December 4, 2025
.@davitb , CEO of @krispHQ, publishes a must-read weekly Voice AI Newsletter and hosts a regular podcast. I joined Davit and @klemensimonic, co-founder and CEO of @soniox_ai, to talk about the current state of real-time AI transcription.
It's relatively easy to build a voice agent proof of concept, today. But we often see product teams get stuck on the path from POC to production.
Many voice agent products *are* scaling rapidly. I think of the POC-to-production challenges primarily as "best practices" problems.
Which models work best for real-world voice agents? How do you evaluate agent performance? How do you deal with noisy environments? What kind of context management do you need to build on top of your basic transcription->LLM->voice loop to maximize success rates? How do you integrate with existing systems (customer databases, support knowledge bases, telephony stacks)? What does production infrastructure look like?
We touched on all of these topics in the Davit's podcast, plus latency, accuracy, and moving from "transcription" to "speech understanding."
Here's the full video[1]