Why this fit
Teams evaluating AI models, assistants and generative workflows, particularly CI/CD pipelines and security scanning — source available on GitHub.
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Catalogue record
github.com
piqc
Read-only Kubernetes scanner that detects GPU waste in AI inference deployments — idle GPUs, tier misplacement, and unallocated nodes. One c...
Checked Oct 27, 2026Evidence completeness: evidenceREADME refreshed Oct 16, 2026
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Read-only Kubernetes scanner that detects GPU waste in AI inference deployments — idle GPUs, tier misplacement, and unallocated nodes. One command, nothing installed permanently.
Best for
Teams evaluating AI models, assistants and generative workflows, particularly CI/CD pipelines and security scanning — source available on GitHub.
Known limitations
Workflows that require fully deterministic, auditable outputs with no human review step.
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Evidence summary
Known limitations
Workflows that require fully deterministic, auditable outputs with no human review step.
Catalogue confidence
Catalogue data checked Oct 27, 2026.
GitHub-backed record with source-attributed context.
Repository context
Step 1 — Apply RBAC permissions (one-time setup)
GitHub / paralleliq/piqc
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- Catalogue updated Oct 27, 2026
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