Your AI assistant for Ruckos Cloud — a context-aware assistant that integrates AI into your Private cloud and management dashboards for use with local models on GPU accelerated hardware.
Serve LLMs and inference endpoints through the same declarative GitOps flow as your apps — commit a manifest, ArgoCD syncs it live. No bespoke MLOps stack to maintain.
Kubernetes schedules GPU workloads onto the right nodes with resource limits and isolation built in, so training and inference share the cluster without stepping on each other.
Run models on your own infrastructure — on-prem, cloud, or edge. Data never leaves the cluster, traffic is encrypted with Cilium eBPF, and runtime is watched by Tetragon.
Prometheus, Grafana, and Loki give you latency, throughput, and cost visibility across every model endpoint — the same observability stack that covers the rest of your platform.
Ruckos meets you where you are — from a quick answer to a fully executed task.
Ask a question and get an answer with context, and links back to the relevant dashboards, docs, or resources.
Ask it to handle the task and it will — executing directly against the platform, scoped to what you've asked for.
Hand it off to a teammate, assign it to the SOC. Ruckos routes the task and keeps context attached, so nothing gets lost in translation.
Ruckos the platform assistant.
Ruckos watches the cluster around the clock — preventing chaos before it happens. All nodes on the cluster are monitored, and every event is correlated to detect anomalies, map them to MITRE ATT&CK techniques, and alert the SOC with recommended remediation. We remove layers of software and complexity from the security stack, and replace them with a single, unified AI-powered platform that intercepts at the kernel level, and if given the authority acts on the cluster in real time.