Tracevox

Hey Product Hunt 👋 I’m Ola, founder of TraceVox.ai. I built TraceVox out of firsthand experience running LLM systems in production and repeatedly hitting the limits of existing observability tools. Traditional APM shows latency and errors, but not why LLMs fail. Existing tools only tell you what happened, not what will break next or how to fix it. With TraceVox, we focus on one thing above all else: - predicting LLM incidents before users are impacted. Here’s what makes us different: - We analyze model behavior as first-class telemetry (not just logs) - Our AI predicts quality, cost, and reliability issues before they escalate - When something goes wrong, AI-powered triage explains the root cause and suggests concrete fixes (prompt, retrieval, tools, model) - Built-in guardrails catch jailbreaks, prompt injection, and PII leaks in real time TraceVox is built for teams running LLMs in production — copilots, agents, and RAG systems — who need answers, not dashboards. We’re early and actively looking for feedback from engineers shipping LLM apps. What’s the hardest part of running LLMs in production for you right now?