We will create an artificially intelligent system which will self-optimise chemical manufacturing to flexibly adapt to variation in external factors (e.g. supply chain issues, cost, environment) by utilising chemical molecular property maps to suggest alternative suitable reagents, catalyst, solvents. This rapid, flexible system will be essential for promoting manufacturing by developing a more responsive chemical manufacturing framework. Here the routes will be tailored for agrochemical applications in line with our industrial partners' interests, but the components of the technology will be transferable across differing chemical manufacturing sectors. We will assemble and program a system capable of conducting several discrete chemical processing options including (i) changing catalyst or reagent choice (ii) altering reactor configuration (e.g. batch to CSTR) (iii) differing requirements based on response to external influences (e.g. cost changes due to COVID19). The system will be programmed by computationally intelligent algorithms which enable self-optimisation of the processes without user interaction or their immediate knowledge (i.e. being invisible) and made accessible through a user-friendly interface.