Why Near-Real-Time Beats Real-Time Call Transcription (Full Transcript)

[00:00:00] Speaker 1: How do you make those design decisions between post-call versus real-time and how do you weigh off some of the trade-offs that you see there?

[00:00:06] Speaker 2: Yeah, so we have some demand from customers for real-time, but we haven't really gone there. So that layer down here that I talked about, which is the integration layer, this is a complex mess of horrible integrations to APIs on old legacy call systems that are pants. And they go down, they fail. And I was a technical founder, so I was involved in building a lot of this stuff at the start, and it's horrible. And asking the team to now, instead of downloading the call after the call, because normally we receive an event or we can run a report every two minutes for how many calls ended in the last two minutes. Okay, just give me those transcripts. That's a much easier loop. Then let's try and connect to the stream, transcribe it in real-time, and then actually get into our API in real-time. So for us, the gain wasn't enough to go down that thing. But what is important for us is we do have one of the large ins for us in high-volume contact centers is that we assess. We assess every call that's happened in the last 30 minutes, and then we compare it to every 30 minutes. So we have a 30-minute interval over the last 30 days, and we look at what are the themes appearing, and is there anything unusual? So we know that at half seven on a Wednesday evening, there'll be this many calls about cancellations and this many calls about password issues. But oh, hey, there's normally not some calls around this payment problem. And then we can build an alert around that and quantify that and get action fast. But that requires us to have the transcripts of the system as soon as possible after the call ends. So for us, the real-time is more around, we call it near-time. We call it real-time on our website, but really, you know, it's posted. First call, we hammer it at the API, and we need a response really quick. And then that can, often in those circumstances, there's an influx of calls. So then we need to kind of scale that up very quickly to transcribe all of those calls and get that result back to the user.