3D simulation and virtual commissioning software for industrial automation
machineering builds iPhysics, a 3D simulation platform that lets manufacturers test machines and production lines virtually before physical installation. The tech stack—TypeScript, React, C++, Qt, Kubernetes, Node.js—reflects a modern web-first architecture layered over domain-specific simulation engines, suggesting an intentional shift toward cloud-delivered SaaS. Current hiring is engineering-heavy (4 open roles) with one sales position, indicating product-driven growth as the core constraint.
machineering is a Munich-based industrial simulation software company founded in 2009 as a spinout from TU Munich's Institute for Machine Tools and Industrial Management. The company sells iPhysics—a 3D simulation platform for virtual commissioning—to machinery manufacturers, system integrators, and production facilities across Europe and globally. Over 1,400 licenses are deployed; customers include large automation and packaging equipment makers. The product is used across engineering, production, sales, and after-sales workflows to detect design flaws, optimize automation logic, and reduce physical commissioning risk before machines are built.
Frontend: TypeScript, React, Svelte, Solid. Backend: Node.js, Express.js. Graphics: C++, Qt, OpenGL. Infrastructure: Docker, Podman, Kubernetes. The stack signals a web-first SaaS push alongside native simulation engines.
Core projects include: iPhysics SaaS platform development, simulation model creation, controller integration, Kubernetes cluster maintenance, and Node.js cloud services. Work centers on scaling the platform's virtual commissioning capabilities.
machineering GmbH & Co. KG's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.