CABGENIE: AI-Powered Multi-Provider Cab Booking and Ride Management System

Kanawade Arnav; Shendage Shubham; Shinde Viraj; Somwanshi Purvesh; A. N. Birari

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 13 | 03 | Page :

Kanawade Arnav,

Shendage Shubham,

Shinde Viraj,

Somwanshi Purvesh,

A. N. Birari,

Student, Department of Information Technology, Jawahar Education Society’s Institute of Technology, Management and Research, Maharashtra, India
Student, Department of Information Technology, Jawahar Education Society’s Institute of Technology, Management and Research, Maharashtra, India
Student, Department of Information Technology, Jawahar Education Society’s Institute of Technology, Management and Research, Maharashtra, India
Student, Department of Information Technology, Jawahar Education Society’s Institute of Technology, Management and Research, Maharashtra, India
Assistant Professor, Department of Information Technology, Jawahar Education Society’s Institute of Technology, Management and Research, Maharashtra, India

Abstract

Urban transportation today demands far more than a simple cab booking interface. CABGENIE is an AI-powered, multi-provider ride management platform that brings together Uber, Ola, Rapido, and BlaBlaCar under one intelligent roof. Rather than forcing passengers to juggle multiple apps and compare prices manually, CABGENIE does the thinking for them. Its embedded AI Agent analyses real-time availability, fare competitiveness, driver ratings, estimated arrival times, weather conditions, and personal ride history to recommend the single best cab option at any given moment. The system also incorporates a dedicated women’s safety protocol, voice-based multilingual booking, a fraud detection engine, and a PCI-compliant UPI-integrated payment gateway. Built on a microservices architecture using Node.js, React.js, Python, MongoDB Atlas, and Firebase, CABGENIE is designed to be modular, scalable, and future-ready. This paper describes the system’s design philosophy, functional modules, AI decision engine, integration strategy, and the engineering choices that make it stand apart from conventional ride-hailing clones.

Keywords: Multi-Provider Cab Aggregation, AI Agent, Ride Recommendation, MCP Architecture, Women’s Safety, Fraud Detection, UPI Payment, Microservices, Real-Time Tracking, Urban Mobility

How to cite this article: Kanawade Arnav, Shendage Shubham, Shinde Viraj, Somwanshi Purvesh, A. N. Birari. CABGENIE: AI-Powered Multi-Provider Cab Booking and Ride Management System. Journal of Software Engineering Tools & Technology Trends. 2026; 13(03):-.

How to cite this URL: Kanawade Arnav, Shendage Shubham, Shinde Viraj, Somwanshi Purvesh, A. N. Birari. CABGENIE: AI-Powered Multi-Provider Cab Booking and Ride Management System. Journal of Software Engineering Tools & Technology Trends. 2026; 13(03):-. Available from: https://journals.stmjournals.com/josettt/article=2026/view=260876

References

Ahead of Print Subscription Original Research

Journal of Software Engineering Tools & Technology Trends

ISSN: 2394-7292

Volume	13
	03
Received	31/07/2026
Accepted	31/08/2026
Published		10/09/2026
Publication Time	41 Days

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