About
AlphaIQ was founded on a narrow observation: the hard part of agent-based modelling is not conceiving the model. It is the months of translation, calibration and validation between a good idea and an answer somebody will act on.
What we believe
A model that reproduces history without explaining it will keep reproducing history right up until the moment that matters. We would rather have a structural explanation with wider error bars.
Rigour loses to deadlines because rigour is expensive. Automating the lifecycle is worth doing mainly because it makes calibration records and sensitivity analysis affordable by default.
Every artifact we produce is meant to be read and argued with. A result nobody can interrogate is not a result — it is an assertion with a chart attached.
Every model has a boundary beyond which it is wrong. Naming that boundary is not a weakness in the work; it is most of the value of the work.
Who we are
AlphaIQ is led by Ilan Gleiser, who works at the intersection of enterprise AI and agent-based modelling for financial services. Replace the biography below with your full team as you hire.
Founder
Works on enterprise AI solutions and agent-based modelling for financial services. Background spans quantitative finance and large-scale AI deployment, with a long-standing focus on complex-systems approaches to markets and institutions.
BiographyBring a question you cannot currently answer and we will tell you honestly whether simulation is the right instrument for it.
