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AI-Powered Legal Documentation System
Nikhil K S Pratham U G
School of Engineering School of Engineering
Presidency University Presidency University
Bangalore, India Bangalore, India
kagdasnikhil@gmail.com prathamug4@gmail.com
Information Science Engineering, Presidency University
Under The Guidance Of
Dr. Shanmugarathinam G Prof. Srinivas Mishra Professor
School of Computer Science School of Computer Science
and Engineering and Engineering
Presidency University Presidency University
Abstract-
The increasing complexity and volume of legal documentation necessitate innovative solutions to enhance accuracy, efficiency, and accessibility within the legal domain. An AI-powered Legal Documentation System leverages advanced technologies such as natural language processing (NLP), machine learning, and intelligent automation to streamline the creation, review, and management of legal documents. This system is designed to assist legal professionals in generating contracts, agreements, and other legal texts with reduced time and error rates, while ensuring compliance with current laws and standards. By automating routine tasks like clause suggestions, document formatting, and risk identification, the system enhances productivity and allows legal experts to focus on higher-value activities. Additionally, it offers capabilities such as intelligent search, version control, and real-time collaboration, transforming traditional legal workflows into agile, data-driven processes. This paper explores the architecture, functionalities, benefits, and potential challenges of implementing AI in legal documentation, demonstrating its transformative impact on the legal industry.
The legal industry is undergoing a significant transformation driven by the integration of Artificial Intelligence (AI) into its core operations. Among the most impactful advancements is the development of AI-powered Legal Documentation Systems, which are revolutionizing how legal documents are drafted, reviewed, analyzed, and managed. These systems employ advanced technologies such as Natural Language Processing (NLP), machine learning (ML), and deep learning algorithms to automate and optimize the traditionally labor-intensive processes associated with legal documentation.
