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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65090
Volume:
10 |
6 |
Jun 2026
Pages:
1-5
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.
Computer Science and Engineering.
Nutan College of Engineering and Research.
Computer Science and Engineering.
Nutan College of Engineering and Research.
Computer Science and Engineering.
Nutan College of Engineering and Research.
Computer Science and Engineering.
Nutan College of Engineering and Research.
Computer Science and Engineering.
Nutan College of Engineering and Research.
The number of legal documents is growing so fast and this has created a very big need for ways to analyze the legal text that are automatic which can handle a lot of work and get better understanding of the text. The growth of legal databases has created this demand that motivated us to represent this paper JURISYNTH, an intelligence framework that used advanced Natural Language Processing techniques to make the legal documents simpler and easier to summarize and predict legal outcomes, contractual risks with high accuracy and case precedents. A hybrid pipeline integrating lexical simplification and syntactic normalization employed by a proposed system. This system uses a combination of techniques to simplify language make the structure of sentences clear and summarize the documents in a way that combines extracting essential information and generating a summary. This is made possible by models like LEGAL-BERT and LEGAL-PEGASUS. To ensure the summaries are accurate and are based on the context; the system uses Retrieval-Augmented Generation to search for information using vectors which enhances the response of the system. This system also has a module to represent entities in a structured way and a layer that allows human beings to check the results to prevent errors and ensure that the system is reliable especially, in important legal cases. Instead, getting overwhelmed by a 60 - page contract, we get a simple breakdown of what is fair, what is risky and what the fine print actually means. JURISYNTH is a system that provides an easy way to understand and efficiently handle the confidential legal texts and documents to support legal decisions in a reliable way.
KEYWORDS
There is testing of the Jurisynth system to evaluate the effectiveness of it. This is accomplished with the use of "appropriate" types of measures, for summarizing and analyzing legal documents. Since there is no set of legal cases to test the Jurisynth system The testing is conducted using actual case studies which are submitted into Jurisynth system The function that the system performs. is checked to see how It is used to address these actual legal cases.
[1] S. K. Nigam, B. D. Patnaik, S. Mishra, N. Shallum, K. Ghosh, and A. Bhattacharya, “NyayaAnumana & INLegalLLaMA: The Largest Indian Legal Judgment Prediction Dataset and Specialized Language Model for Enhanced Decision Analysis,” arXiv preprint arXiv:2412.08385, 2024. [2] S. K. Nigam, B. D. Patnaik, S. Mishra, N. Shallum, K. Ghosh, and A. Bhattacharya, “TathyaNyaya and FactLegalLLaMA: Advancing Factual Judgment Prediction and Explanation in the Indian Legal Context,” arXiv preprint arXiv:2504.04737, 2025. [3] S. K. Nigam et al., “PredEx: Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts,” arXiv preprint arXiv:2406.04136, 2024. [4] S. K. Nigam et al., “NyayaRAG: Realistic Legal Judgment Prediction with RAG under the Indian Common Law System,” arXiv:2508.00709, 2025. arXiv preprint. [5] V. Parikh et al., “LawSum: A Weakly Supervised Approach for Indian Legal Document Summarization,” arXiv preprint arXiv:2110.01188, 2021. [6] D. Datta et al., “MILDSum: A Novel Benchmark Dataset for Multilingual Summarization of Indian Legal Case Judgments,” arXiv preprint arXiv:2310.18600, 2023. [7] A. Shukla et al., “Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation,” arXiv preprint [8] Y. Huang, L. Sun, C. Han, and J. Guo, “A High Precision Two-Stage Legal Judgment Summarization,” Mathematics, vol. 11, no. 6, p. 1320, 2023. [9] Y. Pallavi et al., “LEGAL AI: An AI-Powered Legal Research and Case Prediction System for the Indian Judiciary,” International Journal of Advanced Research in Computer and Communication Engineering, vol. 14, no. 3, pp. 22–30, 2025. [10] X. Shang, “A Computational Intelligence Model for Legal Prediction and Decision Support,” Computational Intelligence and Neuroscience, vol. 2022, ID 5795189, 2022.
Publication Date
6/17/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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