Great question! Most teams deploying voice AI do have testing and QA flows, but they’re often manual, brittle, or incomplete. Unlike traditional software, voice agents don’t have structured inputs and outputs — users phrase things unpredictably, talk over the bot, or express frustration in subtle ways.

Some engineering teams try to build internal testing frameworks, but it’s a massive effort - they have to log and store call data, build a replay system, define evaluation criteria, and continuously update it as the AI evolves. Most don’t want to spend engineering time reinventing the wheel when they could be improving their AI instead.

The teams that benefit most from Roark are the ones with strong QA processes — they already know how critical testing is, but they’re stuck with brittle, time-consuming, or incomplete workflows.