Mindcare: A Multi-Agent AI Architecture for Personalized and Responsible Mental Health Support

Vishal Pattar, Tanishk Patil, Bhaskar Dhuri, Amanullah Karel, Aboli Deole and Sampada Kulkarni
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Vishal Pattar: Dept. of Artificial Intelligence & Machine Learning PES’s Modern College of Engineering Pune, MH, India
Tanishk Patil: Dept. of Artificial Intelligence & Machine Learning PES’s Modern College of Engineering Pune, MH, India
Bhaskar Dhuri: Dept. of Artificial Intelligence & Machine Learning PES’s Modern College of Engineering Pune, MH, India
Amanullah Karel: Dept. of Artificial Intelligence & Machine Learning PES’s Modern College of Engineering Pune, MH, India
Aboli Deole: Dept. of Artificial Intelligence & Machine Learning PES’s Modern College of Engineering Pune, MH, India
Sampada Kulkarni: Dept. of Information Technology PES’s Modern College of Engineering Pune, MH, India

International Journal of Research and Scientific Innovation, 2025, vol. 12, issue 5, 2006-2021

Abstract: Mental health challenges such as stress, anx- iety, depression, and loneliness are increasingly prevalent worldwide, exacerbated by stigma and limited access to professional care—especially in low-resource settings. This paper introduces MindCare, an AI-powered mental health companion chatbot designed to support individuals expe- riencing mild psychological distress. Leveraging fine-tuned large language models (LLMs), MindCare employs a mod- ular architecture with dedicated agents for intent recogni- tion, compliance checking, psychiatric response generation, memory management, correction, and empathetic interac- tion. The system is trained on curated, anonymized datasets from mental health forums and authoritative sources to ensure contextual accuracy and emotional sensitivity. Comparative evaluations show that MindCare outperforms generic conversational agents in emotional responsiveness, relevance, and user satisfaction. This study outlines the system design, data strategy, and evaluation methodology, positioning MindCare as a scalable and ethical digital tool for mental health support. Future work will focus on adding multilingual, voice-based interaction and real-time escalation to human counselors for enhanced accessibility and personalization.

Date: 2025
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