PureTensor Sentinel is an autonomic triage and remediation layer for production systems. It watches every signal, reasons about failures, applies fixes — and commits each fix as a permanent immunity. Your engineers stop being paged for problems the system already knows how to solve.
Modern infrastructure generates more signal than humans can triage. Auto-remediation tools react to known patterns. Neither remembers. The cost compounds every quarter.
A typical production cluster emits thousands of distinct signals daily. Most are noise. The few that matter get lost. On-call rotations burn out faster than the architecture they protect.
Engineers are paged at 03:00 to apply remediation the system already knew about the last three times it happened. Time-to-diagnosis is the largest variable cost in incident response.
Every fix lives in Slack scrollback, a closed Linear ticket, an engineer's head. When the same failure recurs in six months, the team rediscovers it from scratch. Tribal memory does not survive turnover.
Sentinel separates the work by tempo: continuous low-cost triage scans every signal, escalates anomalies to a reasoning core only when the pattern is novel, and commits each successful remediation as an antibody — a permanent immunity recalled by the triage tier next time.
Always-on. Sub-second scan of every signal in the production telemetry stream. Recalls antibodies, applies known remediations. Escalates only when the pattern is genuinely novel.
Invoked only on novelty. Multi-source diagnosis across logs, metrics, configs, code. Proposes a remediation plan, verifies it in a sandbox, applies it — and commits the resulting antibody.
The persistent corpus. Every successful remediation becomes an immunity recalled by Tier 1 on the next occurrence. The system gets faster and cheaper every quarter.
Observability vendors show you what broke. Auto-remediation vendors react to a fixed playbook. Sentinel's antibody database is the moat — a growing corpus of fingerprinted failures, verified remediations, and recall triggers that compounds with every incident.
Triggered when a pod fails to mount a Ceph RBD volume because the previous mounter died without releasing the lock. Sentinel verifies no live mounter, releases the lock, retries the mount.
Detected via service connectivity probe failures from a specific node subset. Sentinel restarts the k3s-agent unit, validates iptables rule propagation, re-runs the probe.
Common after in-place package upgrades that rewrite ExecStart with literal backslash-space sequences. Sentinel diffs against the healthy peer node, scp's the clean unit file, daemon-reloads.
Triggered by ServiceMonitor scrape failures with NXDOMAIN errors. Sentinel cross-references active fleet inventory, prunes stale targets, regenerates the rule manifest.
After a node rotation, the storage CSI driver retains a stale node ID. Volume attachments hang indefinitely. Sentinel deletes the driver pod to force re-registration.
amd64-only image scheduled on the cluster's arm64 node. CrashLoopBackoff with "exec format error". Sentinel patches the deployment with a nodeAffinity exclusion and notifies on missing multi-arch manifest.
Sentinel runs against any production stack — Kubernetes, bare-metal, hybrid. The reasoning core is hyperscaler-portable. The triage tier runs on commodity inference, including local vLLM for air-gapped deployments.
Sentinel can run entirely on customer-owned compute. The reasoning core can be swapped to a local model (vLLM, llama.cpp) for regulated, air-gapped, or data-residency-constrained environments. No mandatory egress to a hyperscaler.
Sentinel V2 entered production on PureTensor's Trinity cluster on 2026-05-18. The numbers below are real, from the live system. We are not pre-product. We are pre-customer.
Internal validation first. Design partners next. Managed offering once the antibody corpus is portable across customer infrastructures.
Sentinel runs autonomically across the Trinity cluster (Kubernetes, Ceph, bare-metal compute, monitoring tier). The antibody corpus accrues from real operational incidents. Every node onboarded reduces median engineer pages by 60–80%.
Selective onboarding of three operational design partners running Kubernetes at meaningful scale. Co-engineered antibody portability, shared corpus modes, customer-specific safety policies. Tight feedback loop on the human-in-the-loop boundary.
Generally available as a managed control plane. Bring-your-own-cloud or fully managed. Antibody corpus federation with cryptographic provenance. Per-incident pricing model.
We are taking introductions from operators running Kubernetes or hybrid infrastructure at scale. Architecture deep-dive, live demo against your incident classes, and design-partner program terms.
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