Authors : Prasanna Adhithya Balagopal; Jishnu Setia; Archit Lakhani

Volume/Issue : Volume 9 - 2024, Issue 9 - September

Google Scholar : https://tinyurl.com/bde6zj84

Scribd : https://tinyurl.com/484h5ve6

DOI : https://doi.org/10.38124/ijisrt/IJISRT24SEP106

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The purpose of this paper is to analyze the impacts of EunoKinetiX, an Enterprise Resource Planning SaaS ( Software as a Service ) in the Fleet Management spheres coupled with Route Optimization for more efficient Logistical provision. EunoKinetiX is a platform intended to assist Logistical providers manage their services and resources, both machine and human power. The product employs artificial intelligence, both predictive and generative for route optimization and payload allocation, effectively reducing costs, CO2 emissions, and saving valuable time. Through advanced analytics, it streamlines logistics, enhancing operational efficiency while contributing to environmental sustainability. The product's integration of AI technology showcases its potential to revolutionize contemporary fleet management practices, offering a compelling solution to disorganized systems to maximize profits.

Keywords : EunoKinetiX ,EuneX, KinetiX, Route Optimization, Fleet Management Software, Software as a Service, Enterprise Resource Planning, Predictive and Generative AI Model, Disorganized, Ineffective, On-Demand Service, Payload Allocation.

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