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arXiv AI By Fatema Tuj Johora Faria, Mukaffi Bin Moin, Jubayer Al Mahmud, M. F. Mridha, Md. Alam Hossain

LabourCrew: A Multi-Agent RAG Framework for Trustworthy Adversarial Deliberation and Statutory Reasoning over Labour Law

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LabourCrew is a multi‑agent Retrieval‑Augmented Generation (RAG) framework designed for trustworthy statutory question answering in labour law. It introduces three grounding mechanisms: StatuteGraph, an evidence‑exchange ledger, and a calibrated trust gate that controls false‑accept rates. Evaluated on a Bangla Labour Act QA set, LabourCrew achieves a false‑accept rate of 0.081 and higher answer relevancy than existing RAG methods, demonstrating that calibrated abstention is key to auditable legal QA.

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