AI Platform
Expanding a Government-Wide Data Analytics System | Ministry of the Interior and Safety
2026.03.16.
Data-driven decision-making is growing more important across the public sector. To improve administrative services, agencies need more than accumulated data—they need analytics environments that turn it into policy and operational insight.
The Ministry of the Interior and Safety set out to upgrade Hyean, its government-wide data analytics system, which had been operated mainly on the internal government network. As demand for public data analytics expanded, the ministry needed a platform that could support not only internal data, but also internet-based social network analysis, online data analysis, and standard analytical models.
To this end, the ministry adopted Mondrian AI's Yennefer Cluster—an AI data analytics platform that enables multiple users to store, share, and collaborate on analysis results. This allowed the ministry to advance public-sector data management and strengthen the analytical foundation for evidence-based policymaking.
■ A Platform That Expands Beyond the Internal Government Network
Hyean had long served as the government-wide analytics system, but rising demand called for support across more data types and environments. Public policy benefits from multi-dimensional analysis when administrative data is combined with external sources—online sentiment, social networks, and citizen inquiry flows.
Yennefer Cluster was chosen to meet this need. By extending the analytics framework beyond the internal government network to the internet, the ministry built a broader environment that includes social network and online analysis. Public agencies can now identify policy issues faster and apply more refined analytical results to their work.
■ An Analytics Environment for Evidence-Based Policymaking
Public-sector analytics must go beyond statistics to drive policy decisions and service improvements. When each department can analyze data on its own, field expertise and data-driven decision-making come together.
Yennefer Cluster gave agencies a systematic analytics environment. By unifying collection, analysis, storage, and sharing on one platform, administrative bodies can apply more accurate and timely results to policymaking.
This strengthened the ministry's evidence-based policymaking environment. Analytical results now provide empirical grounding for decisions and inform both policy direction and service improvements.
■ A Data Sharing Framework That Strengthens Inter-Agency Collaboration
Public data analysis often involves multiple departments and agencies. When data is fragmented or results are hard to share, both efficiency and analytical quality suffer.
Yennefer Cluster offers data storage and sharing features optimized for multi-user environments. The ministry and related agencies can now manage data more systematically and use analytical results in collaborative work.
This collaboration framework strengthens information sharing across agencies and improves data management and utilization. Each agency builds its own analytical capabilities while sharing results and experience through a common platform.
After adopting Yennefer Cluster, the Ministry of the Interior and Safety expanded Hyean's analytical scope and advanced its public data utilization framework. With improved data accessibility and analytics efficiency, public agencies can use data faster and more accurately—strengthening the empirical basis for policymaking.
This case shows that Yennefer can serve not only private-sector AI R&D environments, but also as a platform for advancing public-sector analytics. Through Yennefer Cluster, Mondrian AI helped the Ministry of the Interior and Safety strengthen its data-driven administrative capabilities and deliver better public services.
