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Your monitoring sees GPUs. It doesn't see models. Paralleliq is the model-aware optimization layer for AI inference teams. It scans your Kubernetes clusters for waste and risk — idle GPUs, tier misplacement, OOM risk, KV cache pressure, and CPU:GPU imbalance — and routes every recommended fix through your team for approval before anything changes. Nothing executes autonomously. Every remediation requires operator approval. Full audit trail included. Built for GPU cloud providers, inference platforms, and enterprise AI teams running vLLM, KServe, and similar engines at scale. Try the open-source scanner → github.com/paralleliq/piqc
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Joined Product HuntApril 27th, 2026
