Vendor-neutral AI runtime intelligence that correlates GPU silicon diagnostics with LLM inference performance. From DCGM symptoms to root causes — in seconds, not hours.
Existing tools show you utilization percentages and temperature readings. They can't tell you why your inference costs doubled overnight or why token latency spiked for 12 minutes at 3 AM.
DCGM tells you GPU utilization hit 98%. It doesn't tell you whether that's healthy saturation or a memory thrashing loop burning cycles without producing tokens.
GPU metrics live in Prometheus. Inference logs live in your application stack. Cost data lives in spreadsheets. Nobody connects silicon behavior to business outcomes.
Datadog and cloud-native monitoring don't deploy to sovereign infrastructure, on-premise GPU clusters, or air-gapped environments where your most sensitive workloads run.
Ceptua AI connects four layers that have never been unified in a single platform — from silicon physics to business impact.
When your LLM slows down, the problem could be anywhere: a thermal throttle on one GPU die, a KV-cache eviction pattern in your inference engine, a misconfigured batch scheduler, or a memory bandwidth bottleneck. Ceptua traces the causal chain across all four layers to identify the actual root cause — and tells you exactly what to fix.
Lightweight Python agent collects 50+ GPU metrics via DCGM and NVML at sub-second intervals. Deployed as a sidecar with zero inference overhead.
NVIDIADrop-in SDK hooks into vLLM and Triton inference pipelines to capture token generation timing, KV-cache utilization, batch scheduling, and request queuing.
All EnginesPattern-matching engine correlates GPU silicon events with inference anomalies to surface actionable root causes — not just alerts.
CorePurpose-built React dashboard with correlated timelines, GPU topology views, and cost attribution. No Grafana dependency.
CoreThreshold and pattern-based alerts with context. "GPU:3 throttling → 40% latency increase" beats "GPU temperature high."
CoreHardware Abstraction Layer designed for vendor-neutral observability. NVIDIA today, AMD MI300X on the roadmap — same platform, same insights.
Coming SoonEvery component runs inside your perimeter. No data leaves your infrastructure. No cloud callbacks. No vendor lock-in.
Purpose-built for sovereign cloud, on-premise GPU clusters, and air-gapped environments across APAC and the Middle East.
Deploys within national data sovereignty boundaries. No external telemetry egress.
Helm chart or Docker Compose deployment on bare-metal and private cloud GPU infrastructure.
Built with enterprise security requirements as deployment prerequisites, not afterthoughts.
Run alongside existing DCGM installations with zero interference. Validate before committing.
We're onboarding select GPU operators for shadow-mode deployment. Run Ceptua alongside your existing DCGM stack — zero risk, full visibility.