What observability tools are others using with Pipecat or similar voice AI frameworks? I've built a production voice agent using Pipecat and currently track basic metrics (call duration, sentiment, summary, transcripts) in a custom dashboard. Tomorrow it's going in production so problem I think I can face is When errors will occur, debugging is painful. My current logging approach creates massive log files that are nearly impossible to analyze efficiently when tracking down issues.

Has any one built an voice bot without pipecat and livekit would love to connect with them I have built it and facing some issues in latency part My tech stack is openai llm , Deepgram for ASR and Azure for TTS and one telephony vendor which connects everything

What do you usually track for call metrics? duration, sentiment, rate of booking vs inquiries (if applicable), if caller ended call prematurely. Do you think it is important to track if caller always interrupts the agent and doesn't let the agent finish talking? Am thinking that's a sign the agent is talking too much. But right now I'm having a hard time getting that part right - it's counting more interruptions than the number of times the agent spoke. What else do you track?

Hi everyone! I just joined the community and wanted to say a quick hello. I’m excited to learn from all of you, share what I can, and be part of the conversations. Looking forward to connecting!

Honestly, I've been building voice AI agents with Ultravox AI and the help of Claude. I understand that this community is really about LiveKit and Pipecat and open source, but Ultravox is also open source. I've had a lot of success using Ultravox AI. I've had some success with LiveKit and Pipecat, but I've had the most success with Ultravox AI. I think it's undervalued and overlooked as a source for open source AI agents and building them.oh, and…Claude is king!