Sadeque, Farig YousufAhmed, AbrarAlam, NusaibaRahman, Md. Tawhidur2025-06-162025-06-1620252025-01ID 21301309ID 21301274ID 21301308http://hdl.handle.net/10361/26058Cataloged from PDF version of thesis.Includes bibliographical references (pages 69-72).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2025.The research paper introduces a methodology and analysis paradigm for evaluating and investigating a company’s state through Machine Learning (ML) and Natural Language Processing (NLP). Going beyond traditional analytical limits, this technique provides a comprehensive assessment of a company’s health. This approach enables corporations to make smarter choices, modify their strategies, and position themselves for long-term success. Additionally, the methodology assists Financial Advisors in offering insightful client counsel, eliminating the need for manual company research. In conclusion, this research paper uses Machine Learning (ML) and Natural Language Processing (NLP) to present company health assessments, fostering smarter decisions, adapting to evolving changes, and strategy optimization to sustain success in the corporate world as it navigates the complex terrain of understanding a company’s health.72 pagesenBRAC University theses reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Company evaluationStock market analysisFinancial insightNatural language processingMachine learningMachine learning.Natural language processing (Computer science).Computational linguistics.Human-computer interaction--Industrial applications.Thesis