en.Wedoany.com Reported - The Korea Open Source Association (KOSSA) held the "2026 KOSSA DAY" event on the 8th, aiming to establish a communication platform, expand the open source base, and build an industrial ecosystem.

The event focused on strengthening supplier collaboration and mutual support amid the trend of open source AI transformation (AX). Over 20 open source specialized companies, including Samsung Electronics, CUBRID, and Liwon Ace (리원에이스), participated to share technical and business experiences. Leaders from major communities such as Kubernetes, OpenInfra, PyTorch, and OpenSSF also attended. Newly joined companies from the "Open Source AI·SW Development and Utilization Support Project" supported by the National IT Industry Promotion Agency (NIPA) also participated, broadening the scope of ecosystem exchange. Subsequently, meetings between open source AI demanders and suppliers will continue at the "K-Open Source AX" conference, held annually in a major Asian megacity and Seoul, scheduled for October 28th.

Association Chairman Jang Il-soo stated that open source is a key foundation for the AX era, and through KOSSA DAY and K-Open Source AX, a collaborative ecosystem for the mutual growth of businesses, communities, and the public sector will be fostered.

ThinkforBiel (씽크포비엘) has launched a project to establish credibility standards for the Korean National Police Agency's public safety AI. Following its selection last month as the research execution agency for the policy task "AI Impact Assessment and Risk Management Plan Development," the company officially began the project this month, with plans to complete it by the end of this year.

During the project execution period, ThinkforBiel will conduct surveys on domestic and international policies and organizational status, perform impact assessments on AI projects and services introduced by the National Police Agency, establish AI risk management policies, define the risk management organizational system and roles and responsibilities, and implement measures to ensure safety and reliability along with documentation work. The project is based on the "AI Basic Act" and the "Public AI Act," while also incorporating the specific characteristics of public safety field operations to concretize procedures for impact assessment, risk management, transparency, human oversight, and documentation obligations.

The work will maintain consistency with domestic and international standards, including guidelines related to Korea's AI Basic Act, OECD policy directions, the EU's "AI Act," and ISO/IEC international standards. Company representative Park Ji-hwan stated that public safety AI cannot be subject to technical review solely based on performance, and this project will establish a system and standards for the National Police Agency that can be repeatedly applied in the field of public safety.

Selpasoft (셀파소프트) and Altibase (알티베이스) have signed a Memorandum of Understanding (MoU) for AI-based database management technology cooperation. The two parties will integrate Altibase's high-performance hybrid DBMS with Selpasoft's AI performance management solution "Selpa AI" to jointly build an AI-integrated database operation environment covering database performance analysis to SQL tuning.

Through this collaboration, AI functions will be embedded across all Selpa products, including the Altibase database. Altibase customers will be able to leverage AI to automatically analyze database performance, diagnose issues, and propose improvement plans, enabling even personnel without extensive operational experience to understand performance data and respond accordingly.

Enhance (인핸스) shared business methods for supporting public sector AI transformation at a seminar hosted by the National Information Society Agency (NIA). The company's Product Team Leader, Ahn Hyun-jin, focused on presenting AI Agent workflow design, ontology-based data structuring techniques, and practical industry application cases. Specifically, he introduced techniques for structuring data from complex business environments using ontologies to help AI accurately recognize and execute tasks, along with examples of applying this technology in industrial settings.