Q reality, a big part of the challenge is how to get the data, extract the data. What's, what's the, How does the data engineering part of this work? How do you get all this sound data? For example, what you did with the YouTube content, which was awesome, by the way, uh, how do you ingest that? How challenging is it? And how does that work in an enterprise context?
A Yeah, that's a great question. Um, so when we're talking about voice data, there's a few companies that control the pipes, uh, and those companies are Cisco and Viya, and they have Uh, a pretty large footprint in contact center, and then also in unified conferencing. So, uh, these companies are working really, really hard to make, uh, content that flows through their pipe, media content accessible to voice applications, because it makes, uh, their infrastructure more valuable. And, um, in the process of sort of making their infrastructure more valuable to voice application providers, they're cutting out, uh, system integrators. So there is this sort of natural push to simplify integrations to get access to it. So the, the real sort of questions are, ah, you know, when this will hit a tipping point and sort of every voice interaction inside a business will be sort of easily accessible, ah, via API. And I think that's happening very quick as voice processing technology, voice applications hit, ah, you know, ah, baseline utility levels.
AI assessment note: “there's a few companies that control the pipes, uh, and those companies are Cisco”