Remadder is a software tool which can be used both to identify related records in two separate data sets or to identify duplicate records in a data set. This class of tasks is commonly reffered as record linkage, data matching, data duplicate detection, data deduplication, etc. Remadder successfully addresses hard problem of fuzzy data matching when two related data sets does not share exact common unique identifier. Instead of usual and simple primary/foreign key relational approach, in such cases data matching has to be established on basis of string fuzzy match similarity. This, however, is a complex and resource extensive task exhausting even for the most powerful computers of today. Remadder uses inventive and unique approach for fuzzy match analysis, utilizing various string similarity metrics, along with powerful machine learning algorithms. By allowing users to define exact matching constraints, fuzzy matching constraints and all other constraints in visual and intuitive way, all the complexity of the fuzzy match analysis is hidden from the user and he/she can focus on the business case, rather than technical issues. By combining advanced artificial intelligence with clever blocking techniques and multiple string similarity metrics, ReMaDDer provides unique and superb solution for fully automatic records matching and data deduplication projects.