Development of a Sentiment-Aware Mental Health Support Chatbot with Automated Escalation

Objective: To engineer and deploy a cloud-native chatbot system that provides initial mental health support and contextually escalates critical cases to human counselors based on real-time sentiment analysis.

Mental health concerns among students and young professionals in India are rising, but there is a shortage of accessible, non-judgmental, and timely support mechanisms. Many affected individuals avoid seeking help due to stigma, lack of awareness, and logistical barriers.

This project aims to address this gap by building an AI-powered chatbot that offers 24/7 mental wellness conversations, detects negative sentiment or crisis cues using natural language processing, and automatically escalates high-risk cases to qualified human counselors via secure channels.

The solution will use cloud-native technologies for scalability and security, integrate pre-trained Indian language models for sentiment detection, and include a dashboard for counselors to manage escalations. The working prototype will demonstrate real-time chat, context-sensitive sentiment detection, escalation triggers, and an admin dashboard, deployed on a public cloud platform.

This project has the potential to improve access to early mental health support in educational institutions and urban workplaces, enabling timely intervention and reducing stigma. The modular, scalable architecture supports future integration with healthtech platforms and can be adapted for multilingual and pan-India deployment.