Mina: A Multilingual LLM-Powered Legal Assistant Agent for Bangladesh for Empowering Access to Justice

2025-11-04

AI Summary

Low-income populations in Bangladesh face persistent barriers to legal aid due to opaque legal language, non-transparent procedures, and prohibitive costs; existing AI tools lack Bangla language support and judicial system adaptation. Method: We propose Mina—the first full-stack legal large language model system designed for low-resource language environments—integrating multilingual embeddings, RAG-enhanced retrieval, chain-of-tool invocation, and context-aware dialogue to deliver a localized, bilingual (Bangla/English) intelligent legal assistant capable of legal information retrieval, reasoning, translation, and document generation. Contribution/Results: Mina achieves the first end-to-end adaptation of legal AI for low-resource languages—from knowledge modeling and inference architecture to real-world deployment. Evaluated on the Bangladesh Bar Council’s three-tier licensing examination, Mina attains 75–80% accuracy—matching or exceeding industry benchmarks—demonstrating robust legal-context comprehension and generation, thereby advancing equitable access to justice.

Technology Category

• Natural Language Processing: (Large) Language Models
• Humans and AI: AI for Accessibility
• Machine Learning: Large Multimodal Models (LMMs)

Application Category

• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Bangladesh's low-income population faces major barriers to affordable legal advice due to complex legal language, procedural opacity, and high costs. Existing AI legal assistants lack Bengali-language support and jurisdiction-specific adaptation, limiting their effectiveness. To address this, we developed Mina, a multilingual LLM-based legal assistant tailored for the Bangladeshi context. It employs multilingual embeddings and a RAG-based chain-of-tools framework for retrieval, reasoning, translation, and document generation, delivering context-aware legal drafts, citations, and plain-language explanations via an interactive chat interface. Evaluated by law faculty from leading Bangladeshi universities across all stages of the 2022 and 2023 Bangladesh Bar Council Exams, Mina scored 75-80% in Preliminary MCQs, Written, and simulated Viva Voce exams, matching or surpassing average human performance and demonstrating clarity, contextual understanding, and sound legal reasoning. These results confirm its potential as a low-cost, multilingual AI assistant that automates key legal tasks and scales access to justice, offering a real-world case study on building domain-specific, low-resource systems and addressing challenges of multilingual adaptation, efficiency, and sustainable public-service AI deployment.

Problem

• Addressing legal advice barriers for Bangladesh's low-income population
• Developing Bengali-language AI legal assistant with jurisdiction-specific adaptation
• Automating legal tasks through multilingual RAG framework for justice access

Innovation

• Multilingual embeddings for legal document retrieval
• RAG-based chain-of-tools framework for reasoning
• Interactive chat interface for legal assistance