I build intelligence that has to be right.
I run product, engineering, and data at iQpay, where machine decisions move real money at national scale. I build the systems that make those decisions, and the evaluation and judgment that make them trustworthy enough to run on their own.
I came to machine judgment through the study of human judgment.
I read Psychology and History at Harvard: how people reason and how they fail to, how beliefs take hold, how whole societies decide what is true and what is allowed. Building systems that decide turned out to be the same question from the other side. What does it take to trust a judgment, made by a person or by a machine? Evaluation, it turns out, is epistemology with a deadline. The instinct I rely on most in production, distrust a confident answer until it has earned belief, I learned from studying people long before I applied it to models.
I run product, engineering, and data. The whole technical organization, and the intelligence at the center of it.
iQpay is a payments platform operating at national scale across health and social programs, deciding in real time and product by product what each program covers at the register. I set the technical strategy and make the decisions that carry risk: what we build, what we automate, and what a system has to prove before it is allowed to touch a live payment network. And I build the core myself: the classification pipelines behind those decisions, the evaluation systems that keep them honest, and the controls that let them run unsupervised, at a standard of correctness that is measured, not assumed.
A payment network built only to refuse products can, in my systems, be trusted to allow them. I built the precision that unlocked whole categories it had never been able to offer, and a fresh-produce standard adopted by a state health authority, now live in production.
Decisions that move money cannot be watched by hand at scale. I build multi-model juries, calibrated evaluations, and release gates that make automated judgment reliable enough to run unattended, and honest enough to raise its hand the moment it should not. Read the note on trusting machine judgment →
Seven million products, unified from national retail feeds, live sources, and field data I gathered in person, into the single platform every eligibility decision and every invoice draws on.
0.88 to 0.94, and the model never changed.
Our eligibility classifier had stalled at 0.88 F1, and every architecture we tried landed in the same place. Before spending more on models, I audited the ground truth they were trained and judged against, and found that roughly a third of the labels contradicted one another. So I made the unglamorous call: freeze the modeling, rebuild the labels, and re-measure everything against the repaired truth. The same model came back at 0.94 F1, and the pipeline has run unattended in production since, with model disagreements escalated to a person instead of settled by chance.
At sixteen, I founded an academy. I ran it for nine years.
Arkhé, an independent academy in the social sciences, was my first act of company building: founded at sixteen, run for nine years, and funded in part by a €95,000 grant from the European Endowment for Democracy. Before iQpay I also built product at Turkcell, Turkey's largest telecommunications company. I have never stopped reading in the seams between fields, behavioral science, philosophy, the history of ideas, where the questions worth asking tend to live.