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AI-BASED LEGAL ASSISTANCE AND DOCUMENT SIMPLIFICATION SYSTEM: A CASE STUDY ON SECTIONWISE

Anuj Bopche, Vaishnavi Naktode, Kshitij Telami, Sangameshwar Muskawad, Ritesh Karpe

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Paper Contents

Abstract

SectionWise is developed to address the growing challenges faced by citizens in understanding Indias complex legal framework. Legal documents, statutory provisions, and procedural requirements especially those under the IPC and CrPC are often written in technical language that is difficult for individuals without legal expertise to interpret. This complexity limits legal awareness and creates barriers for people attempting to make informed decisions. The problem becomes more severe in rural areas, where legal assistance is scarce, consultation costs are high, and access to timely legal guidance is limited. Advancements in Artificial Intelligence (AI) and Natural Language Processing (NLP) offer effective solutions to overcome these obstacles. AI-enabled systems can interpret user queries, simplify complex legal text, and retrieve relevant legal sections, thereby making legal information more accessible and understandable. Leveraging these technologies, SectionWise is designed as an AI-powered legal assistant capable of providing instant legal guidance, suggesting appropriate IPCCrPC sections, and simplifying essential legal documents. The system integrates NLP models, a structured legal knowledge base, and a user-friendly interface to enhance the clarity and accessibility of legal content. This study presents the design, implementation, and evaluation of SectionWise.

Copyright

Copyright © 2025 Anuj Bopche, Vaishnavi Naktode, Kshitij Telami, Sangameshwar Muskawad, Ritesh Karpe, Prof. Shrikant Zade. This is an open access article distributed under the Creative Commons Attribution License.

Paper Details
Paper ID: IJPREMS51100078119
ISSN: 2321-9653
Publisher: ijprems
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The International Journal of Progressive Research in Engineering, Management and Science is a peer-reviewed, open access journal that publishes original research articles in engineering, management, and applied sciences.

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