I spent 2 months building observability for AI voice agents because debugging them was driving me insane

Reddit r/AI_Agents 05/29/26, 08:45 PM Tools

observability voice-agents debugging latency hallucinations monitoring vapi

Summary

Developer built VoiceOBS, an observability tool for AI voice agents, providing latency breakdowns, sentiment analysis, hallucination detection, and more, integrated with Vapi.

I've been building voice agents on Vapi and kept hitting the same wall: a call goes bad, the customer hangs up and I have no idea why. Was it latency? Did the LLM hallucinate? Did a function call time out? The existing observability tools (Helicone, Langfuse) only show you prompts and responses, they're built for text, not voice. They can't see the stuff that actually breaks voice agents. So I built VoiceOBS. You connect your Vapi (working on integrating Retell) account with a webhook, and every call gets analyzed automatically: * Latency broken down by STT / LLM / TTS, with p50 and p95 * Sentiment, intent, and a CSAT estimate per call (analyzed by Claude) * Hallucination flags * Full searchable transcripts * End-reason breakdown so you can see *why* calls actually end Setup takes about 60 seconds: sign up, create an integration, paste the webhook URL into Vapi, make a call, and it shows up analyzed. It's free during beta (100 calls/month, no credit card). I'm genuinely looking for honest feedback more than anything, what's confusing, what's missing, what would make you actually use it. Happy to answer any questions. Thank you.

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