Axe Compute
Axe Compute delivers enterprise bare-metal GPU infrastructure for AI and machine learning workloads with global reach, dedicated clusters, and predictable access. It gives teams dedicated GPU clusters delivered in approximately 48 hours across 200+ locations, with full choice across region, GPU type, fabric, interconnect, and topology. It is built to address the hidden cost of scaling AI: provisioning delays, limited cloud availability, quota rejections, rigid provider economics, data movement costs, and performance loss from virtualization. Axe provides 100% bare-metal access with zero virtualization overhead and no noisy neighbors, helping teams run LLM training, inference, diffusion, fine-tuning, enterprise deployment, and other AI workloads with more control. Its distributed GPU backbone supports low-latency placement near users and data, reducing the need to move data into centralized cloud regions.
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Control Plane
Control Plane is a cloud virtualization platform that enables devops teams to compose any combination of cloud infrastructure (bare metal, VMs, k8s, AWS, GCP, Azure, OCI) into one or more AI-native virtual clouds. Applications run at 99.999% availability, backed by an SLA, without added infrastructure complexity. Organizations use it to cut infrastructure costs by 30–50%, eliminate vendor lock-in, and securely deploy workloads, VMs, and AI agents across single-cloud, multi-cloud, hybrid, and on-prem environments from a single AI-enabled interface. SOC 2 Type II, PCI DSS Level 1, HIPAA, and GDPR compliant.
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edgeContinuum
edgeContinuum is a cloud management platform that adds self-service services to OpenStack infrastructure. Through a web console, API and Terraform, administrators can offer managed Kubernetes clusters, PostgreSQL databases, virtual machines and application templates to internal teams or customer tenants. Multi-tenancy controls include organizations, projects, roles, quotas and usage tracking. The platform organizes data centers and edge sites into regions and availability zones, and automates provisioning and lifecycle tasks for Kubernetes and PostgreSQL. Cloud and managed service providers can use it to deliver branded infrastructure services, while enterprises can offer developers on-demand access under IT governance. The control plane can be hosted or deployed on-premises, including in air-gapped environments, with workloads running on the operator's infrastructure.
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Randoli
Randoli is an OpenTelemetry-native observability and cost management platform for Kubernetes, multicloud, hybrid, and AI/ML workloads. It brings infrastructure health, application performance, logs, metrics, traces, incidents, and cloud costs into one control plane, helping teams replace fragmented tools with a correlated view of system behavior. Its federated architecture separates the control plane from the data plane, analyzes telemetry locally, extracts relevant signals, and retrieves data on demand during investigations, reducing ingestion and egress while supporting data sovereignty. Randoli monitors clusters, nodes, pods, workloads, services, dependencies, latency, errors, throughput, and resource usage across AWS, Azure, Google Cloud, OpenShift, and on-premises environments. OpenTelemetry and eBPF provide automatic, low-overhead instrumentation, filtering, enriched telemetry, and real-time signal correlation.
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