In this work, we leverage the capabilities of AiiDA to create a powerful DFT workflow for estimating the lasing performance of organic laser molecules. Taking a SMILES string as input, the AiiDA-enabled workchain efficiently executes the necessary calculations, monitors their status, and retrieves critical data related to the lasing performance. This data is subsequently used in a Bayesian optimization campaign, enabling researchers to make informed decisions and advance their chemical exploration efforts. The workflow is depicted in Figure and additional information can be found in the Methods section.