AI Factory
Input: power + GPUs. Data centers manufacture intelligence, not just host applications.
The AI Factory
Operating Platform
Chthonia turns multi-IDC GPU infrastructure into an AI Factory Operating Platform: the enterprise control plane that makes GPU capacity self-service, governed, observable, billable, and optimizable. It connects GPU infrastructure, AIDC operations, AI platform teams, SRE, and FinOps into one layer that turns raw compute into revenue-aware AI production capacity.
35.8%
GPUaaS Market
CAGR 2025–2032
CAGR 2025–2032
$49.84B
GPUaaS Market
by 2032
by 2032
The economics
Compute Is the New Revenue Line
Jensen Huang's COMPUTEX framing is now an operating reality. A data center no longer just hosts applications; it manufactures intelligence. Power and GPUs go in; tokens come out. Throughput, uptime, and performance-per-watt become financial levers.
AI Token
The production unit: training, inference, and agents are measured and monetized in tokens.
Compute Is Revenue
KPIs shift to tokens/sec and tokens/watt; throughput and efficiency per watt become financial levers.
Enterprise Mandate
Operate compute like a revenue-generating production line: more tokens at a lower cost per token.
The operations gap
Where the AI Factory Leaks Capital
In a CapEx-heavy AI factory, every week without an operating layer is depreciation, power, and idle capacity running at full cost while token output stays at zero.
Chthonia closes the gap between raw GPU capacity and a revenue-operating AI factory.
UNBILLED
Capacity & Lead Time
GPU supply fragmentation and long onboarding cycles mean capacity sits idle while teams wait.
SLOW MTTR
Operational Complexity
Multi-DC, multi-cluster GPU, network, and storage dependencies slow incident response and recovery.
NO ROI
Low Utilization & Cost Opacity
Idle GPUs from weak quota controls, no chargeback model, and no way to prove ROI per token.
DEBT
Governance & Security
Tenant isolation, RBAC, and audit must be standardized from day one, not retrofitted later.
What Chthonia is
Beyond IaaS. An AI Factory Operating Platform
An enterprise platform that turns GPU infrastructure into governed, observable, resilient, and revenue-aware AI production capacity. Chthonia is not just IaaS. Not just monitoring. Not just billing. It connects all three into a revenue-operating control plane.
L4
AI Factory Token Economics
Billing & CostToken OutputTenant MarginROI Analytics
L3
AI Workload SaaS Layer
MonitoringFault ToleranceRDMA Snapshot
L2
IaaS Compute Services
Container ServicesBare MetalQuota & SchedulingGovernanceRBACService Portal
L1
Resource Integration
IDC / ClusterGPUStorageNetworkIB VPC
The operating loop
Operate Compute as a Profit Engine
One closed-loop workflow from capacity planning to token economics. Every stage feeds the next.
Plan
Capacity forecast and AI-agent recommendations.
Allocate
Tenant / project quotas and IB VPC policy.
Run
Container / bare-metal scheduling and resilience.
Observe
Tokens/sec, GPU utilization, NVLink / RDMA health.
Optimize
Cost/token, chargeback, and ROI improvements.
AI Token Output
tokens/sec · tokens/watt
GPU Revenue Yield
utilization × reserved ratio
Cost Discipline
cost/GPU-hour → cost/token
Governed compute = monetizable AI production capacity.
Platform capabilities
Three Modules, One Governed Platform
The economics and operating loop above run on three productized capability modules, delivered today and expanding through 2027, unified on a shared control plane with monitoring, RBAC, billing, and AIOps.
Self-service GPU Cloud Workflows
GPU bare metal and container services with organization and project governance, quota controls, and service portal visibility. Purpose-built for AI platform teams running multi-tenant workloads.
- GPU instances: bare metal & container services
- Multi-tenant org / project / department hierarchy
- Quota, scheduling & policy controls
- Monitoring, telemetry & alerting
- Workflow / BPM automation
- Chargeback / showback data foundation
Organization Management
Resource Quota
Multi-tenant
3-tier Governance
Service Portal
RBAC & Admin Controls
Operations Designed for Real Datacenters
Monitoring, alerts, logs, workflow automation, help desk ownership, and SLA-ready service management. Designed for operations teams managing complex, mission-critical GPU infrastructure.
- Help desk & ticketing with SLA management
- Automation backend & runbook management
- Unified incident response workflows
- AI agent–assisted maintenance support
- Operational log correlation & audit trail
- Multi-IDC health monitoring dashboard
Monitoring Dashboards
Alerts & Logs
Workflow / BPM
IDC Management
Governance and Business Visibility
Asset lifecycle tracking, infrastructure inventory, cost visibility, chargeback-ready data, and audit-friendly controls. Gives both engineering and leadership the transparency needed to govern AI capacity.
- Asset lifecycle tracking & infrastructure inventory
- Business dashboards & executive reports
- Cost visibility by org / project / resource type
- Chargeback & showback configuration
- AI agent assistant for ops insights
- Audit-friendly access & compliance controls
Billing Configuration
System Configuration
Asset Lifecycle
BI Reporting
Revenue intelligence
From Tenant Usage to ROI,
One Operating Model
Chthonia translates technical telemetry into the financial language of the AI factory, so management, tenants, and operators read the same numbers.
Management View
Is cost recovered by tenant and project? Which workloads create token value? Where is revenue at risk?
Tenant View
Do rented GPUs fit the token budget? Is quota right-sized? Are checkpoints protecting training cost?
Unit Economics
Tokens/sec · cost/token · GPU utilization · workload reliability · tenant margin.
AI Factory KPIChthonia Signal
Token throughputAI Job Monitor — tokens/sec, queue, running state
GPU utilizationExecutive Overview + GPU Fleet — reserved ratio, idle GPUs
Cost per tokenTenant & Billing — cost/GPU-hour, ARPU, chargeback
Uptime / reliabilityNVLink / NCCL / RDMA health, checkpoint success
Demand growthAI Agent insights + capacity forecast + quota signals
Tokens/sec × uptime × utilization = productive AI output
Output − GPU-hour cost = AI factory margin
Workload resilience
A Resilient Runtime for
Long-Running AI Jobs
A runtime layer that keeps long training and inference jobs alive, and keeps GPU-hours productive, without user-side code changes.
Fault Tolerance
- Auto-create redundant containers on separate nodes
- Redistribute traffic on NVLink / NIC path failure
- Container and bare-metal support
Snapshot & RDMA Checkpoint
- Capture RDMA state and metadata at runtime
- Policy-based checkpoint backup and retention
- No user-side code changes required
Workload Monitor
- Track job throughput, NVLink health, RDMA latency
- Correlate fault events, failover, and checkpoints
- Operational dashboard for SRE / AIDC teams
Lower Interruption Risk
Faster Recovery
End-to-End Visibility
Stronger AIDC Control
Deploy & integrate
Deploy Anywhere,
Governed the Same Way
Private Cloud
For enterprise AI factories, sovereign AI, and regulated data environments that require dedicated control and on-premises performance.
Public / Managed Cloud
For GPU cloud providers and internal marketplaces that need billing, SLA management, and multi-tenant governance at scale.
Hybrid + Multi-Cluster
For multi-site expansion, global R&D, planned burst capacity, and unified monitoring across regions and deployment boundaries.
ExperienceAdmin Console · Service Portal · API & Integrations
Control PlaneRBAC · Quota · Inventory · Monitoring · Billing · Policy & Audit
Data Plane · NCP / SuperPODGPU Clusters · Bare Metal · Storage · Network across IDCs
Secure by architecture: per-tenant VPC isolation and IB VPC preserve full RDMA performance. Integrates with Kubernetes, OpenStack, observability backends, and NVIDIA NCP / SuperPOD. Full architecture, VPC, and compliance depth on the Technology page (coming).
Product roadmap
Shipping Now. Scaling Forward
GPU cloud first, then full datacenter ops, then enterprise asset management. Each phase builds on a shared, production-grade architecture.
2026 — Available Now
LIVE
GPU Cloud Service
- Core GPU cloud (Q1 2026)
- Enhanced governance & quota
- Full multi-IDC + AI agent
- Marketplace & Job Scheduler
- NVIDIA NCP / SuperPOD integration
H1
2027 H1 — Coming
COMING
AIDC Ops & Maintenance
- Full Datacenter ITSM module
- AI agent maintenance support
- Automated runbook execution
- SLA tracking & incident management
- Multi-IDC health monitoring
H2
2027 H2 — Planned
PLANNED
Asset & Cost Management
- Enterprise BI & Asset module
- Full asset lifecycle tracking
- Chargeback & showback reporting
- Executive BI dashboards
- Private Cloud Operation suite
See Chthonia in Action
Tell us your infrastructure scale and operational goals. We will walk you through a reference deployment and show you how Chthonia maps to your environment.
Chthonia. Powering AI from the ground up.