Design and Implementation of a Reporting Module for a Software Development Company

This thesis focuses on the design and implementation of an intelligent reporting module for the management of an IT company. Its main objective is to extend an existing web application with an advanced analytics layer utilizing generative artificial intelligence, which will provide management with a proactive overview of the status of development processes and human resources. The first part of the thesis analyzes management’s information needs in an agile environment and identifies risks associated with data fragmentation in isolated transactional systems (GitLab, JIRA, SonarQube, BambooHR). The second part then focuses on the design of data integration and the architectural solution for the analytical layer. From a technological standpoint, the solution is strictly divided into a presentation layer in the React JavaScript library and an asynchronous backend in Python, with the user interface emphasizing the minimization of context switching through the drill-through principle. The stated objective was achieved in the third part of the thesis through the implementation of a proactive layer that uses a large language model (Google Gemini) to automate the evaluation of complex process relationships, thereby replacing the previous passive reporting. The result of this work is a pilot proof of concept that demonstrates how artificial intelligence can effectively reduce the cognitive load on managers and identify risks to the stability of the development cycle in a timely manner.