To effectively sample the chemical space related to Ullmann couplings, we employed a multi-stage data science process that was initiated by querying the ZINC20 database for structures containing aryl C-N bonds, as this database contains a large collection of accessible compounds . Curation was performed by filtering these examples according to their LogP (<4.0), molecular weight (<400 amu), and compatibility with the reaction conditions (see SI for full details). This process yielded a dataset of ~2000 compounds, from which cheminformatics tools were used to fragment the compounds into a library of aryl-bromides and primary amines. Finally, we selected examples from these libraries according to their commercial availability and available spectral data. This resulted in ~400 unique arylbromides and ~500 distinct primary amines, whose structures were submitted to quantum-chemical calculations to collect features that capture electronic and steric properties of each substrate. To select representative examples in an unbiased fashion, the computed structural features were condensed by dimensionality reduction (Uniform Manifold Approximation and Projections, UMAP) to build a chemical space followed by unsupervised learning to cluster similar substrates (21) (Ward clustering, see details in the SI). From each cluster, we selected molecules based on price and ease of access resulting in a diverse and representative scope of 24 aryl-bromides and 12 primary amines for the study. In contrast, ligands were selected by prioritizing their commercial availability as well as their reported use in Ullmann reactions . This yielded a diverse collection of 24 ligands to be tested in the initial training set. We conducted the coupling reactions using an HTE setup for micromole-scale experimentation in 96-well plates. Considering the size of this initial search space, an intentional decision to have a constant set of reaction conditions (base, temperature, solvent, concentrations) was made, although various conditions inspired by the Ullmann literature (24) were surveyed for operability and reproducibility prior to deployment (Fig. , see SI for additional details).