Company
Zahavi is built around a simple standard: a compelling mechanism is not enough. It must survive measurement, integration, failure analysis, and deployment constraints.
Operating principles
The company separates conceptual ambition from evidence. Public claims should follow measured performance, not precede it.
The system should make clear which layer can override the policy and under what threshold conditions.
Learning after intervention should remain visible enough for engineers to reconstruct and challenge.
Validation begins with one workcell, one failure mode, and one measurable objective.
Research model
Zahavi's research model draws from control theory, robotics, reinforcement learning, human factors, and biological learning systems, but requires every analogy to terminate in an engineering hypothesis.
Research fellowship
A structured path for researchers to turn a cross-disciplinary mechanism into a falsifiable robotics experiment, measurable failure boundary, and pilot design.
Translation discipline
Projects are evaluated on technical risk, data requirements, integration cost, safety boundary, and what evidence would disprove the underlying thesis.
