Node.js In-App Chatbot LLM API: Moderation Quality Gates Before Review

Short answer: for a Node.js in-app chatbot that classifies game reports, use the API whose measured quality clears the policy floor and whose p95 latency fits the review queue; keep ambiguous cases on a slower escalation path.

A game moderation pipeline should choose an LLM API by the worst acceptable classification error, then test whether the resulting latency fits the human-review queue. The popular question, "Which API is best?", is backwards for this job. The useful answer is a routing contract: a fast first pass for ordinary reports, a stricter path for ambiguous evidence, and an explicit abstention result when the model cannot justify a label.

That design also changes what a Node.js integration needs to preserve. The application must record the original report, the prompt version, the model response, the elapsed time, and the reason a report was escalated.…