They don’t have a full encompassing device. And we are constantly updating that platform as well. We’re seeing people that got caught up in the 5G and the LTE issue. We didn’t have that issue, because we have our own FCC ID. In the Biotres device, we’re seeing tons and tons of patch monitors, but they’re all one channel devices. They’re having to produce custom electrodes. Yes, the customer electrodes are cheap, but it’s still a problem in a manufacturing and a whole cycle that you have to deal with. We don’t have to deal with that because we’re using standard electrodes. We’re focusing on three channels, which provides a better clinical quality and more data. And so, if you — if everything is equal, a physician will always pick a three-channel device over a one-channel device, because your diagnostic yield is better.
And so, if we focus on the clinic clinical aspects and the technical aspects, and we continue to keep our eyes on that, I think we’ll continue to succeed. So far, we’re a leader and that means that we cannot rest. We just need to maintain that lead. So, we’re seeing the opportunity. We’re seeing other people jumping in, but so far, nobody has really come to us and beat us technically. And I think that goes back to our retention rate. Like, we’ve been in the market for about four years now. We’re not losing customers. So, all these guys are coming in, they’re going after — so going after the space, why are they not able to boot us out, right? And the reason is because we are technically superior, we’re clinically superior, we’re constantly updating, and we’re also going deeper into the accounts with our product portfolio.
Kevin Dede: Last question from me, Waqaas. You’ve mentioned AI a couple of times. Now, I know it’s — right, it’s the rage buzzword on chatGPT, right? But can you — I’m assured that you’re not trying to integrate that. Can you just give us a little more insight on how you’re using AI and how you think it will help differentiate your solution?
Waqaas Al-Siddiq: Yes. I mean part of this is proprietary, right? So, I’ll give you a higher level of response perhaps. So, look, we don’t think — people are looking at AI in all types of different ways, right? So, I would say that we use AI in three or four different ways, right? And we really look at it from an application applied perspective, right? So, what do I mean by that, right? So, first thing is there’s this whole deep learning piece, right? And deep learning is how do we look at our data insights and understand where is our algorithm performing well and where is our algorithm not performing well, so we can optimize our algorithm, right? And so that’s a deep learning piece. You take the data sets that you already have, which are based on your device, right?
Because when we first launched our device, our data sets were based on data that was some clinical data and some data that was provided by the FDA. Now we’ve got our own data set, right? After hundreds of thousands of patients, we have our data set, which allows us to understand exactly how our algorithms are working with our devices, and we use that to understand and get insights and that allows us to update our algorithms and how that works. So that’s really about detection and understanding what to focus the physician’s time on. Now why is that important? Because the more data you throw a physician, the less time they have. So, if you can make it more focused and more accurate, every little bit helps from a scalability perspective. The other area that we look at AI has nothing to do with our device and our technology, it’s really about internal automation and making things more seamless and simplified from an internal process level.
