User-generated content is a double-edged sword for online platforms, offering growth opportunities while posing significant moderation challenges due to its vast volume. Traditional manual moderation is impractical, prompting the need for scalable solutions like automated Natural Language Processing (NLP) systems. Large Language Models (LLMs) present a promising approach by utilizing pre-trained machine learning systems that significantly reduce the amount of labeled training data needed for effective text classification, including tasks like toxicity detection. This advancement democratizes the ability of teams to implement content moderation systems without extensive resources. The Cohere platform further accelerates this process by providing an LLM API that allows for quick implementation of text classification tasks with minimal labeled data, making content moderation more accessible and efficient for teams.