Next Generation Legal FIR Analysis: AI-based Summarization and Section Identification
DOI:
https://doi.org/10.31033/IJEMR/16.2.2026.1854Keywords:
FIR Analysis, Legal AI, Semantic Retrieval, Zero-Shot ClassificationAbstract
The increasing number and complexity of first information reports (firs) have made manual legal analysis time-consuming and error-prone. Although firs are essential to criminal investigations, their unstructured format and varied language often make legal interpretation difficult. This paper introduces jurismate, an ai-based system that helps automate the analysis of firs. Jurismate uses the gemini 1.5 language model to extract and structure important details from fir documents and applies a bart-based zero-shot classification method to determine whether an fir is lawful, unlawful, or unclear without requiring labeled data. To support legal research, the system uses semantic embeddings stored in pgvector to retrieve relevant laws and past cases based on similarity. Experimental results show that jurismate improves efficiency, ensures consistent analysis, and provides better support for legal decision-making.
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Copyright (c) 2026 Loshini K, Deepasangkini K, Tharun S, K.S. Janu, D.Parameswari
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Research Articles in 'International Journal of Engineering and Management Research' are Open Access articles published under the Creative Commons CC BY License Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/. This license allows you to share – copy and redistribute the material in any medium or format. Adapt – remix, transform, and build upon the material for any purpose, even commercially.
