Built in Toronto,
for the long middle
Kayraxis Inc. is a research and engineering company founded in Toronto in 2026. We work in the long middle between "humans do the work" and "AI does everything": the decades in which almost all work will be done by Human–AI systems that somebody has to design.
The company runs as two divisions. Kayraxis Research researches the methods for redesigning industrial work, the computational tools, and the Human–AI systems they combine into — with the measurement protocols that put Jahoda's latent functions on the same scorecard as output per cost, and the field trials that test it all. Kayraxis Platform builds what that research proves out: agents built for one link of a chain at a time, verification designed as a first-class human function, and the instrumentation that shows the de-skilling loop before it closes.
The first company built on Kayraxis is Mergen AI, a compliance AI platform for the food and beverage industry, where regulatory work is executed by agents while judgment and accountability stay with the compliance professional.
Tural Gulmammadov
Founder · Kayraxis — Founder & CEO · Mergen AI
Tural has been building AI/ML systems professionally since 2015. Before founding Mergen AI and Kayraxis, he was Head of Core Generative AI Development at Oracle, leading cross-functional teams of data scientists and AI/ML engineers responsible for production-grade generative AI platforms deployed across multiple industries.
He designed and taught an AI/ML Operations course in the joint program between the Vector Institute and the University of Toronto, holds a USPTO patent on graph-based discrete optimization, authored A Practical Guide to Oracle AI Engineering (2026), and was a technical reviewer of Graph Machine Learning. His technical interests sit where this manifesto's method does: graph theory, discrete mathematics and probabilistic reasoning applied to machine learning systems under real-world constraints. Before any of that, there were chess boards and programming olympiads in Baku.
Working notes
The manifesto's operational chapters grew out of a series of essays on how Human–AI systems should be wired. They are the place to read the argument in its engineering form.