Abstract: Tone Tracker's integration of BERT and LSTM technologies allows it to predict and flag offensive language in both Tamil and English social media comments. BERT, a transformer-based model, enables the tool to understand the semantic context of text in multiple languages, ensuring accurate detection of inappropriate content regardless of language. The incorporation of LSTM further enhances this capability by capturing nuanced contextual information, refining the tool's proficiency in content moderation for both Tamil and English content. With its user-friendly features, Tone Tracker becomes accessible to a diverse user base, empowering them to swiftly remove offensive content in both languages and contribute to fostering a secure digital environment. This groundbreaking innovation not only boosts content moderation efficiency but also ensures scalability across various digital platforms, making it adaptable to the linguistic diversity of online communities. Ultimately, Tone Tracker, powered by LSTM and BERT, plays a pivotal role in cultivating positive online spaces where users can engage confidently and respectfully in both Tamil and English.