en.Wedoany.com Reported - Yuracl (represented by Cho Jun-hee and Kwon Tae-il) announced on the 3rd that it has won a project under the "2026 AI Application Product Rapid Commercialization Support Project (Environment)" managed by the Korea Environmental Industry & Technology Institute (KEITI), an affiliate of the Ministry of Climate and Energy Environment. The project is titled "Empirical Verification and Commercialization of a Generative AI Leak Detection Platform Using High-Sensitivity Leak Sensors."
The project will be executed as a consortium with Wiplat (위플랫) as the lead organization and Yuracl as the software development participant. The total project budget is KRW 1.929 billion, with a project period until June 2027, spanning one year. The AI Application Product Rapid Commercialization Support Project aims to apply artificial intelligence technology to environmental products, services, and systems, selecting and intensively supporting promising projects that can achieve market launch and results in the short term. This project is part of the South Korean government's "AX (AI Transformation) Sprint" initiative in the environmental sector, targeting solutions to on-site environmental issues and upgrading the environmental industry.
Through Wiplat's project, the plan is to use generative AI to analyze data collected by high-sensitivity leak sensors and transform the analysis structure. The core goal is to empirically verify and commercialize an AI platform for leak detection that can identify leak patterns and anomaly signs in sensor data, presenting results in the form of natural language reports and response guidelines that operators can immediately understand. Yuracl will develop the platform's core AI module based on its generative AI solution "Athena," utilizing no-code workflow design and high-speed retrieval-augmented generation (RAG) pipelines to achieve an integrated process from real-time sensor data analysis to leak diagnosis report generation and operational decision support.
The two companies plan to improve early leak detection accuracy and reduce the judgment burden on field operators through empirical verification, then promote the technology's deployment to actual operational sites such as local government waterworks offices, aiming to reduce water loss and improve pipeline network operational efficiency. Yuracl CEO Kwon Tae-il stated that the company, which has built and operated mobile legacy systems for numerous manufacturing enterprises, is optimally positioned as a physical AI company. Based on its experience across different industries including semiconductor manufacturing, automotive manufacturing, battery manufacturing, and water resource management, it aims to transform into a leading physical AI enterprise.
