The CAMIO project aims to make a 'real time' and optimum selection, in relation to 2.5 and 3 axis cutting strategies, for machining parts on high productivity machining centres. The results will lead to a reduction of CNC program preparation time, reduced machine tool downtime, reduced machining costs, longer cutting tool life and greater flexibility of shop floor personnel. This will be achieved through a combination of AI learning and optimisation techniques (such as Genetic Algorithms and Neural Networks) and fast implementation (through off load accelerator techniques based on parallel computing). This will reduce the time to develop and optimise a CAM design, for a complex object, by orders of magnitude. A highly robust solution will be ' delivered by learning from analysed results in order to obtain the optimum solution.