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AI System to Summarize and Analyze Legal Documents: A Transformative Approach

Dr.V Shanmugapriya

shanmugapriyav@skasc.ac.in

(Assistant Professor - Department of Computer Science)

Guru Moorthy S 22BCS019, Akash K 22BCS004, Sanjay S 22BCS046

gurumoorthys22bcs019@skasc.ac.in, akashk22bcs004@skasc.ac.in, sanjays22bcs046@skasc.ac.in,

Sri Krishna Arts and Science College, Coimbatore

 

ABSTRACT :

Legal documents, such as contracts, agreements, and case summaries, are often complex, lengthy, and difficult to comprehend. Understanding these documents requires significant time and effort, particularly for legal professionals and businesses dealing with extensive paperwork daily. The emergence of Artificial Intelligence (AI) has opened new possibilities for automating the analysis and summarization of legal texts, making them more accessible and easier to interpret. This paper explores the development of an AI-powered system designed to read, classify, summarize, and analyze legal documents, enabling users to extract essential information quickly and efficiently.

The proposed AI system leverages Natural Language Processing (NLP) techniques to process legal language, identify key clauses, and generate concise summaries while preserving the original meaning. Additionally, it incorporates risk detection capabilities to highlight potentially problematic sections, such as ambiguous terms, unfair clauses, or legal inconsistencies that might require further review. The system also features an advanced search function that allows users to locate specific terms and phrases within lengthy documents, further enhancing usability.

To develop this system, a substantial dataset of legal documents is required for training machine learning models, ensuring that the AI can accurately classify different types of legal texts and generate meaningful insights. The integration of Optical Character Recognition (OCR) further enables the AI to process scanned or printed legal documents, expanding its applicability to various formats. A user-friendly interface is designed to facilitate seamless interaction, allowing users to upload documents and receive structured summaries, risk assessments, and suggestions for potential improvements.

Despite the promising advantages, the development of such an AI-driven legal analysis tool presents several challenges, including the complexity of legal language, the necessity for high accuracy, and the demand for real-time processing. Addressing these challenges involves refining NLP models, enhancing risk detection algorithms, and continuously testing the system to ensure reliability and precision.

This study demonstrates how AI can revolutionize legal document analysis, significantly reducing the time and effort required for document review. By automating the summarization and risk detection process, this AI-powered system has the potential to benefit legal professionals, businesses, and policymakers by offering a more efficient and accurate approach to handling legal documentation. The findings and methodologies discussed in this paper pave the way for future advancements, including multilingual support and applications in other domains such as healthcare, real estate, and regulatory compliance.

Keywords: Artificial Intelligence (AI), Natural Language Processing (NLP), Legal Document Analysis, Contract Summarization, Risk Detection, LegalTech, Machine Learning, Optical Character Recognition (OCR), Automated Legal Review, Clause Identification, Legal Text Processing, AI-Powered Summarization, Document Classification, Legal Compliance, Smart Contracts.

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