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. Even under a conservative upper bound, Mina operates at just 0.12-0.61% of typical legal consultation costs in Bangladesh, yielding a 99.4-99.9\% cost reduction relative to human-provided services. 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.

翻译：孟加拉国低收入群体因法律语言复杂、程序不透明及高昂费用，在获取可负担的法律咨询方面面临重大障碍。现有AI法律助手缺乏孟加拉语支持及司法辖区适应性，限制了其有效性。为此，我们开发了Mina——一个针对孟加拉国语境定制的多语言大模型法律助手。它采用多语言嵌入技术与基于检索增强生成（RAG）的工具链框架，实现检索、推理、翻译及文档生成，通过交互式聊天界面提供上下文感知的法律草稿、引证及通俗语言解释。经孟加拉国顶尖大学法学院教师依据2022年与2023年律师资格考试全阶段评估，Mina在初试选择题、笔试及模拟口试中得分75-80%，达到或超越人类平均水平，展现出清晰的逻辑性、语境理解力与严谨的法律推理能力。即使在保守成本上限下，Mina的运营成本仅为孟加拉国典型法律咨询费用的0.12-0.61%，相较人工服务成本降低99.4-99.9%。这些结果证实了其作为低成本多语言AI助手的潜力，可自动化核心法律任务并扩大司法可及性，为构建领域专用、低资源系统及应对多语言适配、效率优化与可持续公共服务AI部署挑战提供了真实案例研究。