Company Performance Metrics
Paralleliq is the model-aware optimization layer for GPU inference teams.
Our open-source scanner (piqc) detects waste across Kubernetes clusters — idle GPUs, tier misplacement, OOM risk, KV cache pressure, and CPU:GPU imbalance. Our control plane gives operators one place to surface recommendations, approve remediations, and maintain an immutable
audit trail across the entire fleet.
GPU inference clusters waste 30–70% of their capacity. Existing monitoring tools see the symptoms. None of them fix it. Paralleliq closes the loop — from detection to approved, audited execution — without ever acting autonomously.
Why Paralleliq:
Open-source scanner (piqc) — runs on any Kubernetes cluster, first findings in under 5 minutes, no agents required Human-in-the-loop by design — every remediation requires operator approval. Nothing executes autonomously. SOC 2 ready — immutable audit trail records who approved what, when, and what changed Kubernetes-native — OpenShift, EKS, GKE, on-prem. No vendor lock-in. Inference-aware rules — model-specific waste patterns that generic tools miss entirely Multi-cluster fleet view — manage and govern across your entire GPU footprint
Paralleliq is an NVIDIA Inception Program member headquartered in San Francisco, CA.
