The GLAS architecture, which is based on a multilayered Git system and is protocol agnostic, can be adapted to a wide range of laboratory types. As it is based on Basic Methods (BM) defined in proprietary software and can accommodate the majority of traditional communication protocols, it can be used to interface with the majority of existing laboratory equipment without the need for any specific development. Subsequently, the sequences of operations (workflows) are defined in accordance with the requirements of the laboratory and can be presented as a list of steps. The overarching principle is to maintain the intelligence as close as possible at the executor level, to the greatest extent possible. This approach facilitates the development and design of high-level schedulers with a relatively straightforward methodology. As previously outlined, GLAS is currently employed within the Swiss Cat+ framework to directly control laboratory instruments utilizing over six distinct protocols and application programming interfaces (APIs). Furthermore, the REST-API Level 1 Main Laboratory Scheduler oversees a level 2 Agilent Sample Scheduler environment and a level 2 Agilent VWorks environment. Furthermore, a level-2 Bruker Topspin-IconNMR environment is operational, as is another dedicated level-2 Sub-Scheduler for an ensemble of equipment comprising two Chemspeed Swing XL stations controlled by Autosuite and Arksuite, along with a group of five interconnected DEC/Jacomex glove boxes with robotic sample preparation functions. The aforementioned variety of interfaces and instruments provides compelling evidence in favor of a high degree of adaptability to a diverse range of laboratory settings. Another notable strength of the GLAS architecture is its adaptive web client (Figure ). Indeed, the web interface is fully customizable to any laboratory with minimal configuration. By modifying the configuration slightly to suit the laboratory environment, the user can readily display the status of ongoing tasks and the progress made in near real-time.