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C-Gen.AI

For Data Centers + GPU Clouds

BETA

Turn physical GPU capacity into an operated AI platform.

Nucleaton™ is extending its control plane from cluster workloads down into data center operations. The beta connects tenant and workload policy to cluster scheduling, node health, and data center management interfaces so operators can improve eligible fleet utilization and build managed AI services from the infrastructure they already run.

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Data Center Control is currently in beta.
Interfaces and supported management systems are expanding.

COMING SOON

One control loop from contract to rack.

A customer contract should become an enforceable resource policy, not a spreadsheet plus manual operations.

From service to physical capacity

Services + contracts

Northbound

Tenantsreserved capacitymanaged traininginferenceagentsquotasSLAs

Nucleaton™ capacity + service control

Admissionplacementpolicyautoscalingreclaim/drainutilizationhealthaccounting

Data center + cluster

Southbound

SlurmRedfish / BMCcomputenetwork/fabricstoragetelemetryhardware state

BETA

Use policy to make more of the physical fleet productive.

Reserved customers, training jobs, inference traffic, and operator-owned services rarely peak at the same time. Nucleaton™ can place eligible workloads into otherwise-unused physical capacity and return that capacity when higher-priority commitments require it.

Not all idle capacity is recoverable. Eligibility depends on topology, workload requirements, service guarantees, maintenance state, and operator policy.

One physical fleet, different demand curves

Physical GPU fleet over time

  • Tenant training
  • Tenant inference
  • Operator backfill

Policy determines which workloads may fill spare capacity and when they must yield.

COMING SOON

Oversubscribe policy, not promises.

When the commercial model allows burstable, interruptible, or opportunistic capacity, Nucleaton™ can use the difference between guaranteed commitments and actual demand to place additional work. Guaranteed capacity remains protected by policy.

Service classes from one fleet
One physical fleetGuaranteed → opportunistic
  • Guaranteed / ReservedProtected

    Protected capacity; not opportunistically consumed.

  • Managed TrainingScheduled

    Priority- and topology-aware scheduled jobs.

  • Production InferenceBurstable

    Baseline plus burstable capacity where permitted.

  • Interruptible / OpportunisticYields

    Uses eligible spare capacity and yields on demand.

Service guarantees determine what may share capacity.

BETA

Idle and spare GPUs can become a service, not dead inventory.

Capacity held for failures, maintenance, burst, or uneven tenant demand does not always need to remain economically idle. Where policy permits, Nucleaton™ can run inference, agents, evaluation, or other reclaimable workloads on that capacity and return it when the fleet needs it.

Physical fleet

  • Committed / active
  • Spare / resilience / burstOperator policy decides eligibility
  • Unallocated / between leases

Capacity held for failures, maintenance, and burst often sits economically idle.

Nucleaton™ policy-controlled use

  • Inference / agent service
  • Evaluation / batch / other reclaimable work
  • Return capacity when protected demand needs itImmediate or graceful reclaim

Where policy permits, it runs reclaimable services and returns when the fleet needs it.

Sell managed AI services, not only GPU-hours.

White-labeling is supported.
Your infrastructure. Your customers. Your service.

  • Managed Slurm clusters
  • Managed training
  • Inference endpoints
  • Private model hosting
  • Agents
  • Tenant resource pools
  • Project/user access
  • Managed storage
  • Health / monitoring
  • Branded experience
BETA

Workload control that understands the data center underneath it.

Nucleaton™’s data center integrations are designed to connect workload decisions to real infrastructure state through interfaces such as Redfish and other management systems. That creates a path from node health and hardware availability to scheduling, remediation, spare-capacity decisions, and service delivery.

Integrations are designed to connect; specific management system support is expanding.

Hardware-aware control loop
  1. Data center stateRedfish / BMChealth • availability • telemetry
  2. Nucleaton™policy • placement • remediationcapacity decisions
  3. Workloads + servicestraining • inference • agentstenant service classes

Runtime + hardware telemetry feeds the next decision.

Full Operator Stack

From customer contract to physical fleet.

Data center operating stack

Northbound

Customers / contracts / APIs

Tenantsreservedburstablemanaged servicesSLA / quota / priority

Managed AI services

Traininginferenceagentsprivate modelsevaluation

Control

Nucleaton™ service + capacity control

Admissionplacementautoscalingpolicyreclaimhealthutilizationaccounting

Southbound

Cluster runtime

Slurmworkload runtimestoragenetwork / fabric

Data center management

Redfish / BMCtelemetryhardware healthlifecycle integrations

Physical infrastructure

Computenetworkstoragepower / facility context

Northbound commercial intent becomes southbound resource behavior.

FAQs

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C-Gen.AI is a turnkey AI infrastructure orchestration platform. Unlike a standard cloud provider, we provide the software layer (Nucleaton™) that automates the deployment, management, and monetization of GPU clusters across any environment—whether on-premise, private cloud, or bare-metal.

Turn your fleet into a managed AI platform.

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At C-Gen.AI, we see ourselves as the connective tissue between model innovation and operational delivery for startups, data centers, and enterprises.

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