International Journal of Scientific Research and Engineering Development

This paper presents Local Helper Finder, a comprehensive digital platform engineered to bridge the gap between service seekers and skilled local service providers. The platform addresses persistent real-world challenges including the difficulty of locating reliable help, lack of transparent pricing, safety concerns, and inefficient scheduling. At its core, the system integrates an AI-powered recommendation engine that performs intelligent, location-based matching by factoring service type, proximity, and user ratings. Built on a three-tier client-server architecture and deployable across web and mobile interfaces, the platform incorporates real-time in-app communication, secure payment processing, and a transparent two-way rating mechanism. Development follows the Waterfall model with technologies including React, Flutter, Node.js, PostgreSQL, and Firebase. Key outcomes include reduced service search time, improved earning opportunities for local helpers, and enhanced community trust. The system is evaluated against 15 test cases covering functional, performance, security, and compatibility dimensions, all returning satisfactory results.

Darshan Babasaheb Gadhe, Sanket Tarachand Shinde, Atharva Govind Vaidya, Sudarshan Sharad Gambhire, Prof.P.V.Nagare,"Local Helper Finder: An AI-Powered Location-Based Service Matching Platform" International Journal of Scientific Research and Engineering Development, V9(3): Page(1283-1296) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.