In a conversation on theCUBE and NYSE Wired: Physical AI and Robotics, Hemant Banavar of Motive, chief product officer, discusses Motive's development of hardware, software and artificial intelligence for the physical economy. Banavar outlines products and partnerships, including AI Dashcam Plus, AI Omnicam Plus, Atlas and collaboration with Qualcomm, and describes constraints and solutions for edge computing in fleet safety and telematics. They draw on theCUBE Research to frame trends in physical AI and robotics.
Banavar reports that Motive's platform shifts AI from insight to action. Real-time edge AI reduces collisions by about 80% and cuts accident-related costs by roughly 63% while increasing vehicle uptime by 18%. They cite customer outcomes such as Carvana's 10% increase in on-time deliveries, Weston Xpress's 42% reduction in rollovers and Kona's 52% reduction in safety events. They outline automation use cases for fatigue intervention and back-office workflows and explain deployment considerations for fleet managers and telematics teams.
Viewers gain insights into hardware and software integration, edge computing constraints, regulatory and deployment factors to consider and partnership strategies for scaling robotics and physical AI across transportation and logistics operations.
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>> ... Palo Alto studio connection, Silicon Valley and Wall Street. I'm John Furrier, talking to you here at and my co-host...
Gemma Allen
>> Welcome back to theCUBE Studio here at the New York Stock Exchange. I'm Gemma Allen with NYSE Wired: Physical AI & Robotics, an industry worth $50 trillion that some folks feel is largely untapped. And nobody knows that opportunity more than my next guest, Chief Product Officer at Motive, Hemant Banavar. Welcome to theCUBE.
Hemant Banavar
>> Thank you, Gemma. Good to be here today.
Gemma Allen
>> So, to begin, talk to me a little bit about the world that Motive operates in, the world of physical AI. There's somewhat largely untapped opportunity thus far, but growing, and growing in interest, and clear advantage. Fill me in on what it is exactly that you guys do.
Hemant Banavar
>> Yeah, absolutely. We actually build hardware, software, and AI for people who keep the physical economy moving. The people that I'm talking about is really people on the road, in the field, on job sites, in warehouses, and across industrial operations. We actually build AI for them that actually can be deployed in their vehicles, at their job sites. And enables them to actually operate more safely, improve productivity, and improve profitability. This is very different from what you see in the digital world. And the big difference is, in the physical world, what matters is accuracy of AI can be the difference between life and death. If you cannot detect an unsafe situation in a matter of seconds or milliseconds, it actually can cost lives, cost money. And also, if you think about it, the fact that physical AI needs to be really done in real time and accurately, is very different from what you're seeing in the digital economy today, where you can tolerate if your email draft from one of the models is slightly incorrect. You cannot tolerate that here.
Gemma Allen
>> So, we know there's a lot of things happening in this space in a quick pace of time. There's been some really key innovations of late and Motive has been driving some of those. You are just off the back of your annual Vision conference in Nashville, which you're bummed to miss for a number of reasons. One, I love Nashville, but we also love the world of physical AI. Talk to us a little bit about what you guys announced, what sorts of innovations you're bringing to the market, and where the focus has been at such a, I guess, chaotic time in tech.
Hemant Banavar
>> Yeah. We had a really awesome annual conference in Nashville. Definitely, you should come check it out next year. But look, at this time, we have been investing in a lot of just improving physical AI through many different things. One, we launched our AI Dashcam Plus earlier this year, which is a really next generation edge computing device, which has really computer vision capabilities, as well as a lot of other capabilities that enables it to do not only AI, but a lot of things on the edge. It can run automations. It can help the driver navigate through a tricky situation. But also, it can enable them to have a two-way communication with their back office. At Vision, we actually announced a new product around... which we are launching soon, AI Omnicam Plus, which takes that camera that's in the cab of the vehicle. And then actually now gives you 360 degree visibility around the vehicle, on the side, in the rear, inside of maybe a cargo that you want to monitor, all of that. So, essentially, what we are doing is we are creating a halo both around the driver, to keep them safe in a really real world situation, but also halo around the vehicle to ensure that you have full visibility on what's happening and AI that is helping you take action when you need to. The other thing that we announced is Atlas. Atlas is essentially... think of it as an assistant that is available in the cab so the driver can talk to it. Atlas will help them answer questions, but also help them even guide them through unsafe situations, if Atlas detects that there's something unsafe happening. But also, the same Atlas experience is available in the dashboard for fleet managers, to enable them to not only just look at data and figure out for themselves, but very quickly get them insights that they need, that they need to act on immediately. So, Atlas is essentially a new way for us to enable our customers, both in the field and in the office, to take advantage of all the AI capabilities, and actually save time for them, and make them more safer.
Gemma Allen
>> Wow. And that's so important to think about how siloed the data and the intelligible signals have been in this industry for such a long time. I'm very interested in what you said around actually taking that intel and that signal and creating an actionable plan, creating an actionable insight, especially in this world where there's so much risk and opportunity for even to save lives. Talk me through an example whereby you have a driver who might appear drowsy on a dash cam. What will this world look like whereby Motive's technology will actually be able to prevent an accident by taking an action, like in that instance?
Hemant Banavar
>> Yeah. Let's actually walk through that. And I think before we do that, I want to highlight something that is important to think about what has happened in this industry for so long. For so long, if you think about it, there have been a lot of telematics and recording devices that have existed in this industry, but they have been very much about just data collection. And essentially, when we talk to our customers, we hear this a lot that they have a lot of data that they can look back to. They don't have the time to look at all of this and take action in a meaningful way. That is what AI enables us to change. So, coming to your question, how is this helping a driver who is fatigued on the road? Let me make that very concrete. Imagine a driver, driving down the road, probably has been driving for the last 10 hours, had a really long night, has a young kid at home, kept them awake. They're really fatigued. They're very clearly showing those signals of fatigue, yawning, they're trying to keep awake. Our camera has really complex AI models that are running continuously and looking at the driver and how they're driving on the road. It can very quickly detect that they're fatigued. It will alert them first and try to get them to actually react to it and stop. But let's say they still want to power through and they continue to struggle through that fatigue. What now AI enables us to do and automations enables us to do, our customers can just deploy an automation that just says, "Hey, if a driver continues to be fatigued for a longer duration for say more than two minutes," actually initiate a call. And actually have a conversation with them through a AI agent to get them to safely pull off the road, and take a break, and then notify me as the fleet manager who can then actually go engage, if needed. That whole thing, imagine now nobody needs to be watching a dashboard in real time. This is happening through AI. The driver got the help they need. They're off the road, they're safe, they're taking a break. And now, the fleet manager also got alerted, so they know that they need to talk to the driver and ask them to take care of themselves before they start driving again.
Gemma Allen
>> Wow. I mean, that is a technology that has powerful impacts. When we think about the business impacts of that alone, as well as obviously the human impacts are huge and the slight impacts. But in the world of AI 2026, a lot of the conversations have been about receipts. Folks want to see the return on investment for some of these investments they've made in AI. Physical AI I'm sure is having the same conversation. Talk to me about the ROI and the realized ROI for companies like yours, for the partnerships, and the relationships with the customers you've built in this time. What sort of metrics are you measuring and seeing?
Hemant Banavar
>> Yeah. Especially, what I would say in this industry, when we look at our customers, they don't buy AI because it's trendy. They buy it because it can actually cut collisions and save lives. That's the standard that we hold ourselves to. And this is where, on average, something that we see often on average, our customers actually are able to reduce collisions by about 80% once they deploy our technology. They save nearly 1,000 hours a year on reporting and administrative tasks. We actually see a very significant, almost 63% reduction in accident-related costs and an average of 18% increase in vehicle up time. This is something that we are seeing actually across our base. And what this is allowing our customers to do is then take this and compound the value in terms of their business, because now it's helping them run a better business. We saw, for example, Carvana saw a 10% increase in on time delivery just deploying this technology and because of these outcomes. Weston Xpress achieved a 42% reduction in rollovers. This was a big problem for them, pretty much significantly took it off the table for them. Kona achieved a 52% decrease in safety events. So, ultimately, look, AI only matters if it improves the outcomes. And in the physical economy, that is really what people want and that is what we are building towards. And that's the future we see, where we can help them continue to deliver more outcomes that are meaningful for them to run their business.
Gemma Allen
>> Let's talk about the technology that makes all this possible. We talk a lot about the hyper-converged edge, physical AI, AI on the edge. And we know that it's a space that is getting a lot of attention for great reason. Talk to me as a chief product officer of a company like this, about how you think about the innovation in this space, the constraints which we know exist across the board right now, in the world of AI. The edge tends to be lower power, more agile, needs more flexibility. What sorts of unique challenges do you see, Hemant?
Hemant Banavar
>> Yeah. It's a really important question that me and my team think about a lot. When I think about AI and what is happening today and what it can do in this industry, what we see is the next era of AI is about action and not insights. And this is where we see two things. One, to be able to deliver really high quality actions that actually meaningfully deliver the outcomes that we just talked about to our customers. We need to have a proprietary platform that can actually go from hardware to data and software and AI. And that is where we have taken the stance that we have to build it in a way that we have full control over all of those, and can actually take advantage of these three pieces that come together, and we can bolt really meaningful experiences on top of that. The second part is actually when you talk about the hardware, really having a partner who understands what you just described, that edge AI, the power constraints, the environmental constraints that this device needs to operate in. This is not your computer sitting at your desk. This is a compute device sitting in a vehicle. Could be in the heat of the Arizona desert, like 120 degrees or could be in New York in winter, like really extreme conditions. And think about vibrations, heat, dust, everything. So, we wanted to make sure that we partnered with somebody who really understood these environments and could partner with us to build for those. And Qualcomm has been a great partner for us to work with. We use a Qualcomm chip in our AI Dashcam Plus and AI Omnicam Plus, which is at the heart of the compute capacity that we get where we can run our AI models. What this allows us is now with the latest Qualcomm chip in our devices, we can run three times more computer vision models on these devices than the next leading devices out there today. That means we are detecting more unsafe events more, and can alert and take action on more of those events than any of those devices out there. So, that's the future that we see is more compute on the edge, really in those constrained environments, with really capable hardware. And then connecting that to software and AI and building that whole ecosystem, such that we can deliver the outcomes that our customers deserve.
Gemma Allen
>> That fully integrated solution that everyone seeks.
Hemant Banavar
>> That's exactly right.
Gemma Allen
>> When we think about Motive as a company, an interesting part of your story is that you guys outgrew your original name quite quickly. Because business opportunity almost months after launching what was then KeepTruckin, became much, much larger than you, I guess, or that your founders originally envisioned. We're also at a point now, I think, in the industry, where there's so much transferable opportunity for a company like this. We have the Montgomery ruling potentially here in the US, which creates a whole load of inertia at C suite level around what sorts of risks might exist in specific areas. How are you guys thinking about that, about rules, opportunities like that, but also the transferable opportunity for the company?
Hemant Banavar
>> Yeah. Look, actually, the Montgomery verdict that you mentioned, just to give some context for this audience. For the last 20 years, freight brokers have operated with a massive legal safety net. And with this worded, essentially Supreme Court completely took that away. And what that means is now brokers who work with a lot of the carriers who are customers, actually need to do a lot more work to ensure that the carriers that are actually carrying the load are legit, and have really safe business practices, and actually are going to do the job the way they're supposed to do it. This actually is huge, in terms of the amount of compliance and the amount of liability that they carry if they don't do this right. We are actually really at the end of the day in a unique position to help them. If you think about it, we already have a lot of carriers. We have 100,000 carriers on our platform today, who are working with these brokers every single day. They want their brokers to know how good they are. And we are able to help connect the dots for the brokers to work with our carriers in a meaningful way. So, on that front, we see massive opportunity for us to create value, not just for our carriers who we serve, but also help them get better business from brokers and everybody else that they work with in direct ecosystem. And that's kind of like the transformation that you are getting at, Gemma, which is the data, the AI that we have today, enables us to solve more problems for our customers. Where not only it is about what we do today, but it is about solving more problems for them in the future, which helps them run a better business. And that's where we see going in the future.
Gemma Allen
>> Wow. Well, there's certainly huge opportunity on the horizon for you and your team. What else is on that horizon? Last question to you. You've come back on the back of a great event in Nashville a couple of weeks ago. Lots of excitement and enthusiasm in the space. You guys are on quite the upward journey. What does the next 12 months look like for you and the team at Motive?
Hemant Banavar
>> We have been busy and there's a lot for us to do. Again, our conference a few weeks ago in Nashville was both a great validation for how meaningful the product that we have built is actually for our customers, but also, so much more excitement from our customers about what future holds. And what you're going to see from us is a lot more in terms of actions that we can start enabling our customers to take, in addition to the insights that we deliver. The next wave of AI essentially will reduce that operational burden for frontline teams. And essentially, give them a lot of time back, in terms of all the manual processes or repetitive tasks that they have been doing, that we can help AI do it for them. May be intervening when there is an unsafe situation in the field or simply, maybe like a back office task of maybe verifying if I have a valid driver's license. All of these things we can automate and enable them to not have to do these repetitive things, instead focus on what really matters to them, which is about getting leverage and running a better business. So, what you will see from us is a lot more of the actions that AI can help them automate, along with all the stuff that we are already doing over the next four months.
Gemma Allen
>> Well, it's certainly a good time to have a business that helps businesses optimize and build more efficiently. Hemant Banavar, thank you so much for joining us on theCUBE.
Hemant Banavar
>> Thank you so much for having me.
Gemma Allen
>> I'm Gemma Allen here at theCUBE Studio at the New York Stock Exchange. This is Physical AI and Robotics, part of our NYSE Wired series. Thanks for watching.
>> ... Palo Alto studio connection, Silicon Valley and Wall Street. I'm John Furrier, talking to you here at and my co-host...
Gemma Allen
>> Welcome back to theCUBE Studio here at the New York Stock Exchange. I'm Gemma Allen with NYSE Wired: Physical AI & Robotics, an industry worth $50 trillion that some folks feel is largely untapped. And nobody knows that opportunity more than my next guest, Chief Product Officer at Motive, Hemant Banavar. Welcome to theCUBE.
Hemant Banavar
>> Thank you, Gemma. Good to be here today.
Gemma Allen
>> So, to begin, talk to me a little bit about the world that Motive operates in, the world of physical AI. There's somewhat largely untapped opportunity thus far, but growing, and growing in interest, and clear advantage. Fill me in on what it is exactly that you guys do.
Hemant Banavar
>> Yeah, absolutely. We actually build hardware, software, and AI for people who keep the physical economy moving. The people that I'm talking about is really people on the road, in the field, on job sites, in warehouses, and across industrial operations. We actually build AI for them that actually can be deployed in their vehicles, at their job sites. And enables them to actually operate more safely, improve productivity, and improve profitability. This is very different from what you see in the digital world. And the big difference is, in the physical world, what matters is accuracy of AI can be the difference between life and death. If you cannot detect an unsafe situation in a matter of seconds or milliseconds, it actually can cost lives, cost money. And also, if you think about it, the fact that physical AI needs to be really done in real time and accurately, is very different from what you're seeing in the digital economy today, where you can tolerate if your email draft from one of the models is slightly incorrect. You cannot tolerate that here.
Gemma Allen
>> So, we know there's a lot of things happening in this space in a quick pace of time. There's been some really key innovations of late and Motive has been driving some of those. You are just off the back of your annual Vision conference in Nashville, which you're bummed to miss for a number of reasons. One, I love Nashville, but we also love the world of physical AI. Talk to us a little bit about what you guys announced, what sorts of innovations you're bringing to the market, and where the focus has been at such a, I guess, chaotic time in tech.
Hemant Banavar
>> Yeah. We had a really awesome annual conference in Nashville. Definitely, you should come check it out next year. But look, at this time, we have been investing in a lot of just improving physical AI through many different things. One, we launched our AI Dashcam Plus earlier this year, which is a really next generation edge computing device, which has really computer vision capabilities, as well as a lot of other capabilities that enables it to do not only AI, but a lot of things on the edge. It can run automations. It can help the driver navigate through a tricky situation. But also, it can enable them to have a two-way communication with their back office. At Vision, we actually announced a new product around... which we are launching soon, AI Omnicam Plus, which takes that camera that's in the cab of the vehicle. And then actually now gives you 360 degree visibility around the vehicle, on the side, in the rear, inside of maybe a cargo that you want to monitor, all of that. So, essentially, what we are doing is we are creating a halo both around the driver, to keep them safe in a really real world situation, but also halo around the vehicle to ensure that you have full visibility on what's happening and AI that is helping you take action when you need to. The other thing that we announced is Atlas. Atlas is essentially... think of it as an assistant that is available in the cab so the driver can talk to it. Atlas will help them answer questions, but also help them even guide them through unsafe situations, if Atlas detects that there's something unsafe happening. But also, the same Atlas experience is available in the dashboard for fleet managers, to enable them to not only just look at data and figure out for themselves, but very quickly get them insights that they need, that they need to act on immediately. So, Atlas is essentially a new way for us to enable our customers, both in the field and in the office, to take advantage of all the AI capabilities, and actually save time for them, and make them more safer.
Gemma Allen
>> Wow. And that's so important to think about how siloed the data and the intelligible signals have been in this industry for such a long time. I'm very interested in what you said around actually taking that intel and that signal and creating an actionable plan, creating an actionable insight, especially in this world where there's so much risk and opportunity for even to save lives. Talk me through an example whereby you have a driver who might appear drowsy on a dash cam. What will this world look like whereby Motive's technology will actually be able to prevent an accident by taking an action, like in that instance?
Hemant Banavar
>> Yeah. Let's actually walk through that. And I think before we do that, I want to highlight something that is important to think about what has happened in this industry for so long. For so long, if you think about it, there have been a lot of telematics and recording devices that have existed in this industry, but they have been very much about just data collection. And essentially, when we talk to our customers, we hear this a lot that they have a lot of data that they can look back to. They don't have the time to look at all of this and take action in a meaningful way. That is what AI enables us to change. So, coming to your question, how is this helping a driver who is fatigued on the road? Let me make that very concrete. Imagine a driver, driving down the road, probably has been driving for the last 10 hours, had a really long night, has a young kid at home, kept them awake. They're really fatigued. They're very clearly showing those signals of fatigue, yawning, they're trying to keep awake. Our camera has really complex AI models that are running continuously and looking at the driver and how they're driving on the road. It can very quickly detect that they're fatigued. It will alert them first and try to get them to actually react to it and stop. But let's say they still want to power through and they continue to struggle through that fatigue. What now AI enables us to do and automations enables us to do, our customers can just deploy an automation that just says, "Hey, if a driver continues to be fatigued for a longer duration for say more than two minutes," actually initiate a call. And actually have a conversation with them through a AI agent to get them to safely pull off the road, and take a break, and then notify me as the fleet manager who can then actually go engage, if needed. That whole thing, imagine now nobody needs to be watching a dashboard in real time. This is happening through AI. The driver got the help they need. They're off the road, they're safe, they're taking a break. And now, the fleet manager also got alerted, so they know that they need to talk to the driver and ask them to take care of themselves before they start driving again.
Gemma Allen
>> Wow. I mean, that is a technology that has powerful impacts. When we think about the business impacts of that alone, as well as obviously the human impacts are huge and the slight impacts. But in the world of AI 2026, a lot of the conversations have been about receipts. Folks want to see the return on investment for some of these investments they've made in AI. Physical AI I'm sure is having the same conversation. Talk to me about the ROI and the realized ROI for companies like yours, for the partnerships, and the relationships with the customers you've built in this time. What sort of metrics are you measuring and seeing?
Hemant Banavar
>> Yeah. Especially, what I would say in this industry, when we look at our customers, they don't buy AI because it's trendy. They buy it because it can actually cut collisions and save lives. That's the standard that we hold ourselves to. And this is where, on average, something that we see often on average, our customers actually are able to reduce collisions by about 80% once they deploy our technology. They save nearly 1,000 hours a year on reporting and administrative tasks. We actually see a very significant, almost 63% reduction in accident-related costs and an average of 18% increase in vehicle up time. This is something that we are seeing actually across our base. And what this is allowing our customers to do is then take this and compound the value in terms of their business, because now it's helping them run a better business. We saw, for example, Carvana saw a 10% increase in on time delivery just deploying this technology and because of these outcomes. Weston Xpress achieved a 42% reduction in rollovers. This was a big problem for them, pretty much significantly took it off the table for them. Kona achieved a 52% decrease in safety events. So, ultimately, look, AI only matters if it improves the outcomes. And in the physical economy, that is really what people want and that is what we are building towards. And that's the future we see, where we can help them continue to deliver more outcomes that are meaningful for them to run their business.
Gemma Allen
>> Let's talk about the technology that makes all this possible. We talk a lot about the hyper-converged edge, physical AI, AI on the edge. And we know that it's a space that is getting a lot of attention for great reason. Talk to me as a chief product officer of a company like this, about how you think about the innovation in this space, the constraints which we know exist across the board right now, in the world of AI. The edge tends to be lower power, more agile, needs more flexibility. What sorts of unique challenges do you see, Hemant?
Hemant Banavar
>> Yeah. It's a really important question that me and my team think about a lot. When I think about AI and what is happening today and what it can do in this industry, what we see is the next era of AI is about action and not insights. And this is where we see two things. One, to be able to deliver really high quality actions that actually meaningfully deliver the outcomes that we just talked about to our customers. We need to have a proprietary platform that can actually go from hardware to data and software and AI. And that is where we have taken the stance that we have to build it in a way that we have full control over all of those, and can actually take advantage of these three pieces that come together, and we can bolt really meaningful experiences on top of that. The second part is actually when you talk about the hardware, really having a partner who understands what you just described, that edge AI, the power constraints, the environmental constraints that this device needs to operate in. This is not your computer sitting at your desk. This is a compute device sitting in a vehicle. Could be in the heat of the Arizona desert, like 120 degrees or could be in New York in winter, like really extreme conditions. And think about vibrations, heat, dust, everything. So, we wanted to make sure that we partnered with somebody who really understood these environments and could partner with us to build for those. And Qualcomm has been a great partner for us to work with. We use a Qualcomm chip in our AI Dashcam Plus and AI Omnicam Plus, which is at the heart of the compute capacity that we get where we can run our AI models. What this allows us is now with the latest Qualcomm chip in our devices, we can run three times more computer vision models on these devices than the next leading devices out there today. That means we are detecting more unsafe events more, and can alert and take action on more of those events than any of those devices out there. So, that's the future that we see is more compute on the edge, really in those constrained environments, with really capable hardware. And then connecting that to software and AI and building that whole ecosystem, such that we can deliver the outcomes that our customers deserve.
Gemma Allen
>> That fully integrated solution that everyone seeks.
Hemant Banavar
>> That's exactly right.
Gemma Allen
>> When we think about Motive as a company, an interesting part of your story is that you guys outgrew your original name quite quickly. Because business opportunity almost months after launching what was then KeepTruckin, became much, much larger than you, I guess, or that your founders originally envisioned. We're also at a point now, I think, in the industry, where there's so much transferable opportunity for a company like this. We have the Montgomery ruling potentially here in the US, which creates a whole load of inertia at C suite level around what sorts of risks might exist in specific areas. How are you guys thinking about that, about rules, opportunities like that, but also the transferable opportunity for the company?
Hemant Banavar
>> Yeah. Look, actually, the Montgomery verdict that you mentioned, just to give some context for this audience. For the last 20 years, freight brokers have operated with a massive legal safety net. And with this worded, essentially Supreme Court completely took that away. And what that means is now brokers who work with a lot of the carriers who are customers, actually need to do a lot more work to ensure that the carriers that are actually carrying the load are legit, and have really safe business practices, and actually are going to do the job the way they're supposed to do it. This actually is huge, in terms of the amount of compliance and the amount of liability that they carry if they don't do this right. We are actually really at the end of the day in a unique position to help them. If you think about it, we already have a lot of carriers. We have 100,000 carriers on our platform today, who are working with these brokers every single day. They want their brokers to know how good they are. And we are able to help connect the dots for the brokers to work with our carriers in a meaningful way. So, on that front, we see massive opportunity for us to create value, not just for our carriers who we serve, but also help them get better business from brokers and everybody else that they work with in direct ecosystem. And that's kind of like the transformation that you are getting at, Gemma, which is the data, the AI that we have today, enables us to solve more problems for our customers. Where not only it is about what we do today, but it is about solving more problems for them in the future, which helps them run a better business. And that's where we see going in the future.
Gemma Allen
>> Wow. Well, there's certainly huge opportunity on the horizon for you and your team. What else is on that horizon? Last question to you. You've come back on the back of a great event in Nashville a couple of weeks ago. Lots of excitement and enthusiasm in the space. You guys are on quite the upward journey. What does the next 12 months look like for you and the team at Motive?
Hemant Banavar
>> We have been busy and there's a lot for us to do. Again, our conference a few weeks ago in Nashville was both a great validation for how meaningful the product that we have built is actually for our customers, but also, so much more excitement from our customers about what future holds. And what you're going to see from us is a lot more in terms of actions that we can start enabling our customers to take, in addition to the insights that we deliver. The next wave of AI essentially will reduce that operational burden for frontline teams. And essentially, give them a lot of time back, in terms of all the manual processes or repetitive tasks that they have been doing, that we can help AI do it for them. May be intervening when there is an unsafe situation in the field or simply, maybe like a back office task of maybe verifying if I have a valid driver's license. All of these things we can automate and enable them to not have to do these repetitive things, instead focus on what really matters to them, which is about getting leverage and running a better business. So, what you will see from us is a lot more of the actions that AI can help them automate, along with all the stuff that we are already doing over the next four months.
Gemma Allen
>> Well, it's certainly a good time to have a business that helps businesses optimize and build more efficiently. Hemant Banavar, thank you so much for joining us on theCUBE.
Hemant Banavar
>> Thank you so much for having me.
Gemma Allen
>> I'm Gemma Allen here at theCUBE Studio at the New York Stock Exchange. This is Physical AI and Robotics, part of our NYSE Wired series. Thanks for watching.
John Furrier
Gemma Allen