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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63697
Volume:
10 |
5 |
May 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Software Engineering
Vivekananda Global University
Law
Vivekananda Global University
Software Engineering
Vivekananda Global University
Management
Vivekananda Global University
Foreinsic Science
Vivekananda Global University
Computer Science and Applications
Vivekananda Global University
Honestly, getting legal help is a headache for most people - I've noticed this in my family as well. Some time ago, my uncle got a legal notice but didn’t understand what it meant or what to do next. This situation is very common in India. Many people have minor or simple legal problems but do not know where to turn for help. Hiring an attorney can be expensive, and free legal services are often too far away or too crowded. This project is based on this problem. As part of my Bachelor of Technology (BTech) studies, I built a chatbot that tries to make legal information accessible. Chatbots use plain language to understand what people are asking and then provide clear and understandable answers. I use Python to build the backend and libraries like spaCy and NLTK to process the script. For questions that the system does not recognize, connect to the LLM API to check the answer. During the inspection, the chatbot can answer a variety of common legal questions, such as tenant issues, payroll issues, and consumer complaints. Of course, it is not replacing the lawyer, and this is obvious to the client. Rather, it helps people understand their situation and decide whether they need professional legal help. Even this small step can make a big difference.
KEYWORDS
The project grew out of a simple observation: legal aid is still inaccessible to many ordinary people—a problem that technology can address to some extent. The chatbot developed as part of this project is not a comprehensive solution; It has real-world limitations and certainly does not act as a substitute for a qualified legal expert. However, it can achieve one significant thing: it can give people a starting point. Understanding the nature of your own legal issues, knowing the laws that apply, and being informed about your rights in certain situations are of the utmost importance. These factors can determine whether a person decides to fight for their rights or succumbs to an unfair situation. From a technical perspective, the project demonstrates how Natural Language Processing (NLP) and Large Language Model (LLM) tools can be integrated in practical and easily accessible applications. The hybrid approach used proved to be effective during testing, and the system successfully handled many common queries. With further improvements in areas such as multilingual support, real-time data integration, and document clarification, the system can turn into an invaluable tool for raising legal awareness in India.
[1] A. J. Sandefur, "Access to What?" Daedalus, vol. 148, no. 1, pp. 49–55, Jan. 2019. [2] J. Brownsword, E. Scotford, and K. Yeung, The Oxford Handbook of Law, Regulation and Technology. Oxford, UK: Oxford University Press, 2017. [3] N. Aletras, D. Tsarapatsanis, D. Preoiuc-Pietro, and V. Lampos, "Predicting judicial decisions of the European Court of Human Rights: A natural language processing perspective," PeerJ Comput. Sci., vol. 2, p. e93, 2016. [4] Y. Feng, "Legal question answering using structured knowledge and neural networks," in Proc. ACL 2018 Student Research Workshop, Melbourne, Australia, Jul. 2018, pp. 26–32. [5] T. Brown et al., "Language models are few-shot learners," in Advances in Neural Information Processing Systems (NeurIPS), vol. 33, 2020, pp. 1877–1901. [6] M. Quaresma and T. Goncalves, "Using NLP techniques in a question/answer system in the legal domain," in Proc. 1st Workshop on Automated Legal Text Processing (ALTP-2006), 2006, pp. 1–8. [7] R. Dale, "Law and word order: NLP in legal tech," Nat. Lang. Eng., vol. 25, no. 1, pp. 211–217, 2019.
Publication Date
5/22/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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