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Missions

AI-driven Risk Prediction & Early Warning System
In response to rising industrial complexity and global uncertainty, this project aims to develop an AI-powered system that detects potential risks and provides early warnings before crises occur.
By leveraging multi-source industrial data, the system identifies anomalies, quantifies risk levels, and offers actionable recommendations through Routeway’s proprietary platform, QROX.ai.
By leveraging multi-source industrial data, the system identifies anomalies, quantifies risk levels, and offers actionable recommendations through Routeway’s proprietary platform, QROX.ai.

AI Service PoC Design & Validation Study
This research aims to establish and validate AI Proof-of-Concept (PoC) frameworks tailored to each industry, verifying the technical feasibility and business applicability of AI solutions before full-scale deployment.

AI-Policy Integration & Public Data Utilization Study
This study aims to strengthen the efficiency and implementation capacity of digital transformation
by integrating artificial intelligence (AI) technologies into public data policy frameworks.
The core of the research lies in evaluating the level of public data utilization,
developing AI-driven policy analysis models,
and proposing practical policy strategies to enhance data governance and intersectoral collaboration
by integrating artificial intelligence (AI) technologies into public data policy frameworks.
The core of the research lies in evaluating the level of public data utilization,
developing AI-driven policy analysis models,
and proposing practical policy strategies to enhance data governance and intersectoral collaboration

AI-based Optimization Model for Industrial Productivity
The goal of this project is to develop an AI-powered optimization model that enhances industrial productivity.
Through the integration of predictive analytics, machine learning, and simulation methods,
it establishes a data-driven decision-making system designed to improve efficiency across manufacturing and service sectors.
Through the integration of predictive analytics, machine learning, and simulation methods,
it establishes a data-driven decision-making system designed to improve efficiency across manufacturing and service sectors.

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