Personal Data Discovery

Artificial-intelligence computer-implemented processes and machines predict whether personal data may be present in structured software based on metadata field(s) contained therein. Natural language processing preprocesses input strings corresponding to the metadata field(s) into normalized input sequence(s). Individual characters in the sequence(s) are embedded into fixed-dimension vectors of real numbers. Bidirectional LSTM(s) or other machine-learning algorithm(s) are utilized to generate forward and backward contextualization(s). Neural network output(s) are provided based on element-wise averaging or feed forwarding based on the contextualization(s) in order to predict whether one or more value fields corresponding to the metadata field(s) may contain personal data.