▮ COMPANY
Control engineering, applied to AI.
Aurvionics gives enterprise AI the treatment every safety-relevant machine already gets: independent instruments that measure it, independent controllers that correct it, and an independent authority that can stop it. Turbines, reactors, and flight systems earned trust this way. AI will too.
▮ ORIGIN
From governors and control loops to enterprise agents.
Gammatic began as engineering research at Politecnico di Torino. The thesis, “Designing Under Uncertainty: the Gammatic Multi-Agent Framework,” asked whether the discipline of measurement and feedback control could govern probabilistic AI the way it governs physical machines. The answer became a working system: agent work treated as a measurable process, claims verified deterministically, and stopping authority held outside the model.
Deterministic runtime assurance
A control and verification layer that sits between probabilistic models and consequential enterprise decisions. The long-term category is an epistemic operating system for enterprise AI.
Manufacturing
Structured operational data, physical constraints, costly mistakes, and managers who should never need prompt engineering. It is the right proving ground for verified numerical claims.
Evidence before language
The company communicates the way the product works: every public claim is typed, statused, and backed by research, prototype evidence, and stated limits rather than adjectives.
▮ WORK WITH US
We are building the layer that lets enterprises trust what their AI claims, by measuring it.