Mindcare AI: Transforming Mental Health Support with AI
Janapala Lohith Kumar1, Topella Venkata Mahipathi Rao2, Vetsa Ganesh3, Puttur Swetha4, Jonathan Bathula5
1Janapala Lohith Kumar, Student, Department of Computer Science & Engineering, KL University, Guntur (Andhra Pradesh), India.
2Topella Mahipathi Rao, Student, Department of Computer Science & Engineering, KL University, Guntur (Andhra Pradesh), India.
3Vetsa Ganesh, Student, Department of Computer Science & Engineering, KL University, Guntur (Andhra Pradesh), India.
4Puttur Swetha, Student, Department of Computer Science & Engineering, KL University, Guntur (Andhra Pradesh), India.
5Jonathan Bathula, Assistant Professor, Department of Computer Science & Engineering, KL University, Guntur (Andhra Pradesh), India.
Manuscript received on 28 February 2026 | Revised Manuscript received on 08 March 2026 | Manuscript Accepted on 15 March 2026 | Manuscript published on 30 March 2026 | PP: 14-19 | Volume-6 Issue-3 March 2026 | Retrieval Number: 100.1/ijpmh.C114206030326 | DOI: 10.54105/ijpmh.C1142.06030326
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© The Authors. Published by Lattice Science Publication (LSP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Mind Care AI is an AI-driven conversational agent designed to bridge the gap between unmet demand for mental health services and limited therapeutic resources. The platform combines advanced natural language processing (NLP), finetuned transformer models (Llama 3.2), cognitive-behavioural therapy (CBT) modules, and a reinforcement-learning personalisation layer to deliver real-time, evidence-based mental health support. In a four-week pilot study with 100 participants, the emotion detection module achieved an accuracy of 88% and an F-score of 0.88. At the same time, user engagement metrics showed high repeat-usage rates and positive satisfaction scores. MindCare AI operates 24/7, addresses stigma through a discreet self-care coach interface, and follows a blended model of care that escalates users to professional counsellors when necessary. Privacy is ensured through AES-256 encryption and compliance with GDPR and HIPAA. Future work includes multimodal input, multilingual support, wearable integration, and deeper integration with clinical workflows. These results validate MindCare AI as a promising, scalable solution for democratising access to mental health support.
Keywords: Artificial Intelligence, Cognitive Behavioural Therapy, Conversational Agent, Emotion Recognition, Mental Health, Natural Language Processing, Personalization.
Scope of the Article: Maternal Health