Shipping Production LLM Ops Without Surprises

Enterprise analysts needed an AI assistant they could trust in regulated environments. JarvisX blended deterministic automations with LLM planning, but only after we layered in ruthless observability.

We instrumented every prompt, tool invocation, and fall back path. Evaluations ran nightly on red-team scenarios so we could ship confidently and catch regressions early.

This post walks through the guardrails, monitoring topology, and human-in-the-loop patterns that let us deploy LLM features without surprises.