ZippriZIPPRIAI HUB · RABBIT INDUSTRIES
AI Hub / Spaces, Jobs & Playground
SPACES · JOBS · PLAYGROUND · ENDPOINTS

Move from repository to runnable AI without losing the evidence chain.

Zippri connects application/tool repositories to Space configuration, compute and training jobs, running managed endpoints and an interactive Playground. Runtime configuration does not bypass verification, production authority or provider capacity rules.

AI SpacesGPU jobsAI playgroundmodel inference endpointscale to zero AI
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Public before loginCore information is readable without an account.
Evidence-awareProduct claims follow current verified platform state.
Human authorityHigh-risk actions remain explicitly approval-gated.
End-to-end AI lifecycleBuild, verify, benchmark, deploy and commercialize.

Zippri Spaces

Application and tool repositories can define framework, entrypoint, hardware intent, visibility and scaling preferences. A Space can bind to an existing managed deployment, but deployment verification and production approval stay separate.

Spaces

Repository-backed demo/runtime configuration.

Jobs

Provider-neutral governed compute and training work.

Playground

Interactive testing of running managed endpoints.

Endpoint Profiles

Capacity policy without falsely claiming unsupported provider autoscaling.

Jobs and training

The existing compute fabric tracks queued, approved, running and completed GPU/CPU work with wallet and provider boundaries rather than hiding resource consumption.

Playground

The Playground discovers compatible running deployments and invokes the proven Zippri runtime contract so teams can test an asset without copying endpoint credentials into another application.

Inference profiles

Endpoint profiles persist min/max replica intent, scale-to-zero request, idle timeout, concurrency and request timeout. Actual elasticity is enforced only when the selected provider/runtime advertises that capability.

Common questions about Spaces, Jobs & Playground

Does creating a Space deploy an application automatically?

No. Space metadata is separate from deployment authority. A verified managed deployment can be bound later.

Does Zippri currently claim OpenAI-compatible chat completions?

No. The proven runtime contract is Zippri /v1/invoke unless a provider/runtime explicitly supports another contract.

Can jobs use external GPU providers?

The compute architecture is provider-neutral. Live capacity depends on formally connected and healthy providers.

Related AI Hub topics

AI DeploymentDeploy evidence-bound AI endpoints with provider-owned lifecycle, signed manifests, preview and production gates, health checks and rollback-aware control.GPU CloudPlan and govern rentable GPU capacity for AI training, evaluation and inference with provider connections, job lifecycle, metering and cost controls.AI DevelopmentBuild AI models, AI applications and production systems with one lifecycle for repositories, evidence, benchmarks, GPU work, deployment and governance.AI Model TrainingOrganize AI model training, fine-tuning, checkpoints, GPU jobs, datasets, costs, telemetry and evidence in one governed workflow.AI Product FactoryTurn evidence-backed AI research tools into trusted prototypes, tests, verified packages, immutable repository artifacts and controlled Marketplace drafts.
Zippri separates engineering readiness from external/provider acceptance. Public pages preserve REVIEW and external-gate states instead of presenting unfinished external integrations as live.