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Use cases / 01–04

Infrastructure.
In operation.

Four workflows across the distributed AI estate.

/01

Recover a known failure.

A VM or service stops responding.

Propose a supported recovery, authorize the action and check fresh service health.

/02

Validate a change before rollout.

A firmware, configuration or workload change is proposed.

Evaluate the supported change against a model and constraints before an approved rollout.

/03

Place workloads under policy.

An AI workload needs execution capacity.

Select a permitted destination, authorize execution and record usage.

/04

Find what limits GPU capacity.

Demand grows or a workload slows.

Investigate constraints and review a capacity recommendation before any operational change.

Illustrative operating scenarios based on the Invences portfolio. Integrations and operating boundaries depend on the deployment.

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