[jnovek]

I noticed this on your website regarding transcription --

"More accurate than Deepgram, supporting 50+ languages with a word error rate of just 8.6%."

Can you explain how this helps me? At the end of the day you are not my transcriber, wouldn't I want to test using transcriptions produced by the transcriber that I'm actually using in production?

[zammitjames]

We help capture discrepancies between your transcription model and errors in order to effectively calculate a Word Error Rate (WER) as part of your evaluation process. Post-call transcription tends to be more accurate, and we’ve seen teams manually do this by hiring humans to label a dataset and test against it for WER calculations.

By providing a more accurate baseline, Roark helps teams quantify how well their production transcriptions match reality and flag cases where the model is introducing errors that could impact downstream agent performance. That way, you’re not just testing if your agent responds correctly, but whether it’s getting the right inputs in the first place.