AIBIZ (CEO Ha Seung-jae), a specialist in industrial AI (artificial intelligence), announced on the 9th that it was selected for the 'Stepping Stone' (Didimdol) track of the '2026 Startup Growth Technology Development Program' hosted by the Chungnam Regional Office of the Ministry of SMEs and Startups, and will develop an 'industrial AI system for semiconductor OSAT (outsourced semiconductor assembly and test)'. The 'Startup Growth Technology Development Program (Stepping Stone)' is a government program that supports research and development (R&D) for early-stage technology-based SMEs to secure technological competitiveness and verify commercialization potential. The company was selected for the First Step (Chungnam Regional Office R&D) track. This is a region-specific R&D project operated directly by a regional Office of SMEs and Startups, aiming at field-oriented technology development that reflects local industry characteristics. The project is 'Development of a Deep Learning-Based Real-Time Test Data Analysis and Advanced Packaging Defect Cause Tracing System for Improving Semiconductor Back-End (OSAT) Productivity'. It involves developing AI-based anomaly detection and cause analysis technology tailored to the semiconductor back-end environment. AIBIZ was selected for this project with technology that uses sensor-based time-series data to detect anomalies during processes in real time and automatically analyze their causes. In particular, the company said one of the reasons for its selection was the ability to process the large-scale test data generated in semiconductor back-end processes and to detect and trace defects in packaging processes at an early stage. Ha Seung-jae, CEO of AIBIZ, said, "The back-end is an area where identifying the causes of defects is difficult because of diverse variables and complex data structures," adding, "We were recognized for the differentiator of being able to trace the causes of defects, not just detect process anomalies, based on data." He continued, "Through this project, we will advance the process diagnostic technology needed in the field and contribute to improving semiconductor productivity and quality."