AI Powered Legal Advisor Assistant

Access to expert legal advice is often restricted by high costs, limited availability of qualified professionals, and time-consuming processes. The AI-Powered Legal Advisor Assistant addresses these challenges by providing an intelligent, cost-effective, and user-friendly platform for delivering preliminary legal guidance. Leveraging Artificial Intelligence (AI) and Natural Language Processing (NLP), the system interprets user queries presented in natural language and provides tailored responses based on relevant legal statutes, case law, and regulatory frameworks. This assistant integrates advanced machine learning models for text classification, information retrieval, and sentiment analysis, allowing it to continuously improve through user interaction. Its design enables the identification of legal issues and offers support across various legal domains, including contract law, intellectual property, civil rights, and employment law. Legal practitioners benefit from automation of routine tasks such as document drafting and case assessments, while individuals and businesses receive timely insights into common legal matters. The system is developed with a strong emphasis on ethical considerations and legal compliance, incorporating data security measures and clear disclaimers to prevent overreliance on AI-generated advice. Overall, the AI-Powered Legal Advisor Assistant represents a transformative step toward democratizing access to legal services, enhancing the efficiency of legal professionals, and illustrating the impactful application of AI technologies in the legal sector..

Authors

Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2025-04-08
DOI
https://doi.org/10.48175/ijarsct-25044
Primary Topic
Artificial Intelligence in Law
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Powered Legal Advisor Assistant

Ankush M. Sargar, Rohan Surve, Asst. Prof. Punam Bagul, Abhishek Singh et al.
International Journal of Advanced Research in Science Communication and Technology
Artificial Intelligence in Law
article

AI Powered Legal Advisor Assistant

Ankush M. Sargar, Rohan Surve, Asst. Prof. Punam Bagul, Abhishek Singh, Sudhanshu Mohite
article en

Abstract

Access to expert legal advice is often restricted by high costs, limited availability of qualified professionals, and time-consuming processes. The AI-Powered Legal Advisor Assistant addresses these challenges by providing an intelligent, cost-effective, and user-friendly platform for delivering preliminary legal guidance. Leveraging Artificial Intelligence (AI) and Natural Language Processing (NLP), the system interprets user queries presented in natural language and provides tailored responses based on relevant legal statutes, case law, and regulatory frameworks. This assistant integrates advanced machine learning models for text classification, information retrieval, and sentiment analysis, allowing it to continuously improve through user interaction. Its design enables the identification of legal issues and offers support across various legal domains, including contract law, intellectual property, civil rights, and employment law. Legal practitioners benefit from automation of routine tasks such as document drafting and case assessments, while individuals and businesses receive timely insights into common legal matters. The system is developed with a strong emphasis on ethical considerations and legal compliance, incorporating data security measures and clear disclaimers to prevent overreliance on AI-generated advice. Overall, the AI-Powered Legal Advisor Assistant represents a transformative step toward democratizing access to legal services, enhancing the efficiency of legal professionals, and illustrating the impactful application of AI technologies in the legal sector..

International Journal of Advanced Research in Science Communication and Technology
Openalex Percentile: Top 92%
Artificial Intelligence in Law
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AI Powered Legal Advisor Assistant — Ankush M. Sargar, Rohan Surve, et al. · International Journal of Advanced Research in Science Communication and Technology (2025) | TGRS Research Map | TGRS