International Research Journal of Engineering and Technology (IRJET) Volume: 13 Issue: 02 | Feb 2026
www.irjet.net
e-ISSN: 2395-0056 p-ISSN: 2395-0072
AI Based - Legal Document Analyzer Shreya Sakpal1, Nidhi Shinde2, Unnati Shinde3, Samruddhi Jadhav4 1Shreya Sakpal Co, Viva Institute of Technology, Shirgaon, India 2Nidhi Shinde Co, Viva Institute of Technology, Shirgaon , India
3Unnati Shinde Co, Viva Institute of Technology, Shirgaon, India
4Samruddhi Jadhav Co, Viva Institute of Technology, Shirgaon, India
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Abstract - Legal documents often use complex language,
Reading and analyzing these documents takes a lot of time and legal knowledge. With improvements in AI and NLP, computers can now understand and process human language to some degree. These technologies allow for the automatic analysis of large amounts of text data. Using AI and NLP in the legal field can help simplify the analysis of legal documents and reduce the need for manual work.
include long clauses, and contain important obligations that need careful interpretation. This makes manual analysis challenging and time-consuming, especially for those without legal training. Understanding these documents promptly is crucial to reduce legal risks and support better decisionmaking. Traditional document review methods usually depend on manual reading or simple keyword tools. These methods can be inefficient, prone to mistakes, and limited in context.
The AI Legal Document Analyzer proposed in this paper aims to automate the process of legal document analysis. The system assists users by extracting key information, summarizing content, and presenting the results clearly. This project seeks to make legal documents easier to understand and more accessible to both legal professionals and the general public.
This paper discusses the design and development of an AIbased Legal Document Analyzer that automates the analysis of legal documents using Natural Language Processing and large language model techniques. The system accepts documents in PDF and Word formats, as well as direct text input, allowing for flexible and uniform processing. It applies text preprocessing and semantic analysis to create concise summaries, extract key elements like involved parties and important dates, identify significant clauses, and spot potential legal risks.
2. Proposed System The proposed system is an AI-based Legal Document Analyzer designed to help users interpret legal documents efficiently. Legal texts can be long and complex, which makes reviewing them manually challenging and slow. The system tackles this problem by providing an automated framework that analyzes legal content and extracts useful information in a structured way. Its purpose is to support users in understanding legal documents better, without taking the place of professional legal judgment.
Additionally, the system includes a Law Explorer module that identifies relevant legal provisions mentioned in the document and offers simple, context-aware explanations of applicable laws. This feature helps users gain a deeper understanding of legal concepts. By combining automated analysis with interactive exploration of legal knowledge, the proposed system increases efficiency, reduces manual work, and makes legal information more accessible. This solution is especially valuable for students, startups, and those without a legal background, providing useful insights and improving understanding of legal documents in real-world situations.
Users can input legal content by uploading documents or entering text directly, providing flexibility. After receiving the input, the system changes the document into a standardized text format suitable for analysis. A preprocessing pipeline organizes the content by separating sections, identifying sentence boundaries, and getting the text ready for further interpretation. This structured preparation ensures that the legal information is processed accurately and consistently.
Key Words: Legal Document Analysis, Natural Language Processing, Artificial Intelligence, Large Language Models, Law Explorer, Clause Extraction, Risk Detection
1. INTRODUCTION
Once preprocessing is complete, the system uses Natural Language Processing techniques to analyze the legal text. It identifies key clauses, contract conditions, responsibilities,
Legal documents are important in areas like courts, companies, educational institutions, and government organizations. Documents such as contracts, service agreements, terms and conditions, and legal policies are often detailed and hard to understand.
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and references that are important to the document’s purpose. Rather than just performing surface-level analysis, the system aims to understand the contextual meaning of legal statements, which helps in clearly identifying significant legal
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