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Most founders never see a hundred-million exit. Barbaros Ozbugutu closed one on December 17, 2019. What it taught him is that iyzico left a multibillion outcome on the table by operating in one country. Klarna’s first employee in Germany in 2010, he turned down a Deutsche Telekom contract to move his family to Istanbul in 2013 and built iyzico through the downturn years that followed. The co-founder of iyzico and now of Donnerstag.ai joins GTM Vault for the first ever Coffee Walk, from Galata down to Karakoy, to explain why the second company was global from day one, why it runs on rules rather than on an LLM, and what a co-founder’s diagnosis seventeen days after the exit did to how he spends his time.
About Donnerstag.ai
Donnerstag.ai is a system of action for enterprise finance: it connects ERP, service and banking data to reconcile transactions line by line, surface discrepancies, and run the workflow that follows, starting with accounts receivable for suppliers. It was founded in 2025 in Frankfurt by Barbaros Ozbugutu, co-founder of iyzico, and Volkan Ozkan, co-founder of Yolda. The team of thirteen works across Germany, Turkey, Spain, the UK and Dubai with no department heads. In November 2025 it raised a €4.3 million seed round led by Speedinvest, with QED Investors, Crestone VC and European angels.
Episode highlights
(0:00) One Country, And What It Cost
(2:21) Klarna’s First Employee In Germany
(12:24) The Deutsche Telekom Offer, And Moving The Family To Istanbul
(15:25) Hire People Better Than You, And Why There Is No Playbook
(20:46) Tahsin’s Diagnosis, Weeks After The Exit
(25:00) Why Donnerstag.ai, And Falling In Love With The Problem
(29:05) The Action Gap: The ERP Records, Excel Acts
(31:30) Three To Five Percent Leakage, 95 Percent Manual
(36:06) Never Send Financial Data Into An LLM To Match
(45:24) Global From Day One, And The Country Discount
What you’ll learn:
Why a market-leading company in one country gets a country discount on valuation and fundraising, and why the second company was global from day one
The action gap: why SAP, Oracle and Dynamics are systems of record, and why every real finance action still happens in Excel
What a system of action is, and how it sits on top of the ERP instead of replacing it
Three to five percent revenue leakage, 95 percent manual work, and a 10 to 15 day close: the three numbers driving enterprise finance automation
Why you never send financial data into an LLM to match transactions, and what the LLM is for instead
How a one-hour meeting with the people doing the work replaces ten consultants and a slide deck
Why nobody in a large enterprise buys a horizontal AI orchestration project, and why the vertical problem wins
Why there is no playbook in 2026, and what that changes about who you hire
Why you hire people better than you, say expectations out loud, and fire fast when the gap does not close
What a co-founder’s diagnosis seventeen days after the exit, and losing him eighteen months later, changed about how he gives, plans, and spends a day
Key takeaways
1. The country discount is real, and it is the one thing he refused to repeat.
iyzico led its market in Turkey, and Barbaros reads two or three more countries as the difference between a hundred-million exit and a multibillion one. One market meant a discount on valuation, a ceiling on fundraising, and a limit nobody set on purpose. Donnerstag.ai started global on day one, with people in Spain, Turkey, Germany, Dubai and the UK, because a finance team’s reconciliation problem is the same in every country.
2. The ERP is a system of record. Every real action still happens in Excel.
SAP, Oracle and Dynamics record everything, and the moment a finance team wants to act on it (cash flow, open positions, line-by-line reconciliation), the data leaves the ERP and lands in a spreadsheet run by a person. That round trip is the action gap. Donnerstag.ai is the system of action on top: it pulls the data, matches it, surfaces discrepancies, runs the workflow in autopilot or with an approval step, and writes the result back with an audit trail.
3. Three numbers make the case: three to five percent leakage, 95 percent manual, and a 10 to 15 day close.
Enterprise finance operations leak three to five percent of revenue because nobody can run them line by line. Ninety-five percent of the work is done by hand, and nobody wants that job anymore, which turns a cost problem into a talent problem. Month-end close takes 10 to 15 days, and until the books close the CEO does not know whether the quarter hit or whether there is cash to pay the invoices.
4. Never send financial data into an LLM and ask it to match. Use the LLM to write the rules.
A model is not deterministic, so three runs give three answers, and an auditor asking why a step was taken will not accept “the AI did that.” What the LLM does well is read the contracts and extract the rule set, so the matching runs deterministically and every decision is explainable. The moat is not the model. It is understanding the customer’s process, done in a one-hour meeting with the people doing the work rather than ten consultants and a slide deck.
5. There is no playbook, so hire people with opinions, hire people better than you, and fire fast.
Everything is at zero in 2026: nobody knows the right shape of a technology company or its go-to-market, so people who execute a playbook are the wrong hire and people who run experiments are the right one. Donnerstag.ai runs thirteen people with no department heads. Hire people better than you so you can take a day off, say the expectations out loud, and when the gap does not close, fire fast, because at ten people one person is the company.
Barbaros Ozbugutu
LinkedIn: https://www.linkedin.com/in/barbaros-ozbugutu-34763619/
Donnerstag.ai: https://www.donnerstag.ai
Rick Koleta (Host)
LinkedIn: https://www.linkedin.com/in/rickkoleta/
Newsletter: https://gtmvault.co/
GTM Vault
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