We developed a POC using Natural Language Processing (NLP) to classify and prioritize complaints. Various NLP techniques like stop word removal, lemmatization, stemming, vectorizing using TF-ID, etc. were applied to pre-process the complaint data. Once vectorized, various machine learning classification algorithms like Logistic Regression, Support Vector Machine, etc. were used to classify the data into the correct categories automatically. For prioritization, Sentiment Analysis techniques were applied. Priority was assigned based on the sentiment and polarity of the text.