A machine learning software was developed for automatic analyses of metallographic duplex stainless steel samples, measuring the ferrite content and austenite spacing. Handling preparation artifact is the crucial point for this software to be used in an industrial context. Structuring the industrial workflow according to this software has allowed a great saving of time, an increase in the quality of the data collected and the creation of large and reliable databases.