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AI-Driven Mental Health Assistant for Working Professionals
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
DOI: https://doi.org/10.64388/IREV9I10-1715893
Abstract
The increased psychological pressure in today’s working environments requires easy access to mental health facilities. Issues like stress, burnouts, emotional exhaustion, and poor work-life balance are common in working environments. However, existing mental health facilities are not easily accessible due to social stigmas, lack of access, costs, and timing issues. This paper describes the design and implementation of an AI-powered Mental Health Assistant tool developed for working professionals. The tool utilizes Large Language Models, emotion detection, crisis detection, and a full-stack framework for providing continuous non-clinical emotional support to working professionals. The tool utilizes the MERN technology stack, which provides flexibility in deploying the tool and safe data storage options. An efficient prompt engineering framework ensures integrity, ethics, and safety regulations for each persona. The tool also utilizes crisis keyword detection for providing emergency resources to the user. The tool architecture is developed with emphasis on data privacy, data transparency, and data ethics in AI usage. The experimental results demonstrate the tool’s effectiveness in providing responsive, emotional, and flexible support to working professionals. The framework bridges the gap between mental health accessibility and intelligent, stigma-free tools for working professionals.
Keywords
Artificial Intelligence, Digital Mental Health, Large Language Models, Emotion Detection, Ethical AI, MERN Stack, Crisis Detection, Conversational Agents.
How to cite this paper
@article{1715893,
author = {Preethi Ganesh Babu, Murali D, Obliraj R, Pavan Kumar PK, G Sharmila},
title = {AI-Driven Mental Health Assistant for Working Professionals},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {10},
pages = {193-200},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715893.pdf},
abstract = {The increased psychological pressure in today’s working environments requires easy access to mental health facilities. Issues like stress, burnouts, emotional exhaustion, and poor work-life balance are common in working environments. However, existing mental health facilities are not easily accessible due to social stigmas, lack of access, costs, and timing issues. This paper describes the design and implementation of an AI-powered Mental Health Assistant tool developed for working professionals. The tool utilizes Large Language Models, emotion detection, crisis detection, and a full-stack framework for providing continuous non-clinical emotional support to working professionals. The tool utilizes the MERN technology stack, which provides flexibility in deploying the tool and safe data storage options. An efficient prompt engineering framework ensures integrity, ethics, and safety regulations for each persona. The tool also utilizes crisis keyword detection for providing emergency resources to the user. The tool architecture is developed with emphasis on data privacy, data transparency, and data ethics in AI usage. The experimental results demonstrate the tool’s effectiveness in providing responsive, emotional, and flexible support to working professionals. The framework bridges the gap between mental health accessibility and intelligent, stigma-free tools for working professionals.},
keywords = {Artificial Intelligence, Digital Mental Health, Large Language Models, Emotion Detection, Ethical AI, MERN Stack, Crisis Detection, Conversational Agents.},
month = {April},
doi = {https://doi.org/10.64388/IREV9I10-1715893}
}