Cooperative catalysis, in which multiple catalytic units operate synergistically, underpins a variety of synthetically and mechanistically important organic reactions1–4. Despite its potential utility in new reactivity contexts, approaches to the discovery of cooperative catalysts have been limited, typically relying on serendipity or on prior knowledge of single-catalyst reactivity1,5. Systematic searches for unanticipated types of catalyst cooperativity must contend with vast combinatorial complexity and are therefore not undertaken6–10. Here, we describe a pooling–deconvolution algorithm, inspired by group testing11, that identifies cooperative catalyst behaviors with low experimental cost while accommodating potential inhibitory effects between catalyst candidates. The workflow was validated first on simulated cooperativity data, and then by experimentally identifying previously documented cooperativity between organocatalysts in an enantioselective oxetane-opening reaction. The workflow was then applied in a discovery context to a Pd-catalyzed decarbonylative cross-coupling reaction, enabling the identification of several ligand pairs that promote the target transformation at substantially lower catalyst loading and temperature than previously reported with single ligand systems.