern is "inconsistency," the output will be inconsistent. To benefit from AI, you first need a System of Record—a single source of truth where data is structured, validated, and clean.

First build the database. Then build the intelligence.

2. 80% of your problems are "Dumb"

Most inefficiencies in mid-sized businesses don't require complex neural networks. They require basic logic:

"If an order is over €10k, notify the CEO."
"If a document is missing, don't allow a status change."
"Calculate the commission based on this fixed percentage."

These are deterministic processes. They have a clear "Right" and "Wrong" answer. AI is probabilistic—it gives you a "best guess." For your accounting, production planning, or contract management, you don't want a "best guess." You want a result that is 100% correct, 100% of the time.

3. The "Shadow Work" Trap

Many companies use AI as a "band-aid" for bad processes. They have a staff member spend 4 hours a day copying data from one old system to another, and they want an AI to do the copying.

The better solution? Integrate the systems. A professional API connection is faster, cheaper, and more reliable than any AI trying to "read" a screen or a PDF.

When AI does make sense for SMBs

Once you have a solid, custom software foundation, AI becomes a powerful multiplier. Here are three areas where it actually delivers value:

1. Unstructured Data Extraction

If you receive hundreds of different-looking invoices or PDF contracts, an AI can "read" them and suggest values for your system. But a human (or a rule-based system) still needs to verify and save them into a structured database.

2. Intelligent Search (RAG)

Instead of searching for a file name, you can ask your system: "Show me all projects from 2023 that had a delay in the delivery phase." The AI searches your entire documented history and gives you a summary.

3. Predictive Maintenance / Analytics

If you have years of clean data from your production or sales, AI can help identify trends that a human might miss. "Based on the last 5 years, we will likely have a bottleneck in department X next month."

The Roadmap to AI

If you want to introduce AI in your company, follow these steps:

Standardize: Turn your "Excel habits" into a documented process.
Digitalize: Build a custom system that enforces this process and captures clean data.
Integrate: Make sure your tools talk to each other automatically.
Augment: Now add AI features on top of your clean data to automate the "smart" tasks.

Conclusion

AI is a tool, not a strategy. If your foundation is made of spreadsheets and manual workarounds, AI will only make your mistakes faster.

I help companies build the digital foundation they need to actually be "AI-ready." No hype—just systems that work.

Let's talk about your foundation