The design, modelling and simulation of solid-liquid mixers remains one of the least advanced aspects of particulate processing due to difficulties in quantifying complex slurry hydrodynamics from first principles and in acquiring reliable experimental data for model verification and development. This contribution describes the application of electrical resistance tomography (ERT) for three-dimensional imaging of the concentration of solids in a slurry mixer as a function of key process variables (particle size, impeller type, agitation speed). It is demonstrated how ERT can provide a wealth of detailed data to allow model development, which ultimately will lead to much improved design capabilities and the generation of mixing models which could reside within particle process simulators. This principle is illustrated using descriptions of mixer behaviour based on an empirical approach, although the measurement methodology described is equally suited to development of computational fluid dynamics models, cellular models or design approaches based on artificial intelligence. It is demonstrated that ERT can be used for routine acquisition of experimental information thereby accelerating the development of empirical correlations for design and scale-up. The experimental data can be built into a visualization databank, which acts as a ‘process toolkit’ by allowing a library of process responses to be catalogued. Hence these data can be accessed for the purposes of model development, equipment selection, optimization of operating conditions or testing on-line control strategies.