The asynchronous operation at the Orchestrator and Action Server levels was particularly motivated by hierarchical active learning schemes, for example human-in-the-loop or fully autonomous hierarchical active learning. When workflow-level decisions are made by a human with autonomous workflow execution, a community of asynchronous Orchestrators enables humans to execute on any available workflow. We envision that this mode of operation will be critical for integrating physicallyseparated laboratories and realizing cloud laboratories. HELAO-async is being actively developed in 2 public repositories: Experimentation/helao-core encompasses the API data structures and Experimentation/helao-async contains instrument drivers, API server configurations, and experiment sequences. These repositories contain drivers for our suite of experimental resources spanning motion control, liquid handling, electrochemistry, analytical chemistry, and optical spectroscopy. Our Orchestrator-level implementations include scanning droplet electrochemistry, scanning optical spectroscopy, electrochemical cells with scheduled electrolyte aliquots for monitoring corrosion, and several methods of coupling electrochemical transformations with analytical detection of the chemical products. These latter 2 examples share the need for liquid and/or gas aliquoting from operational electrochemical cells, for which we typically use a Tri Plus robotic sample handling system (CTC Analytics), which is a shared resource across multiple workflows.