I built a tool to debug Vapi/Retell voice agents (Latency breakdown, Cost tracking)

Voice AI pipelines are black boxes. When a 12-turn conversation chokes, you’re left guessing whether it’s:

• ASR taking 800ms to transcribe
• LLM streaming chunks slowly
• TTS buffer underrun

So I built Hevo – a debugging dashboard specifically for Vapi/Retell voice pipelines.

What it actually shows you:

• Latency waterfall per turn: See exactly where time bleeds (ASR vs LLM vs TTS). Values are inferred from provider logs since most don't expose granular server-side timing yet.
• Cost tracking per conversation: Retell's pricing is opaque; Vapi's varies by model. This aggregates actual spend per call.
• Unified view: One schema across providers. Switching from Vapi to Retell (or running both) doesn't break your analytics.

Current limitations (beta honesty):

• Latency numbers are approximations based on round-trip deltas, not internal provider timers
• Only supports Vapi/Retell right now (Bland/Deepgram agents next)

What I need from you:
If you're building voice agents, what’s your biggest debugging nightmare? Is it latency spikes, cost explosions, or something else entirely?

Check it out here : https://hevo.dev