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An AI-Driven Framework for Simplifying Marathi Legal and Commercial Contracts for SMEs

Samrat Ashok Babar, Pallavi Dnyandeo Patil, Vishal S. Pawar

Abstract


Small and Medium Enterprises (SMEs) in Maharashtra often face significant difficulties in understanding complex legal and business documents, mainly because of the use of outdated and highly specialized Marathi language. While English-based NLP (Natural Language Processing) tools for simplifying legal jargon are progressing, regional languages like Marathi remain largely overlooked. This paper presents an innovative NLP-based framework designed to convert complex Marathi legal text into 'Common Man’s Marathi' (Sophi Marathi). By utilizing Transformer-based models and Named Entity Recognition (NER), the proposed system identifies difficult legal terms and provides contextually accurate simplifications or summaries. The research highlights how such a digital solution can enhance legal literacy, reduce dependence on expensive intermediaries, and support business activities in rural and semi-urban areas of Maharashtra. The study concludes that NLP for regional languages is not just a linguistic necessity but a crucial driver for inclusive economic growth in the global business landscape.


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References


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