We developed NLP pipelines to clean, process, and extract relevant details from the web-scraped content. The user data and user-generated content were flagged by the client’s moderators, which helped us train and fine-tune machine learning models. We combined the client’s data with publicly available datasets of toxic posts and customized rule-based algorithms to detect PII and other blacklisted items. Dynamic training was used for enabling the models to automatically learn from newer posts and improve performance.