Tracevox – Predict LLM failures before they hit production

Summary: Tracevox predicts quality, cost, and reliability incidents in LLM applications using AI-driven analysis of model behavior. It correlates latency, tokens, evaluations, and security events in a unified trace to identify root causes and suggest fixes before failures impact users.

What it does

Tracevox monitors LLM systems by treating model behavior as telemetry and uses AI triage to detect and explain issues across prompts, tools, and models. It also enforces enterprise guardrails to catch jailbreaks, prompt injections, and PII leaks in real time.

Who it's for

It is designed for teams running production LLM applications such as copilots, agents, and retrieval-augmented generation (RAG) systems needing proactive incident detection and resolution.

Why it matters

Tracevox addresses the gap in observability tools by predicting LLM failures and providing actionable insights before users experience problems.