A chatbot is a conversational device designed to provide smart communication with humans through speech and text. Chatbots emerge as virtual machines that interact with humans through their dialect, offering both spoken and textual conversation and responses to questions. In recent times, there has been tremendous progress in the development of virtual assistants and chatbots with advanced technologies based on speech recognition. This paper presents a chatbot for the web-based Crime Reporting and Handling System in the Malawi Police Service. The chatbot utilizes a combination of classification and generative models. It features a complaint registration system that allows users to file complaints. A custom named entity recognition model is employed to extract structured information such as location, time, and crime type from unstructured complaints, enabling authorities to comprehend complaints effectively and efficiently. The chatbot strives to provide efficient and user-friendly methods for registering complaints using these techniques, as well as informing individuals about the crime reporting and handling system. Thus, the system aspires to apply Natural Language Processing (NLP) for social good. In this paper, we will discuss how chatbots are designed, the machine learning and deep learning techniques and algorithms used, compare the technologies, and evaluate the performance of chatbots. Chatbots are becoming friendlier to humans, evolving beyond mere communication machines and representing future aspects of human and technology interaction.