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  Published Paper Details:

  Authors

  Manoj Patil,  Pravin Rajnale,  Sonu Sharma,  Mayank Rathod,  Soham Sarwadhikari

  Keywords

Artificial Intelligence, Ticketing System, Issue Tracking, Machine Learning, Natural Language Processing, Automation, Software Support

  Abstract


In today's fast-moving world of software development, bugs and the little glitches that stop programs from working right are a big headache. Fixing them the old way takes too much time and effort. Support teams often feel buried under piles of reports, trying to figure out what's most important and who should fix it. This slow process can upset customers, delay projects, and even hurt a company's name. Our paper brings a fresh solution: an AI-powered ticketing and issue-tracking system that takes the stress out of bug fixing. This system isn't just a tool. It's like a smart helper that uses advanced technologies like machine learning (ML) and natural language processing (NLP). Machine learning is like giving the computer a brain to learn from past mistakes so it can spot patterns and make decisions. For example, if it sees that bugs about "app crashes" are always urgent, it learns to flag them fast. Natural language processing, meanwhile, helps the system understand what people write in their bug reports. If someone says, "The payment page isn't loading," the AI knows it's a serious issue tied to money, so it acts quickly. Imagine a busy support team getting dozens of bug reports every day. Without help, they'd spend hours just reading and sorting them. Our system changes that. It automatically sorts tickets into categories--like "website issues" or "app crashes"--and decides which ones need fixing first. It can even suggest solutions based on what worked before. For instance, if restarting a server fixed a similar problem last time, it might recommend that right away. What makes this system special is how it works in real time. As soon as a bug is reported, the AI analyzes, sorts, and sends it to the right person without anyone lifting a finger. It's built with modern web tools, so it's easy to use and can grow with a company, whether it's a small startup or a big business.This means faster fixes, happier customers, and less pressure on support teams. But it's not just about speed. The system also makes things more accurate. No more guessing which bug is urgent or sending it to the wrong team. Cutting down mistakes keeps everyone on the same page: developers, support staff, and customers. Plus, it's flexible enough to fit into whatever tools a company already uses, like email or project apps. In short, our AI-powered ticketing system is a game-changer. It turns a messy, tiring process into something smooth and smart.This paper will walk you through how it works, why it's needed, and how it can make bug fixing better for everyone. Whether you're a developer tired of endless tickets or a manager wanting happier users, this system has something for you.

  Cite this article

  Manoj Patil,  Pravin Rajnale,  Sonu Sharma,  Mayank Rathod,  Soham Sarwadhikari,   "An AI-Powered Ticketing and Issue Tracking System for Efficient Bug Resolution", IJRAR - International Journal of Research and Analytical Reviews (IJRAR), E-ISSN 2348-1269, P- ISSN 2349-5138, Volume.12, Issue 1, Page No pp.13-20, March 2025, Available at : http://www.ijrar.org/IJRAR25A2996.pdf  

  IJRAR's Publication Details

  Unique Identification Number - IJRAR25A2996

  Paper ID - 307878

  Author type - Indian Author

  Page Number(s) - 13-20

  Pubished in - Volume 12 | Issue 1 | March 2025

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.44443

  No Of Downloads - 98

  Author Country - India, 400053, Mumbai, Mumbai, 400053, Science and Technology

  Publisher Name - IJPUBLICATION | IJRAR | www.ijrar.org | E-ISSN 2348-1269, P- ISSN 2349-5138

  E-ISSN 2348-1269, P- ISSN 2349-5138

  Published Paper PDF : - http://www.ijrar.org/papers/IJRAR25A2996

  Published Paper URL: : - http://ijrar.org/viewfull.php?&p_id=IJRAR25A2996

  Published Paper PDF Downlaod: - download.php?file=IJRAR25A2996

  Cite this article

  Manoj Patil,  Pravin Rajnale,  Sonu Sharma,  Mayank Rathod,  Soham Sarwadhikari,   "An AI-Powered Ticketing and Issue Tracking System for Efficient Bug Resolution", IJRAR - International Journal of Research and Analytical Reviews (IJRAR), E-ISSN 2348-1269, P- ISSN 2349-5138, Volume.12, Issue 1, Page No pp.13-20, March 2025, Available at : http://www.ijrar.org/IJRAR25A2996.pdf

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