To tackle the problem we have used the Levenshtein algorithm, which allows tracking the percentage of rows’ matchings. We have implemented this solution, so that when creating new address entries, the system will automatically find the similar ones, rank them from 100 to zero, and push the most relevant ones up. When entering a new address, an operator will see all the similar records and decide, whether to edit the old entry in case of a mistake, or create a new one. There were also added lots of filters that help to find an address more precisely and limit the search to a country or state. All the contacts have been organized into groups.