Risk Detection in Supply Chain Management using AI

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Risk Detection in Supply Chain Management using AI

Use Case Description

We propose an AI-powered system leveraging automation and advanced analytics to manage real-time emergencies like fires and earthquakes in supply chain management. Predictive analytics forecasts disruptions, while AI models trained on real-time Twitter data provide geographic alerts, identifying and categorizing threats from user content. This enables swift hazard mitigation and reduced downtime. A centralized dashboard ensures real-time visibility and actionable insights, empowering proactive decision-making to safeguard operations and enhance resilience in critical situations.

AS-IS WORKFLOW, TO-BE WORKFLOW

UiPath Hyperhack 2024_SS_AI_Champs.pdf

Other information about the use case

Industry categories for this use case: Customer Service, Logistic

Skill level required: Advanced

UiPath Products that were used: UiPath Studio, UiPath Orchestrator, UiPath Process Mining

Other applications that were used: MYSQL, AZURE, Third party AI Models

Other resources: Have shared in the pdf

What is the top ROI driver for this use case?: Accelerate growth and operational efficiency

1 Like
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Well done Suraj and Dinshaw ! Thank you both for sharing, it sounds like an interesting case here. There is indeed a problem to be solved, however, I do wonder whether this proposed solution is sufficiently composed to solve the said issue.

a. I would propose you look at the the input?
Is Twitter or X alone the only trigger for noting an event ( natural disaster)?
What other inputs can be leveraged and further how do you validate the X tweets to
ensure that you are not executing remedial action on false/ inaccurate tweets?

Wishing you both well.