All right, welcome back. We are in Atlanta, Georgia at the 2025 NRTCCA conference. I still wish we had a shorter name. And I have Motorola. And I'm going to let you say your full name. I know it's Mahesh, but I cannot pronounce your last name.
There we go. That sounded way better than if I would have said it. So, it's phonetic.
Yeah, it's just scary, but it's phonetic.
How are you doing, brother?
I'm doing well. Thank you.
Thank you very much, first of all, for coming out and honoring what we're doing. You spoke today. Very great speech. Motorola is one of the anchors of law enforcement. We've me out at Fort Worth, we're Motorola heavy and you guys have a lot of great products. The last thing that you guys had come out with that we was really pumped about that finally made it to us because you know how it goes with cops was the NXT 6. Is that what it is? NXT the radio that has the screen where I can see where I'm at with the mapping system, all that stuff. Super the N70.
Loved it. Love that product. My guys out in the field, you know, I'm a sergeant now, so I don't really have to do that. But love that stuff. But Mahesh, can you please tell me first and foremost, what brought you out here? You know, when we think about data today in law enforcement, there was a time when data was hard to find. Data was siloed. Now I think we have desiloed data. There's a ton of data. There's a different varieties of data. But the problem right now is that it's so easy to be overwhelmed with data. So where once you didn't have enough data, now you have too much of it, both of it has the same consequence. You can't find what you actually need.
I think RTCCs are one of those powerful integration sources of data of all sorts. And really to make it all actionable, AI plays such a big role. We launched this capability called Assist not too long ago, integrating community information, 911 data, video data, etc. Radio data very specifically and really making it relevant to that particular event so you can take change the trajectory of that event in that moment. And so that is why we are here because we believe that when the word data integration data fusion comes into play, RTCCs are the center of it. Bringing RTCCs closer to 911, to dispatch, to records, to frontline officers, leveraging AI is what we're all about. And so that's why we're here.
Okay. So, the big reveal this year is going to be Assist. That's what you're calling it, correct?
So, we launched Assist for 911 last year. And through the course of this year, we've been launching Assist in its various different forms. Think of Assist as one AI assistant that straddles every single application that a public safety workflow entails. So everything for going from 911 to dispatch to records to evidence to what we launched as SVX which is a body one camera RSM combination which connects to the N70s that I think you use your department uses. All of that allows us to have voice-based conversational and visual exchange with data in a way that was not possible before.
So, you're taking all police's existing platforms such as their RMS system, CAD system, video management systems, and Assist is allowing them to communicate together and pull stuff information that they're looking so quick, fast, and in a hurry.
I mean, you've probably been Motorola Solutions customer for a very long time. And we've always been about collaboration and communication. What we're enabling with Assist is the ability to collaborate and communicate with data directly. So have a conversation with data and that's what Assist really enables you to do.
Excellent. So that is kind of the theme with the NRTCCA as it is anyway is integration. We always want our stuff to work together and to communicate and with what it sounds like with the what Assist is doing. So for our members out there listening and you want to figure out more about this from what I hear as a cop I'm hearing that you have just created something so I don't have to go into RMS start searching. I can't find it here. Let me go over to the CAD system. Now, we all know that takes a lot of time and it when things matter in real time, this sounds like it's going to be a lot faster solution for.
That's right. I mean, if you want to do a real-time investigation on vehicles, as an example, you want to understand, there was a vehicle that was perhaps a red Mazda that you were looking for, but you're looking for a red Mazda in a park. Well, you can search for that. And it's a conversational search. And you just say, 'Show me all Red Mazdas in a park.' Okay.
And so not only do we understand the fact that there's a make and model associated with it, maybe you didn't have the license plate number. But in the background, we see that it's a park that is the background for that particular vehicle. That now gives you enough of an information to do that real-time investigation at the RTCC to take the decisions that you need to take.
Excellent. Now, how far down the rabbit hole does this go? I understand that it's for real-time crime centers. That's great. Can officers in the field use it?
