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New framework uses multi-agent LLMs for supply chain risk assessment

By PulseAugur Editorial · [1 sources] ·

Researchers have developed AutoMARS, a novel framework designed for the automatic and scalable assessment of supply chain risks. This system utilizes a multi-agent approach, where specialized agents coordinate to plan tasks, employ external analytical tools, and synthesize results for integrated risk evaluations. AutoMARS is built with a multi-domain, multi-agent, and multi-tool architecture, incorporating diverse risk factors such as socioeconomic, disaster, environmental, and transportation data to support informed location-based risk analysis. AI

IMPACT This framework could enhance the efficiency and scalability of risk assessment in supply chains by leveraging multi-agent LLMs.

RANK_REASON The item describes a research paper published on arXiv detailing a new framework. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework uses multi-agent LLMs for supply chain risk assessment

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The item describes a research paper published on arXiv detailing a new framework. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yinzhu Quan, Zefang Liu, Frederick Benaben, Benoit Montreuil ·

    AutoMARS: Automatic and Scalable Multi-Agent Large Language Model Framework for Supply Chain Risk Assessment

    arXiv:2610.17206v1 Announce Type: new Abstract: We propose AutoMARS (Automatic Multi-Agent Risk Assessment), an agentic framework for automatic and scalable comparative risk assessment in supply chain networks. The framework enables end-to-end execution of analytical workflows by…

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