BugMind

BugMind is an AI-native issue tracker that understands bugs, not just tickets

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Inspiration

I worked as a Software Engineer in a Technical Support domain where my day to day responsibilites included working with tickets and troubleshooting. Based on that, I got an idea, where I thought of building ticket tracker tool for teams powered by AI which can help teams to speed up ticket resolution to meet deadlines faster.

What it does

It is a issue or ticket tracker application where teams can not only work on their tickets with manual effort, but also use Generative AI to resolve tickets.

How I built it

I build the app with tools such as React, Redux, Python Flask, Gemini 3 Flash Api, Json-Server (Fake backend API), Google Stitch (To generate UI and HTML) and used some AI generated tickets to test the app. Flask app interacts with the information provided by the frontend React app and generates the root cause analysis and optional code fix. Json-Server is a fake backend API that is used to store tickets and user information.

Architecture

The Json-Server interacts with Frontend React application and vice-versa. Json-Server server stores data of tickets and users. In the AI resolution section the ticket data is posted through flask api to the AI_Engine. There after the response is generated, the root cause analysis and code fix is then fetched back as response to the frontend where the data is then taken and updated accordingly.

Challenges I ran into

I created a very interactive apps. Initially, I had trouble finding the right database for the project only to understand later that Json-Server could be a good and flexible choice to fasten up the development process as no dedicated backend server is required for it. Challenges in frontend side were mainly with choosing the right data struture or data types such as where to choose a set or a arraylist or object so that code execution could be faster. I also put a lot of time working on User Experience and wanter to ensure a very comfortable experience for users working with the app. For that I tried to implement as much as error handling and clarity as I could. Although there were many plans, but I chose to keep some functionalities unhandled for as of now and maybe I can work on it later. What I mean is that some buttons or features in the app are still redundant such as Export to csv and some filters. Lastly, I had interest in working with notification features but could not work on it as of now.

Accomplishments that I am proud of

I am proud to create such a beautiful app with so much precision and passion. And the fun fact is that it is working very good. For all the information provided in the ticket, the Gemini 3 Flash API is giving a very good and apt response. I am also feeling great because I think this is one of the very difficult projects I have done till now. It took intense programming and brainstorming and although I was a bit worried at first, but now I feel good that I could make it.

What I learned

This was my first Generative AI project. I learned alot about handling data through API's and how I could generate response by querying the Gemini 3 API.

What's next for BugMind

If this project goes well and creates an impact to judges, I am keen to work and develop it for a larger purpose. As mentioned before there are a lot of work left to do on this project. I can think of some other possibilities that be good for both Tech teams and for business. Let's hope for best!!

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