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Still running. Two years from now too.

I take over, refactor, and automate grown Excel, VBA, Access, reporting, Power Query, Python, and AI workflows. Until a second developer understands them in three to five days.

What started as an Excel file now carries half a business process. What was meant to be a Python script from the ex-intern is now production. I clean up, document, make it handover-ready.

  • 18 years of IT practice, from Excel/VBA to Power BI and local AI
  • Directly with the engineer, no sales in between
  • Remote across Germany, on-site in the Rhine-Neckar region
  • Refactor over rebuild, wherever that's possible
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Read the AI stance

Abstract long-exposure photograph of sweeping gold and red light trails against a dark blue-toned background, symbolizing continuous operation over time
Photo: Egor Litvinov / Unsplash

/ Stack

  • Excel · VBA
  • Access · SQL
  • Power Query
  • Python
  • Reporting · BI
  • ETL · DWH
  • Local AI · LLMs
  • n8n · MCP
  • Vector DBs
  • RAG
  • GDPR · EU AI Act

/ Stance

I do not build slick prototypes for LinkedIn. I build systems that still run in two years, that the team can keep alive without me, and that do not crumble at the next update.

Excel, VBA, Access, SQL, Power Query, Python, local AI, classic reporting pipelines. The tools are not the interesting part. The interesting part is taking a grown-over process and making it predictable again.

Overhead view of a tidy desk with a mechanical keyboard, wooden wrist rest, plant, coffee and laptop
Photo: Jakub Żerdzicki / Unsplash

/ Why work with me

0

sales layers in between

You write to me, you talk to me. No account manager, no handoff to a project team you never meet.

01 // Focus

What teams usually walk in with

Four constellations I get called in for most often. Each with a concrete before-and-after, no stock imagery.

  1. 01Reporting · BI · ETL
    5hsaved per month

    Reports rebuilt by hand every single month

    Same exports, same pivot, same five hours. We structure import, logic, and output once, usually Power Query plus a small VBA layer.

  2. 02Excel · VBA · Refactoring
    2hfor a colleague to onboard

    Excel files nobody dares to open

    Nested formulas, broken references, macros from 2014. Refactor into clear zones, typed ranges, documented steps. Nobody has to guess what happens.

  3. 03Access · SQL Server · Migration
    0data loss during migration

    Access databases from the back office

    Grown-over Access apps where business logic, data, and UI are one big soup. Carefully untangle, document, and optionally migrate to SQL Server.

  4. 04AI · n8n · MCP · local LLMs
    100%on-prem, no cloud egress

    Internal AI workflows that must stay GDPR-clean

    n8n pipelines, local models, embedding stores, MCP servers, document analysis. Pragmatic architecture instead of cloud lock-in for data that cannot leave.

02 // Architecture · sample

What a typical reporting pipeline looks like with me.

A schematic, not a mockup. What comes out of the discovery workshop tends to look about like this. The clarity is the point: who does what when, where the data comes from, where the responsibility sits.

SOURCESSAP exportCSV dailyCRMAPI · hourlyITSMSQL · read-onlyOperationsXLSX manualPower QueryImport · Cleanup · JoinreproducibleData modelStar · MeasuresDAX · typedReportXLSX · PDFBEFORE~5 h per month, manualAFTER1 click, documented, handover-ready

03 // Disciplines

13 disciplines, one engineer.

A compact index so the scope is clear at a glance. Each discipline has its own service page with problem, approach, and typical deliverables.

All services in detail

  1. 01VBA · Excel + Access
  2. 02Excel templates & structure
  3. 03Reporting automation
  4. 04Internal business tools
  5. 05Knowledge bases
  6. 06Access VBA & databases
  7. 07Power BI & Data Analytics
  8. 08ITSM & IT Infrastructure
  9. 09Process automation
  10. 10Power Query & data prep
  11. 11Python & SQL
  12. 12AI · Integration
  13. 13Training

04 // Engagement

What working together looks like in practice

Seven formats I offer most often. Each has a clear scope, a clear start, and a clear point where you decide on your own terms whether more makes sense.

All amounts are final, no VAT is charged under the German small business rule (§ 19 UStG). Small fixes under one hour are not billed. Larger pieces can move to a fixed-price package once the scope is clear.

Close-up of a handshake between two business partners in an office
Photo: Cytonn Photography / Unsplash
  1. 01

    Intro call

    30 min · Zoom

    Short get-to-know call. You outline the topic, I give an honest first read on whether the project makes sense at all, including an honest no if that is the answer.

    free
  2. 02

    Deep-Dive workshop

    90 min · remote

    Longer session with written assessment: data flow, risks, three realistic options with sequence. You can think it through internally, with or without me.

    €390
  3. 03

    System audit

    1 - 3 days

    Review of an existing Excel, Access, or reporting estate. Risks named, concrete sequence for change proposed.

    €1,000 - €3,000
  4. 04

    AI readiness

    1 - 2 days

    Where AI realistically helps in your stack, where it does not, what GDPR and the EU AI Act mean for it, which architecture holds.

    €1,000 - €2,000
  5. 05

    Implementation

    hourly

    The actual work: code, data model, pipelines, refactoring, migration. Iterative, documented, handover-ready.

    €100 / h
  6. 06

    Retainer

    monthly

    Agreed monthly hours for maintenance, adjustments, urgent questions. Response within two business days.

    from €700 / month
  7. 07

    Training

    1 - 2 days

    In-house, remote, or hybrid. Excel, VBA, SQL, Power Query, or an AI block tailored to your team.

    €1,200 - €1,600 / day
05 // Voices

What clients actually said.

Feedback from finished projects, straight from the people I worked with.

Finally someone understood why our monthly reporting was broken in the first place, before trying to fix it. Everyone else only ever knew the symptoms.
Head of Controlling, mid-sized manufacturer
No AI coach theatre. An honest assessment of whether our use cases were ready for local inference, and a sensible sequence plan.
Head of IT, public sector
For the first time we did not have to click our weekly reporting back together by hand. Five hours of clicking became one button. Sounds banal. It was a small liberation for the team.
Operations lead, logistics provider
Understood our data flow first, then our tables, then the actual process. Only after that did code enter the picture. Exactly the sequence we were not used to.
Managing director, B2B services
Our Access app from 2009 was still running, but nobody dared touch it. Three weeks later the code was documented, the backend mirrored to SQL Server, and the app ran faster than before. Without a single user noticing.
Head of Finance, industrial services
An Excel file that had been growing for eight years and nobody really understood. Refactored in two weeks, clear zones, documented logic. What surprised us: he also told us which parts to leave manual on purpose, because automation would not pay off there.
Senior consultant, audit firm
We wanted to throw ChatGPT at our contract base. What we got was a local RAG setup with citations, GDPR-compliant, on-prem. Exactly what our data protection officer had been saying we would need all along.
Department head, legal at a mid-market company

/ FAQ

Honest answers to the questions clients actually ask.

Not an SEO FAQ. This is what people genuinely want to know before the first conversation. Answers are as short as possible, and as long as necessary.

/ Engagement

01What does a typical project look like?
Discovery workshop (90 min), then a short written profile with risks and sequence, then iterative work in one-to-two-week increments with quick status reviews. Handover includes documentation. Optional retainer for maintenance.
02How much does a typical project cost?
A classic reporting automation project typically runs 6 to 12 weeks from the discovery workshop to a validated production run, depending on data shape and depth. A system audit alone €1,000 to €3,000. AI readiness workshops 1-2 days. We arrive at a real range after the discovery workshop.
03Solo or with partners?
Solo, intentionally. For larger pieces I bring in trusted specialists (Power BI, SQL Server admin, data-protection lawyer) on a case-by-case basis, always transparently.
04How does the discovery workshop work?
90 minutes remote. You describe process, data, and goal; I ask specifically about the realities (what grew over time, what is internal politics, what cannot leave the building). You get a written assessment afterwards with a proposed next step, or an honest no.
05Long-term support?
Yes, via retainer. Agreed monthly hours, response within two business days. Useful when business-critical things have been built and there is no internal deep-knowledge owner.

/ Existing systems

01Do you work with what we have, or does everything need to be rebuilt?
Almost always with what is there. Excel files, Access apps, grown macros, old SQL views. Refactor beats rebuild in 80% of cases because the process knowledge lives in the existing artifacts. Rebuilds only when the old structure provably no longer carries.
02Can existing Excel files keep being used?
Usually yes. We separate input, logic, and output cleanly, push recurring calculations into Power Query or VBA, and document the zones so a second person understands the file in two hours.
03What if our processes are simply chaotic?
We start by observing, not automating. Automating a broken process gives you a fast broken process. First understanding, then structure, then code.
04When does VBA still make sense?
When the work lives inside the Office world and the output stays inside Excel, VBA is often the soberest answer. If the output leaves Excel or multiple sources arrive, I prefer Power Query, Python, or n8n.
05When is automation NOT worth it?
When a process eats less than 1-2 hours per month and is unstable on top. The cost of maintaining the automation will outweigh the manual effort. I will say so.
06How do you document?
Readable code with commented assumptions. README with setup, assumptions, known limits, maintenance notes. For sensitive topics, an additional short handover video. Goal: a second developer is self-sufficient within three to five days.

06 // A short note is enough

If something in your stack eats the same hour every month, it is worth a conversation.

Send a short email about what still runs manually. You get an honest read back, no sales funnel.

Get in touchcontact@mikeit.dev