Run VMs, containers, AI agents, and model services on one unified software-defined platform. Arcfra helps enterprises deploy private AI with full control over infrastructure, data, security, and cost.
Seamlessly integrate AI into existing infrastructure governance with stable operations, flexible scheduling, and auditing.
Retain 100% data sovereignty. Deploy on-premises with strict access boundaries and total compliance.
Break down operational silos. Run traditional apps, legacy VMs, containers, and AI workloads together.
Dramatically lower your infrastructure costs with highly predictable, cloud-free pricing.
AI readiness
AI agents are changing infrastructure requirements. As enterprises deploy more agents, the number of tool calls, context reads, model requests, and business system interactions grows rapidly. Infrastructure must now support elastic resources, secure data access, workload isolation, and end-to-end visibility across agents, applications, and models.
Agentic AI
Every plan, tool call, context read, and model response increases demand on compute, GPU, storage, networking, security, and observability.
Enterprise AI infrastructure needs to support two core scenarios:
AI agents need to access files, tools, APIs, databases, and business systems. This requires reliable compute, high-performance storage, secure networking, permission control, audit trails, and observability across every call path.
Files | Tools | APIs | DatabasesPrivate and public models need to be deployed, served, monitored, and scaled efficiently. This requires GPU resource management, inference engines, AI gateway capabilities, model access control, token usage visibility, and performance monitoring.
Models | Gateway | GPU | ObservabilityAECP + Neutree
Arcfra helps enterprises extend their existing infrastructure into a private AI platform. Instead of building a separate AI stack, organizations can run traditional VM workloads, containerized applications, AI agents, and model services on one unified enterprise cloud infrastructure.
Enterprises get the infrastructure foundation for virtualization, Kubernetes, distributed storage, networking, security, backup, disaster recovery, and unified operations. Your AI workloads gain:
Enterprises get a private Model-as-a-Service platform for deploying, managing, and serving AI models across their own infrastructure. Neutree provides:
Enterprise apps and agents
Arcfra Enterprise Cloud Platform provides the unified infrastructure layer for business applications and AI agents. Enterprises can run VMs, containers, storage, networking, security, and agent-native file sharing in one consistent architecture.
Run VMs, containers, and AI agent workloads on a shared infrastructure platform.
Support concurrent read and write operations, context access, and file sharing for agent workflows.
Apply consistent security policies across VMs, containers, and AI workloads, while tracking call paths, access behavior, and resource consumption.
Provide easy-to-use file sharing and infrastructure capabilities for agent collaboration and enterprise workflow integration.
Model services
Deploy Neutree on Arcfra Kubernetes Engine to build production-grade model infrastructure faster. Enterprises can centralize model access, inference services, GPU resources, and observability across private and public models.
Centralize access to private and public models, including open-source models and external model providers.
Integrate inference engines such as vLLM and SGLang to deliver low-latency, high-throughput model services for long-context and multi-turn AI scenarios.
Manage heterogeneous GPU resources across sites and improve utilization through unified scheduling and GPU virtualization.
Monitor GPU usage, inference performance, call logs, token consumption, and service health for troubleshooting, auditing, and optimization.
Customer Success
ConnectWave, a leading e-commerce solution provider in Korea, needed to support AI-powered consumer and seller services while keeping infrastructure costs under control. By deploying Arcfra Kubernetes Engine, ConnectWave built a unified infrastructure platform for VMs, containers, and AI workloads.
With Arcfra, ConnectWave accelerated AI model training and deployment, improved infrastructure efficiency, and reduced IDC operational costs by 15%.
