Reflexion Engine deploys Actor/Critic AI agents on Vertex AI that observe, reason, and remediate Kubernetes incidents before your on-call engineer finishes their coffee. Probabilistic reasoning, not brittle runbooks.
Not a consultancy. An engineering team that ships production-grade agentic infrastructure.
Reflexion Engine replaces deterministic runbooks with probabilistic adaptation. Actor/Critic agents on Vertex AI handle novel failures traditional automation cannot anticipate.
ShrikeOps MCP Bridge lets AI agents reason over live cluster state. Every manifest scanned by Pluto, Polaris, kube-score, and OSV.dev before it reaches your estate.
No PII-laden telemetry leaves your perimeter. Vertex AI, AlloyDB, and Cloud Run locked behind VPC Service Controls. Pass FinReg audits in 48 hours — JPMorgan/BNY-grade compliance by design.
Mathematical rightsizing: VM changes only execute if projected SLO compliance stays ≥95%. Cut token hemorrhage 40–60% via intelligent context caching.
Before & After · Reflexion Engine
Mean Time To Recovery
Hypothesis-driven RCA vs. 14-dashboard switchingTokens Per Incident
Sub-1K targeted actions vs. monolithic LLM callsBaseline Cost / Month
Mathematical rightsizing, not over-provisioningWe built the Reflexion Engine because we were tired of 3 AM pager duty for incidents that follow the same 10 patterns every single time.
Observation Brain ingests telemetry. Reasoning Brain hits AlloyDB pgvector in <100ms. Action Brain executes Terraform/kubectl. Context bloat eliminated.
Cloud Run with pre-warmed instances. First byte <80ms. No container spin-up during a production incident.
Vertex AI, AlloyDB, Cloud Run inside VPC Service Controls. Incident telemetry never leaves your GCP org. FinReg compliant by architecture.
Every remediation action is gate-checked against SLO projections. Drops below 95%? Action blocked and escalated. Automation with a kill switch, always.
Architecture · Dual-Brain Reflexion Engine
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