Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{192771,
        author = {Aryav Jain and Akshat Kumar and Pratibha Gautam and Sweta Yadav},
        title = {Sarthi – The Helping Hand: An AI-Assisted Framework for Optimizing NGO–Volunteer Coordination},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {2818-2827},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192771},
        abstract = {Coordinating volunteer efforts with organizational needs remains a persistent operational challenge faced by non-governmental organizations (NGOs) across India. Current volunteer management approaches rely heavily on manual processes such as spreadsheet-based tracking and messaging applications, leading to suboptimal matching, delayed mobilization, and underutilization of available human resources. This research presents Sarthi – The Helping Hand, an AI-assisted digital platform engineered to facilitate intelligent matching between volunteers and NGO projects by leveraging content-based filtering algorithms. The system incorporates integrated modules for user onboarding, skill-based task assignment, real-time communication, transparent feedback mechanisms, achievement-based gamification, and administrative analytics. A working prototype was developed and tested through a controlled pilot study involving participating NGOs and 10–20 volunteer participants across a three-month evaluation window. Experimental validation demonstrated matching accuracy ranging from 60–75%, with measurable improvements in coordination efficiency compared to conventional manual approaches, it tries to improve task transparency & sustained engagement through gamified elements. The study identifies current system limitations and outlines strategic directions for enhanced feature development, increased scalability, and expanded geographic deployment. This work demonstrates the viability of AI-assisted volunteer management systems in the Indian social sector context and provides a replicable framework for digital innovation in community-driven initiatives.},
        keywords = {Volunteer management, non-governmental organizations, Artificial intelligence, Content-based filtering, Task allocation, Resource optimization, Gamification, Digital platforms, social impact technology.},
        month = {February},
        }