Autonomous or “self-driving” laboratories combine robotic platforms with artificial intelligence to increase the rate of scientific discovery. They have the potential to transform our traditional approaches to experimentation. Although autonomous laboratories recently gained increased attention, the requirements imposed by engineering the software packages often prevent their development. Indeed, autonomous laboratories require considerable effort in designing and writing advanced and robust software packages to control, orchestrate and synchronize automated instrumentations, cope with databases, and interact with various artificial intelligence algorithms. To overcome this limitation, we introduce ChemOS, a portable, modular and versatile software package, which supplies the structured layers indispensable for operating autonomous laboratories. Additionally, it enables remote control of laboratories, provides access to distributed computing resources, and comprises state-of-the-art machine learning methods. We believe that ChemOS will reduce the time-to-deployment from automated to autonomous discovery, and will provide the scientific community with an easy-to-use package to facilitate novel discovery, at a faster pace.