Why I Started This

A personal essay on data, AI, and the Hungarian SMB left behind

Every week, someone at the clinic was running after an invoice.

Not metaphorically. Literally opening folders, cross-checking Excel sheets, calling the bookkeeper, reconciling what was paid last month against what was supposed to have been paid. Hours spent not because the work was complex, but because no one had ever built a system that made it simple.

Expenses were logged manually. Invoices too. Duplicates crept in. Payments slipped through. When someone from finance needed a cash flow report — for a loan application, for an audit, for a board meeting — the answer was always the same: give us a few days. And a few days later, the result was a document that everyone hoped was accurate but no one could fully trust.

I watched this pattern play out not once, not twice, but continuously. And what struck me wasn't the chaos itself. It was the resignation around it. The sense that this was just how things work. That this was normal.

It is not normal. It is expensive. And it is fixable.

A Decade of Enterprise Data

Before the clinic, I spent ten years at STARSchema, working on data infrastructure for large organizations. Enterprise clients. Big budgets. Teams dedicated to data engineering, reporting, analytics.

Those companies had problems too — but they had the resources to solve them. They could afford the tools, the consultants, the platforms. When they decided data mattered, they could act on that decision.

What I noticed, over and over, was that the smaller companies never got that option. Not because the need wasn't there — it absolutely was — but because the economics didn't work. Good data infrastructure was priced for enterprises. SMBs were simply priced out.

So they improvised. They used Excel. They used WhatsApp threads. They used the memory of the one person in the office who knew where everything was — and when that person left, they started over from scratch.

The Hungarian SMB Blindspot

There is something particular about the Hungarian business culture that makes this harder to solve than it should be.

It is not incompetence. The people running these businesses are often sharp, hardworking, and deeply committed to what they do. But there is a tendency — and I say this with respect, because I have lived and worked inside it — to avoid the uncomfortable reality. To not look too closely at what is not working. To patch rather than rebuild.

Data problems are invisible until they are catastrophic. A missed payment does not feel like a data problem in the moment. A week spent producing a report does not register as a structural failure. A loan application that almost fell through because the numbers weren't ready — that becomes a story about stress, not a story about systems.

Hungary has ambitions to modernize, to grow, to compete at a European level. But you cannot build a competitive business on a foundation of guesswork. You cannot forecast your growth if you don't know where your money went last month. You cannot make good decisions from bad data — or from no data at all.

The gap between Hungarian SMBs and their Western European counterparts is not a gap in talent or drive. It is, in large part, a data gap. And it is widening.

A Door That Was Previously Closed Has Now Opened

For most of the last decade, solving this properly required enterprise budgets. The tools were expensive. The expertise was scarce. The implementation was slow. A small business trying to get its data in order was looking at a project that cost more than it could justify.

AI has broken that equation.

What used to require a team of data engineers and a six-figure platform budget can now be done leaner, faster, and within reach of a business with twenty employees. Not perfectly, not overnight — but meaningfully. The systematic approach that worked at the enterprise level can now be adapted, scaled down, and applied where it was never accessible before.

This opportunity is here now. Those who take it will build advantages that compound year on year. Those who wait fall behind — not because the world moved fast, but because they stood still.

Why I'm Here

I'm not building a consulting career. I've simply watched too many good businesses — with good people and good products — hit unnecessary obstacles because their data was disorganized. That's frustrating. And today there's no excuse for it.

I want Hungarian SMBs to be successful not just domestically, but at a European level. To be able to sit across the table from a foreign investor, partner, or client and present their numbers with confidence. To make decisions backed by real information, not estimates and hope.

Organized data enables. Bad foundations limit. That is not a slogan. That is something I have watched play out, up close, for over a decade.

If any of this sounds familiar — if you recognize your business in the Excel sheets, the missed payments, the reports that take days — let's talk.