International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 11 Issue: 07 | July 2024
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p-ISSN: 2395-0072
AI & ML Based Legal Assistant Drashti Shah1, Jai Vasi2, Tanik Gandhi3 1Drashti Shah 2Jai Vasi
3Tanik Gandhi
Prof. Kanchan Dabre Department of Computer Science Engineering (Data Science) Dwarkadas J Sanghvi College of Engineering ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract - The use of Artificial Intelligence (AI) and 1.2 Motivation Machine Learning (ML) in legal assistance has gained significant attention in recent years. This paper explores the application of AI and ML techniques to aid in the analysis and interpretation of loan and employment contracts. Specifically, we focus on gap resolution strategies to handle diverse document formats and semantic understanding for accurate inference.
The motivation behind this research stems from the recognition of the time-consuming and complex nature of legal contract review processes. By automating these tasks, we aim to significantly reduce the burden on legal professionals, ultimately saving both time and money for businesses. Legal professionals often spend countless hours reviewing contracts manually, a tedious and errorprone process. An automated system could streamline this endeavor, allowing them to focus on more strategic and high-value tasks.
This research paper introduces a novel community-based legal advice platform designed to address these challenges by leveraging advanced natural language processing techniques. Our platform enables users to connect with experienced legal professionals for personalized advice and guidance on a wide range of legal matters.
Moreover, the integration of statistical figures and data specific to the Indian legal landscape can enhance the app's value proposition. Incorporating legal precedents, case law, and market trends can provide users with comprehensive insights, enabling more informed decision-making processes. Automation can also help mitigate the risk of human error in contract review, ensuring a higher degree of accuracy and consistency.
1. INTRODUCTION The legal domain has traditionally been a labor-intensive field, relying heavily on manual processes, extensive documentation review, and rigorous analysis of complex information. However, recent advancements in artificial intelligence (AI) and machine learning (ML) technologies have opened up new possibilities for streamlining and enhancing various aspects of legal operations. This research explores the development of an AI-Based Legal Assistant tailored specifically for courtrooms and legal professionals, aiming to introduce automation and intelligence to court-related tasks.
Furthermore, many individuals face barriers in accessing legal services due to the associated costs and complexities. Our proposed app, catering to both legal professionals and common users, has the potential to bridge this gap, making legal assistance more accessible and affordable. In the subsequent sections, we will delve into the methodology, design considerations, and implementation details of our AI-Based Legal Assistant, highlighting its innovative features and the potential impact it can have on the legal landscape.
1.1 Background We aim to develop an AI-Based Legal Assistant for the operations of courtrooms and legal professionals. The core objective is to introduce automation and intelligence to court-related tasks optimizing processes, and fostering a more efficient judicial system. Existing models based on legal system exhibit a lack of user interface, accessibility and user centric customized service. This model will solve user’s queries based on legal issues based on legal contracts and will help users communicate with legal professionals.
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2. Literature Survey 2.1 Analysis of Literature Survey Numerous studies have explored the application of natural language processing (NLP) and artificial intelligence (AI) techniques in the legal domain. This section provides an overview of relevant research papers, highlighting their contributions and findings.
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