Materials acceleration platforms have the potential to reduce the cost- and time-to-market of new materials from 20 million USD and 20 years to as little as 1 million USD and 1 year; however, the capital and expertise are often significant. Previously, we introduced the idea of a minimal working example for a self-driving laboratory that uses RGB light-emitting diodes and a discrete-channel spectrophotometer in conjunction with optimization algorithms to match target spectra. We extend this idea to a color-matching materials optimization problem using dilute colored dyes. This optimization task costs less than 300 USD, requires less than three square feet of desk space, and less than three hours of total setup time from the shopping cart to the first “autonomous drive.” The demo is modular and extensible; additional peristaltic pump channels can be added, the dye reservoirs can be increased, and chemically sensitive parts can be replaced with chemically resistant ones.