Bridging academic rigor with industrial-grade engineering in quantum and ultra-high-vacuum systems.
This platform is designed for researchers, engineers, and institutions working at the intersection of quantum science, cold-atom physics, and ultra-high-vacuum engineering.
It serves both academic laboratories seeking open, reproducible experimental systems, and industrial and applied research teams requiring robust, maintainable, and scalable hardware platforms.
Universities and research institutes benefit from transparent system architectures, deep physical insight, and designs that can be fully understood, modified, and extended by students and researchers.
Industrial users require systems that behave predictably over long operational cycles, tolerate environmental drift, and integrate cleanly with control software, automation, and production constraints.
Golan Ben-Ari is an independent deep-tech engineer, system architect, and researcher with more than 25 years of experience spanning software, embedded systems, experimental hardware, and applied AI.
His background includes senior R&D leadership roles in industry, startup founding and acquisition, and hands-on development of real-time control systems, optimization pipelines, and autonomous platforms.
Today, alongside doctoral research in a Cold Atom Laboratory (Department of Electrical Engineering), his work focuses on designing open, modular, and AI-ready quantum experimental systems — from vacuum chambers and magnetic field engineering to autonomous experiment control.
Every system is designed to be understood, measured, and modified. There are no hidden control loops, undocumented assumptions, or vendor-locked subsystems.
Mechanical, thermal, magnetic, and vacuum design decisions are derived directly from physical constraints and experimental goals, not from generic templates.
Modern experiments must run autonomously for days or weeks. Control, monitoring, logging, and AI-assisted optimization are considered core system components — not add-ons.
Beyond hardware delivery, the platform includes structured educational content covering vacuum engineering, cold-atom system design, and experimental automation.
This dual approach ensures that users do not merely operate a system, but fully understand its limitations, tradeoffs, and optimization paths — enabling long-term independence and innovation.