AUTOMATED TICKET RESOLUTION

A device, including a memory storing instructions, and one or more processors that execute the instructions causing the one or more processors to communicate with a server to obtain historical ticket data, generate a plurality of data models based on processing the historical ticket data, a different data model, of the plurality of data models, generated for a different ticket type in the historical ticket data, communicate with a client device to obtain ticket data relating to an issue associated with a project, classify, using a particular data model of the plurality of data models to apply a natural language processing technique, the ticket data into a first ticket type, train the particular data model by receiving an indication regarding whether to modify a classification of the ticket data from the first ticket type to a second ticket type, modify, based on receiving the indication, the classification of the ticket data from the first ticket type to the second ticket type, process, using the particular data model based on training the particular data model and based on modifying the classification of the ticket data, a subset of the historical ticket data, generate, using the particular data model and based on processing the subset of the historical ticket data, a set of recommended resolutions for resolving the issue, select, from the set of recommended resolutions, a particular resolution based on one or more values that indicate an effectiveness level of the particular resolution for one or more issues associated with the historical ticket data, perform one or more actions to implement the particular resolution to resolve the issue, the one or more actions based on the issue being internal to the device and including at least one of an automatic generation of additional code directed to resolving the issue, an automatic alteration of existing code of the project to produce altered code directed to resolving the issue, or an automatic removal of existing code of the project to resolve the issue, apply a machine learning technique to one or more of the ticket data or the historical ticket data, the machine learning technique applied to predict another issue, generate additional ticket data based on predicting the other issue, the additional ticket data different than the ticket data or the historical ticket data, and generate, using the particular data model, another set of recommended resolutions for resolving the other issue. D, 4- 0 Cu -0 0 w CU 0