Bare Metal · Private Cloud · Agent-Native · Full-Stack

Complete End-to-End
AI Infrastructure Stack

From dedicated bare metal GPU infrastructure to production-ready autonomous agents — a complete AI platform, entirely within your environment.

Running AI at enterprise scale requires control at every layer.

Most enterprises are running AI on a patchwork — public cloud compute here, external APIs there, tools that don't talk to each other. Every seam is a cost, a risk, or a performance loss. For the first time, all five layers are available from a single provider, fully integrated and fully within your perimeter.

Layer 0

Velox|Bare Metal Cloud

The compute foundation. No compromises.

Dedicated physical servers with zero hypervisor overhead. Up to 18 PFLOPS FP32 per node on NVIDIA HGX B200 × 8 — provisioned in minutes via API, not days. When the rest of the stack needs raw GPU power, Velox is what it runs on.

Bare MetalZero Noisy NeighborKubernetes-NativeInfiniBand NDR
Layer 0

Telox|AI Native GPU Cloud

GPU infrastructure to AI operations — as a single cloud.

NVIDIA H200 · B200 · B300 infrastructure, Kubernetes-native runtime, Kueue-based GPU scheduling, Metis LLMOps/MLOps, and Signium governance. For teams that need the complete AI workload environment, not just bare metal.

AI Native GPU CloudNVIDIA H200 · B200 · B300Kueue GPU SchedulingMetis LLMOps/MLOps
Layer 1

Aegis|Private Cloud

Your cloud, inside your perimeter.

VM, Bare Metal, and Kubernetes — unified in a single private cloud platform. Enterprise AI workloads run on infrastructure you fully control, with predictable costs and no exposure to public cloud variability. TCO break-even in approximately 8.2 months versus hyperscalers.

On-PremisesVM · Bare Metal · K8sPredictable TCOCSAP-Ready
Layer 2

Metis|MLOps Platform

Your GPU investment, fully utilized.

A Kubernetes-native AI operations platform that manages distributed GPU/xPU resources, automates training and fine-tuning pipelines, and runs serverless inference — all within your infrastructure. GPU utilization above 75%. The entire AI lifecycle on one platform.

xPU SchedulingServerless InferenceOn-Prem Fine-TuningMLOps Automation
Layer 3

Praxis|AI Agent Platform

Autonomous agents that never leave your walls.

Build and operate multi-agent workflows on your internal data — without external API dependencies. Hybrid RAG engine, MCP Tool Hub, and full AgentOps audit trails. Token costs reduced by up to 75% versus external API-based approaches.

On-PremisesLow-CodeAgentOpsMCP-Native
Control Plane

Signium|Unified Control Plane

One control plane across every layer.

IAM, audit logs, security, KMS, alerts, and Cloud Builder — unified across Aegis, Metis, and Praxis. Deploying a cloud and controlling one are different things. Signium is what makes the difference.

IAM · RBACAudit TrailKMSCloud BuilderWorks with: Aegis · Metis · Praxis

The full stack, measured at every layer.

18 PFLOPS

FP32 compute per node — NVIDIA HGX B200 × 8, zero hypervisor overhead

Velox / Telox
Up to 20%

Performance reclaimed by removing the hypervisor layer

Velox / Telox
~8.2 months

Average TCO break-even vs. hyperscalers

Aegis
75%+

GPU utilization achieved with xPU scheduling optimization

Metis
Up to 75%

Reduction in external token costs when running agents on-prem

Praxis
0

External API dependencies when operating fully within your perimeter

Platform-wide

Thaki Cloud Full-Stack Architecture
One stack. Designed end to end.

Most enterprise AI environments are assembled from parts — compute from one vendor, infrastructure from another, tools from a third. Every boundary between them is a gap in performance, security, or control. Thaki Cloud's architecture was designed without those gaps: from bare metal GPU compute through private cloud infrastructure, AI operations, and autonomous agents, every layer is built to work with the one above and below it — and governed by a single control plane, Signium Unified Control Plane, across all of them.

Praxis · Autonomous Agent Platform

Build and operate multi-agent workflows on your internal data without external API dependencies.

Metis · MLOps Platform

Kubernetes-native AI operations platform managing distributed GPU/xPU resources, training pipelines, and serverless inference.

Aegis · Private Cloud

VM, Bare Metal, and Kubernetes unified in a single private cloud platform with predictable costs.

Velox · Bare Metal Cloud

Dedicated physical servers with zero hypervisor overhead.

Telox · AI Native GPU Cloud

Full-stack AI-Native GPU Cloud from infrastructure to AI operations.

Data Center — Private / Dedicated

Private / Hybrid AI cloud infrastructure customizable to customer environments.

Ready to own
your AI infrastructure?

From bare metal to agents — one integrated stack, one provider, fully within your perimeter. Talk to a Thaki Cloud solutions architect about the configuration that fits your workload.

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