AI Infrastructure & Physical AI
Success in AI business begins with the most robust infrastructure.
Core Engineering Competencies
K8s Container & Hybrid PaaS Platform
SUNGWOO HS standardizes and automates applications based on Kubernetes (K8s) and container platforms to ensure rapid deployment and outstanding scalability. Through HPE Ezmeral, a proven global solution, and MANTECH ACCORDION, an all-in-one PaaS optimized for local enterprise environments, we enable stable and flexible operation of diverse enterprise workloads.
- Container-based Architecture: Maximize infrastructure operation speed through application standardization and management automation utilizing Kubernetes standard technology
- Korea-Specialized PaaS Platform (Mantech Accordion): Implement uninterrupted CI/CD deployment and high-visibility monitoring through an all-in-one integrated PaaS environment optimized for Korean enterprise environments
- Global Enterprise Platform (HPE Ezmeral): Provide integrated K8s cluster orchestration across heterogeneous hybrid/multi-cloud environments and high-performance data fabric for AI/ML workloads
Physical AI Intelligent Platform
Applies Physical AI technology to industrial sites, collecting data from physical environments in real time and analyzing and controlling it via AI.
- Sensor and IoT-based real-time data collection and analytics platform
- Customized intelligent control systems for manufacturing, logistics, and defense sectors
- Real-time intelligent response via Edge Computing
HPE PCAI (Private Cloud AI) Solution
SUNGWOO HS, as an official HPE partner, provides an optimal Private Cloud AI environment. It is an integrated solution optimized for developing, training, and deploying high-performance AI models within on-premises infrastructure without public cloud security concerns.
- Enhanced Security: Securely manage critical training data and model assets within internal infrastructure
- Performance Optimization: Guarantee optimal processing speed optimized for AI workloads
- Scalability: Flexibly expand computing and storage resources in accordance with business growth
Time-to-Market
Shorten project timelines by building efficient AI development environments
Cost Reduction
Reduce infrastructure costs through resource optimization and operations automation
Innovation Success
Launch innovative AI services overcoming technical limitations