The Latest Technology in Freight Transportation with Samsara

I'm so excited to be here for many reasons um and I appreciate Samsara um having me here. Two brilliant people to have this conversation with. Just a little bit background about myself. Um I've I've covered as a reporter and an author uh e-commerce and retail for about a dozen years uh largely the intersection of technology and retail. Um a lot of time that's meant focusing on the consumer side of things. Uh now at my new publication The Eisle, AI's impact on online shopping, on recommendations, on consumer search. But what often is dismissed among the sources and companies I talk to is the hard parts happening behind the scenes once you click um purchase and once you um step away from that maybe that AI agent giving you a product recommendation and you go on and actually complete that um before it shows up at your door. So um it's going to be a fun conversation. Angie, I'm going to start with you real quick. Uh you just came out with some very important research that I think would be relevant to a lot of people in this room. Why don't you give us sort of the top two or three major findings and then we can jump off from there? >> Awesome, thanks. Um great. So just a little bit of background also um Angie Katerla, research scientist at MIT's Center for Transportation Logistics. What we do at CTL is we work with companies to try to understand what are their issues within transportation supply chain. Um and one of the things that kept coming up for me was AI, right? And digital technologies and all these new technologies coming out all the time. Um and I had this question of well what's actually happening on the ground, right? So there's a lot of talk about these these end-to-end solutions and things like that. But I wanted to understand what is actually happening. And so because we have great interactions with uh with companies, with partners, I decided well let me go out and ask. And so, I interviewed a number of of folks from um all industries, right? From manufacturing, food, retail, um and those that kind of have their own assets in transportation, those that outsource, 3PLs, 4PLs, all sorts. Um and I was asking them, what do you do in in with technology in your transportation process? So, from um the procurement to the forecasting to the actual assignment of of providers to measuring and tracking and things like that and then closing the loop and and seeing how that all ties back. Um and so, we can get into some of the details, but I think that a couple things that came out for me was that um the the implementation of digital technology, so it wasn't specific to AI, it was kind of all technologies. Um it's it's kind of step-wise. So, it's not this big transformational process that a company's going to go through and say, you know, we're going to change everything. It was very much like they're very problem-specific and here's a problem within our our our processes, how do we implement some type of technology that automates it or improves some efficiency. >> A refreshing point, by the way, for someone who spends a lot of time focused on consumer technology companies where often we see even the best companies develop uh products in search of a problem that may or may not exist. So, I'll let you continue, but um starting there seems like like the thing that makes the most sense. >> cuz I think a lot of folks are wondering, you know, should I be investing in in this hype? Is it a hype? Um or is it something that's really going to add value? And so, be a little bit more cautious about how they're implementing. Um the second thing that was also somewhat surprising was that um you know, Excel, email is still predominantly the way that a lot of transportation is happening. Um and so, the question is, why is that? And I think currently that's because there's um everyone knows it, right? Uh there's a lot of new technologies that are out there, but I think there's the the um challenge of actually implementing and getting getting your folks to use a new technology or use a new app or a new process. Um so that change management is very slow today. But I think that the last thing was that, you know, the biggest bottleneck still is data quality, data aggregation, um data is siloed across different functions within the company. And um who owns it, how are you filtering for things is still the main thing that's coming up across all of my interviewees. >> Um I don't know if you have any reaction to and anything Angie just talked about there. We're going to dive into um some of the stuff you're doing here specifically, but I'm curious for your thoughts on any of those takeaways. >> I think we see that with our customers um not from a research perspective, but from an anecdotal perspective. Uh you know, our customers are busy doing really important work. It takes time to adopt, takes time to actually do these things. So being practical is kind of at our core ethos. We we when we listen to customers, you kind of hear about a dynamic range of where people are at in this journey. There are folks that are getting started. They've just digitizing today. There are folks that are, you know, pushing the boundaries of what you can do with AI, but it's very tactical. And it's to solve a specific problem. And I think um the when we build products, we do this in concert with them to make sure that we're actually solving meaningful problem because anybody can build a product. But building the right product is much harder. And so I we we see this in and out and it's it's it is a journey. Uh we see it across the journey not just from sort of um digital transformation, but like which assets are you going to transform? And then what problems do you solve for those assets? And then okay, we solved this one. Now how do we go to the next one, the next one? So it is definitely not a step function. >> There's so much talk in both the public markets and just technology in general right now about productivity, right? Productivity ROI when you're talking about AI investments. Um and that often leads to discussions of layoffs, cutting staff, um finding more efficiencies. I'm more curious like where humans still have value. And I'm just I'm I'm not just talking society at large, but which is another question, but in in businesses and in the type of businesses that you were surveying. So, I'm curious for companies that are integrating some AI solutions, like where is the human just paramount and not being replaced? >> Yeah, I think that was one of the main takeaways was that humans are still in the loop in so many ways. So, first I'm seeing AI technologies being used as kind of an analyst's tool not to replace them. Um it's helping kind of understand, well, what are the things that I can um that can help me understand my job better. It's helping um you know, be better at looking into the the data or summarizing. But, in terms of actual decision-making, that's not where AI is going to be at least today is not being implemented. Um so, there's this this you know, at critical milestones and at critical steps, folks really wanted a human still in the loop to say, "Okay, am I you know, gut-checking what the solution is saying? Or am I gut-checking what the recommendation is?" Um and there was also this element of making sure that what the AI is recommending actually makes sense to the people that are it's being recommended to. So, I was talking to one manager and he said I remember he said, "You know, this this solution that was being provided to me showed, you know, seven different solutions." I was like, "Don't show it to my people cuz they may think you're telling them to do all of this." So, they're still trying to figure out how AI can help make decisions, but still have that human be the one that makes the decision. >> Was there Was there any sense in the surveying of of folks being overwhelmed on where to start? And and if so, I'm I'm I'm curious if there are any takeaways about, you know, best practices. And and I know one of them is just seems like look for an actual problem. And then what are the tools to solve it? But, I'm I'm curious if there anything there to dive into. >> Yeah, I think the um so, it was find the problems that you need the most help with, right? Um and see if there's a solution there. The other thing was there's certain areas and you know, I was specifically looking at transportation, but there was specific areas where a some type of digital technology made sense. So things that are easily automated, right? You can think about in kind of the transportation in your shipments, right? Across your network. There is about 80% of the lanes that only cover like 20% of the volume, right? That's that's difficult stuff, right? That's where there's maybe a manual input that's needed. That's where there's there's inefficiencies, uncertainties. That's where, you know, there's something can go wrong and it probably will and that's where humans probably need more manual input. On things that are a little bit more regular, on things that are more consistent, that's where AI automation, auto tendering, things like that are working really well. And so finding areas where, you know, it's it's a it's a process that's pretty well known in your in your organization, that's maybe a good area for technology. >> Dynamic pricing. >> Mhm. >> Big conversation point on the consumer side of things in retail and e-commerce, obviously. With some companies, I don't know if any of you follow this, but company called Instacart, which is grocery delivery, they got sort of caught a few months ago in doing dynamic pricing. Same same product, same store, different customer, different price. Um different flavor of this obviously in the B2B world, but what what did you find or what came up in conversations around where dynamic pricing doesn't does not make sense right now? >> Totally. Um so there's a couple elements here. I think the last 8 to 10 years what a lot of our work has been on at at MIT has been what what transportation should go through a contract, right? So that's very stable demand, contracts make sense. And what should be more of a dynamic kind of transactional spot type of transportation. Um and we've talked about portfolios of spot versus contract for for forever. Now we're starting to think about well, the stuff that should go to a spot or dynamic price. Typically is like I said that that, you know, low volume inconsistent lanes, those, you know, 80% of lanes that's low volume. That should be a more dynamic price. Now, the question today is well, what are the mechanisms by which you should be having a dynamic price. So actually this is some new research that we're going to be doing over the next few months and having some some round tables at at MIT about is from the shipper or the carrier perspective, how do you actually utilize potentially agents or things like that to have an algorithm that backs what your pricing might look like. So should shippers be setting the price? Should carriers be setting looking at the price? Auction mechanisms, things like that. So I don't have an answer for you now, but maybe six months from now >> David, let's talk a little bit about um tracking label announced. People excited about that? >> Yeah. >> All right. Wow. We're ready to party tonight. Tracking labels are for everyone. Um why is why was sort of now the right time versus [snorts] a year ago or two years from now? >> Yeah. So um Tracking label, just a reminder, is a Bluetooth-based uh disposable tracker for shipment visibility. And I think you know, tracking shipments is not new. People have been trying to track shipments and tracking shipments for a long long time. Today, the state of the art is roughly barcode scanning. So at a cross dock or loading dock, somebody or a machine literally scans a barcode and we know where that thing is. Um And the the challenge that our customers face with that, and I think our customers' customers face with that, is that those barcode scans can be super sporadic both in time and space. So you might have, you know, most recent barcode scan from several hundred miles ago and several hours ago. And so the question is like, where is it right now because I have a critical shipment that needs to show up. The landscape kind of looks roughly like RFID on one side of the equation and cellular connectivity on the other side of the equation. It's sort of landscape that our customers have have explored. And RFID is super appealing for certain applications. Uh very low cost tags, so everybody gets excited about that. But there's a CAPEX component here, which is really really burdensome. And frankly, I think only maybe the top one or two customers can really go implement something this saving. Notably, UPS just put a really uh tremendous capital expenditure towards RFID scanners. Nonetheless, RFID still has these challenges where you have to be in close proximity to an RFID reader in order to have visibility. And so, um one of the challenges is shipments fall off the back of the truck. Uh literally and proverbially. Now, the other is that the spectrum there's there's cellular [snorts] connectivity and GPS-based devices, which are ubiquitous and robust, but expensive. And so, people have to be super judicious about where do they apply that technology? And so, Bluetooth has been something people have kind of naturally gravitated towards because it's relatively low cost. The challenge is that you need to have a network. Uh and what's happened over the past couple years is that Samsara's network has been deployed to real scale. Um and just for context, our network is comprised of, you know, millions of buses, bulldozers, uh trucks, trailers that are in residential areas, they're in intermodal yards, they're in airports, on GSE. And so, that that network is actually what enables a product like the track labels. That's why now is possible and it wasn't even, you know, 2 years ago. >> I know how much companies love talking about limitations of new products, but um we we we have to go there. Like, what should a What should a a customer who's thinking about um engaging and and using these tracking labels like know about where maybe they do and don't make sense. >> Yeah, I mean, I there's a couple things. So, first of all, the the product is still warm, right? I mean, it came out of the oven yesterday. So, um whenever you launch a new product, you're going to learn new things and they're going to see new stuff. And I think one of the fun things about our customer base is so diverse, they just get pulled into a thousand conversations that I can never thought about that. Um because you you would never have thought about it that that impetus. Um a couple of the obvious ones are the Samsara network is where Samsara is. And so if you're North America and Europe, you're in business. Um if you're trying to do global shipping, you have to sort of put some dedicated infrastructure in place to to take care of that. The other one though is um you know, we're really excited about this product. It's a brand new and like any new technology, it's going to scale with cost over time. And so at least today we view this as a product for critical shipments. And we view critical as either really important in time and must be delivered otherwise there's significant downtime and cost. So think about, you know, a data center being shut down because something's missing. Uh or super high value and prone to theft. So that could be scrap metal. That could be um you know, expensive jewelry. Like all sorts of things you might imagine. Kit Kat bars uh most recent one. >> So saw a couple of those. >> Yes. Yes. So so those are kind of that that where we sort of think the sweet spot is. And then as you kind of get out of the edges, there's some it can probably work but we need to partner together a little bit. >> Is there anything you learned during this process of of your team building um about cargo theft that maybe was either surprising or or or might help folks who've um been challenged by uh sort of the ramp up in in theft over the last few years? >> Yeah, I mean I think maybe the most surprising thing is just how you biquitous theft is. Uh and frankly how sophisticated it is uh and how it just it's everywhere. I mean you you read the headlines about this stuff, you probably get to read about maybe 1% or less than that of what's actually going on in the real world. Um so and and and the more we dig in, we've spoken to experts on this stuff. Like it is a sophisticated operation. There are real organized crime rings out there that are participating I guess we can call it an ecosystem. For sort of weird that we'd say that but it is sophisticated, it's organized and and it's tactical. Um and I think that the organizations that are really proactive about this are preparing against that stuff. They're taking measures. Yes, they're tracking their cargo. Yes, they're tracking their vehicles, but they're also employing workflows to avoid double brokering. They're really thinking about sort of the holistic picture here. >> Um last thing on for now on this. What what are the keys over the next few years so that the cost drops down that it that it becomes something that is not just maybe the most critical items, but um sort of wide widespread either inside an organization or or just in you know, across a sector. >> I mean, the key is volume. So So it's an electronic product like any electronic products, there are economies of scale. You know, inside of our our device there is a Bluetooth radio, there's a battery, there's some chip set. Those will come down in cost as our volumes go up. And then manufacturing techniques will also improve over time. So I think we'll see that, you know, over the next two, three, four, five years we can scale costs, which will be fun. I think our our product today is a location-based products, but um we like to future proof. Maybe that's what I'll say on that topic right now, and I think you can expect to see over time more sensors kind of integrating [snorts] with this. The kind of interesting thing about the Samsara network is that it really has evolved over time. When we first launched it, it was for location. And then what we've seen over the past couple years is we're using for location sensor data and location sensor voice data. Now we've also added the cameras to that network as well. So you'll see the hardware evolve commensurately with it, and the network can support that kind of stuff. >> I actually I have a question to ask you. Um so one of the things that that have come up from the research was about this like the data quality and then integration and the infrastructure underlying all of that. And you guys have tons of data, right? How are you managing all of that and then being able to share that with your customers to make it valuable? >> Yeah, so I mean, if you think about our typical customer, they've got a fleet of vehicles, fleet of equipment, Uh, and we collect a ton of data off of those, whether it's geolocation, fault code information, utilization, whatever it might be. And we really build on top of that. So, we aggregate that data into things that are useful. Nobody wants to see an individual GPS data point. They want to understand utilization or productivity of that asset or the health of that asset or whatever it might be. Um, so we we build that out natively in our cloud platform. And then I think the sort of interesting new innovation over the past couple of years has been that we've been baking more and more customer uh uh customization in with trip data AI into the product so that customers can just go answer their own questions and make sense of this. >> Cool. >> Um, so you can imagine, you know, in short order asking which shipments are at risk because of the vehicle it's on has a active fault code kind of thing. >> you're taking care of kind of that background data >> right. Yeah. Yeah, we're I mean, our objective fundamentally, I think, is like we want our customers to enjoy their morning cup of coffee without grinding away at other things and multitasking. And we want the system to go handle the grind so that they can do what they're great at. >> Do we have other Yeah, question over here? >> My name's Morgan Parrish. I work for Spartan Companies. We're an energy construction company. We're building data centers and oil and gas for BP and >> I've heard about those. >> Um They're all over. This is the largest one just outside of El Paso. But uh a lot of things that we build that are out in the middle of nowhere, so this network is really helpful with the you know, 500 600 trucks we have in that area. When we install some of our equipment, when we leave those job sites out in West Texas, if you've ever been there, uh no one's there to protect it. And so, this would be great to be able to to do that. >> Can you be the only ones to read those Bluetooth devices or are are is there some type of protection so that it's not detected by thieves or other groups? >> Oh, I see. >> Is there some technology that only allow those that are printing and scanning and activating to read those? >> Yeah, so I mean, the way we think about Bluetooth security in general is we we don't we take a pretty different approach to consumer-grade Bluetooth. So, we baked in security and anonymity into that Samsara network from day zero, you know, 2 2 years ago. Uh ultimately, if something's in the air, a motivated thief can listen for it. The question is, how do you figure out what that is >> [snorts] >> and trace it down, all these kinds of things? And we've taken significant measures to make that pretty difficult. Um And so, you know, what I can say today is we have asset tags that use the same technology. Typically, when we see those things being uh stolen, it's inside jobs. So, it's folks that know actually where those were installed or what they're looking for rather than a third-party kind of independent thief. So, you know, unfortunately, theft and loss is a cat-and-mouse game. We think we're maybe a couple steps ahead right now, and we're going to continue to invest to make sure that we stay a couple steps ahead. >> I I just have one follow-up to that. So, is it So, someone may be able to detect if they're committed enough, the the general area, but knowing exactly or is that not what you're saying? >> Well, I'm saying that, you know, if you if you take out a wireless scanner and you listen, you will see radio transmissions in the air, no matter where you are, no matter what the device is. There's nothing It's electromagnetic wave in the air, you can detect it. How do you go pinpoint something? How do you know what that thing is? How do you determine whether that's a Samsara label versus anything else? That's a different question. So, we try to make that step as challenging as possible. >> Um my name is Kelly Sutherland. I'm here at Samsara, but I really I have a question um for David, and that is What are some good use cases that you've seen from customers? It's been in beta for a little bit. So, what are some good use cases where you've actually been able to find something unique or that was helpful for our customers? >> Yeah, I mean, so again, the diversity of customers means that we just see a lot of stuff, but we we we have talked to chemical distributors that are looking at one-way shipments of mission-critical chemicals. If they're not at the job site the next day, things get shut down. So, that's been a good use case. Uh we've seen super high value shipments where people just need visibility on them. That's been a good use case. We've seen uh pharmaceuticals. We've talked about biological samples. You can imagine if that biological sample doesn't make it to the lab on time, you have to go take another biological sample. So, a real cost associated with this. Um we've seen auto transport. Uh so, car carriers, for example, they want to track a Ferrari from, you know, dealership to dealership, something like this. And then there's stuff involved. So, we literally, I mean, I won't say we've seen it all. I think we've seen 1% of what we'll see, but we've seen a lot. Um but really it is all about criticality. That's kind of how we think about it. It's like, does time matter or does dollars matter? And sort of what's at risk? >> Um Johannes Fieger and I work at Samsara here. Um I had a quick question for um for Andrea Corcella. Um when you did that study and you identified data being one of the constraining factors, right, in the space, did you control for what kind of technology or systems they had in place already? It's purely selfish question from a Sorry, it's that [laughter] blind. Is there a differential >> I love being up front about that. >> Yeah, no, that's fine. >> [clears throat] >> Um yeah, so so this was basically just interviewing folks and asking kind of generally what's going on. Um so, not a, you know, a deep dive into into the types of technologies. Um but I did hear it from across the different interviewees that were from all sorts of different companies. Um so, it can it can come from the the transportation managers, it can come from different industries, it can come from the the transportation providers. Um I've heard it and in fact we were talking before this session, um before I was a as a research scientist at CTL, I was um working with the Port of Rotterdam on digitization of their operations. And the data issue was a problem there, too, right? So, it's it's been a consistent issue for digitization in every setting that I've looked at. >> Um one more on the theft question. Um throughout the building of of this technology, uh did you learn about or um or could you recommend are there any complimentary technologies or processes that you feel like the best organizations maybe not a UPS size but um below that are utilizing to try to sort of come at this problem from various sides? >> Yeah, certainly. I I I mean so our customers typically start off tracking their vehicles and that that's actually really helpful to do this because now we can link is that shipment on this particular vehicle. We can do that sort of detection automatically. Um a lot of your customers have our multicams and safety cameras and in that context around the shipment can add a quite a bit. So, we can see if that shipment is stalled, where is the vehicle, what's going on around the vehicle. Cameras. Um and door monitors. We have door monitor product that customers will use and is that door being opened outside of, you know, a known geofence or a safe area, these kinds of things. Uh many of our customers in Mexico have done a tremendous job at identifying risk zones and looking at operators going through those risk zones and making sure that it's really quick, nobody's stopping there. So, there's a lot of measures that folks can take and um you know encourage customers to talk to one another and kind of learn best practices, but there there's beyond tracking a shipment, you can do much much much more to make sure that stuff's getting from point A to point B. >> Um want to switch gears just a little bit in this, you know, last 15 or so. Um in the coverage I do at at readtheaisle.com, my new publication there's a lot of talk around on the consumer side of things, the idea of agentic shopping. So, AI personalization that will eventually know you so well that it will help you make purchases or maybe carry out purchases, it's some types of purchases in your life on its own. There's a lot of discussion about that among the retail companies and e-commerce companies I talk to and the AI labs, not a ton about what happens if those systems ever meet sort of agentic supply chains or really AI-driven supply chains with few humans in the loop. I'm I'm asking us to future cast a little bit. I'm curious what sort of problems sort of folks who sit more on the consumer side should be thinking about as they're trying to maybe in the most forward-looking organizations plan for these days. Angie, I don't know if you have thoughts on that. >> Yeah. I For me, this is sort of a question that is answered by if we look back to like blockchain and how that was supposed to like revolutionize supply chains, right? I think that the issue when it comes to supply chains and and transportation is that there is a physical truck that needs to show up. There's a human that is driving that truck. There's information that needs to be you know, shared with them. Um there's real rubber on the road, right? And I think that's where so many challenges can come into to making this There's sticking points. Um so, you know, thinking that like what are all the steps and the complexities that make it such that the product that you're ordering has to come from warehouse, has to get picked by a warehouse worker, put into a a box, right? Then a driver needs to show up, gets to put on the truck. It needs to not get lost along the way. Um so, many things that physical aspect of it. It's not just a like a digital computed type of um transaction. There's physical aspect to it. >> Hi, how's it going? Uh thank you all for coming out today in the presentation. My name's Milan and I work at Rhyanous. We're a bunch of software nerds essentially, so >> Love it. >> this is kind of right up my alley. Um I just was wondering uh question for David. Um you mentioned some of your like a customer in Mexico uh did a good job of identifying, you know, high-risk zones. Um can you tell me a little bit about how that works? Is that like a geofence on the system? And then if the driver kind of arrives close to the area, he'll be told not to go that way or does it go to like maybe the fleet manager who reaches out to the driver? >> Yeah. There there there are a couple ways it can work. Um in this particular case, the customer may have geofenced a place where there's known to be um particular crimes. Uh you can kind of imagine what those might be. So, uh either either they can route around those areas or when they go into those areas, they simply set policies like cannot stop in this area. And when they do stop, you can imagine sort of the automations framework that we have and the agents kind of kick in and and help take over and scale the human operation uh behind there. >> The AI agents are helping us right now with the geofence located in all the risk zones on on the country and they are talking to the driver to not stop and remind them that it's for their safety and to get back home with their family. So, it's also talking to them and reminding them the importance of doing that. So, it's pretty good. >> I I think you asked a question earlier about AI and humans. And I I I think this is a good example. Like we we deal with physical AI, which is a little different than I think consumer chat GPT stuff. Like Anthropic put out one of these star charts of showing industries that are going to get disrupted by AI. And if you kind of look at where they're forecasting at software engineering, finance, sort of maybe corporate office jobs, physical AI is not going away with humans. And I think this is kind of the human AI interaction that we sort of foresee and how you can scale teams and actually augment the people to do more and run these operations more efficiently, which then of course helps the supply chain and everything else around it. But this is the kind of example that I think we sort of forecast. >> And is that is that AI agent um is that commun- actually handling the communications with the drivers or is there is there someone else involved? >> The AI agent. We activated maybe 3 weeks ago and we're testing it. Whenever they stop on on side of the road and they're not supposed to stop there. The AI agent calls them and tell tells them, "Turn off the radio. Is it safe to talk to you right now?" And they have to answer. And then they start a communication. We also can dial uh through the camera and talk to them so they don't have to grab their cell phones. So, yes, pretty much the AI and also when it's needed we call them to remind them. >> You can imagine you could do this with people but you'd have to have an entire staff of people to make these phone calls, observe where drivers are stopping, all sorts of stuff. So, that's kind of a the special thing here is that the AI gets to do that work on behalf of the people. >> Yeah. It's pretty much great because in Mexico there's not only one reason. It's multiple and it's all around the country. And we have almost 400 trucks driving each day and we have a a team of professionals looking at that operations but it's it takes too much time calling each driver. And maybe they are on traffic and we get the alerts. So, the AI is helping us like remind them, "Don't stop. If you're in anything, press the panic button and we are here to help you." >> Mhm. Have you got I'm just curious one more on this. Um have you gotten feedback yet from the drivers? I mean, it doesn't sound like it's their choice but I'm curious what kind of feedback you've gotten or observed. >> The first time we activated when I was we were testing this uh the the some drivers responded like "Why is it talking to me?" And so some said, "Oh." They started they started laughing and he was on a cell call a cell phone call and he's like, "Oh, the camera is talking to me. It's very cool. I'm going to start talking like uh two ways. So, they some drivers are are taking it on the good way because >> them to remind remind them. So, it it takes a lot of job from our people and Sentinels center we have looking at them. >> I was going to say a little bit about the the driver experience, right? I So, I liked your question about, you know, how are drivers experiencing these new technologies? Cuz, you know, from from our perspective, it's helping them be safer, be more efficient, do their jobs better, right? Um but there there is an element of, you know, they're humans and it's a very one on the one hand it's a very isolated job, but it's also sometimes drivers like that they have the freedom to kind of do do what they they want to, right? When they're when they're out on the road. And so, you know, finding this balance between how how do we make sure that it's it's helping them, they understand that it's helping them, while also recognizing that maybe there's might be some pushback. >> We we you know, when we first [clears throat] put out dash cams, um I don't know, 8 years ago, I think a lot of and maybe customers in the room had this experience, but drivers would look at that dash cam and say, "What is Big Brother doing spying on me?" And then within a week, invariably somebody's exonerated from an accident. And immediately the driver sentiment shifts and understands that this is not here to spy, it's not listening to them, it's here to help and get you home safely to your family and protect your communities. And these organizations, I mean, I think as a consumer, I don't think safety's appreciated the way that our customers appreciate safety. And you're dealing with 10,000 drivers, it is a completely different ball game than when you're just driving your Honda Civic to and from. And so, um and these organizations have tremendous responsibility in their community. I mean, tremendous. They're Their names are up everywhere. Like these are you know, stewards of of of the citizenry. So, they take it really seriously and I think ultimately, um the adoption curve on this stuff has been extraordinarily quick. Extraor- I you know, and people talk and drivers go to different organizations, and I think at this point it's I'm curious to hear if anybody else has had this experience, but we see as soon as people understand it's for the safety of themselves that it is it's a no-brainer. >> I think we have a question up here. >> Uh Thomas Watson, FreightWaves. One of the things looking at adoption rates of this technology, uh, as we're starting to see at least in our side of the freight cycle turn, the demand for drivers is going to continue to rise. Do you think that this will become part of a fleet's toolkit as a differentiator? You know, for example, it used to be you get like a brand new truck, you get home, but are drivers now going to start evaluating these companies on these little things where, oh, yeah, you're looking out for me as well because it's my points on my license in addition to your points. Do you think that's going to be one of the trends that we're going to see moving ahead compared to times where when we had a crunch for drivers, that didn't really it wasn't on the table. >> I I I I think so. I I mean, I don't know exactly how it will manifest within the drivers, but we have driver recognition. I mean, I think one of the challenges I hear about from our customers is how do we maintain the best drivers in our organization? How do we coach kind of the middle? And then, how do we make sure that, you know, for the super risky drivers, we deal with them one way or another. Uh, and I think that, you know, we do a lot of positive recognition, whether that be a monetary award, whether it be, you know, a gift card, or just a shout-out, or a kudo. And we've seen a lot of customers do a really good job gamifying uh, positive behaviors, and therefore keeping a culture of safety where it's really rewarded and valued. And those I mean, I don't know if you were here at the keynote, but we had we showed a video of UNFI, and the driver's speaking he says it's the best job he's ever had. And that's not random. That's because UNFI specifically is invested in making this a reality for their community of drivers. >> I'll also add I think Thomas you make a good point that we're going into a new tight market, a constrained market, where the the reasoning for it and the underlying structure of the market is a little different than it has been in the past where it's very much driven by a capacity issue, like the capacity side, the supply side versus the demand side. And so, yeah, being aware of what is actually going to bring maintain drivers, retain drivers, um, I think it's going to be at the forefront of a lot of a lot of areas. >> Any final takeaways, um, either based on your research or a discussion we had that you want to make sure folks are thinking about or as they go back to their organizations next week. >> Yeah, I think so for me I think the one of the things that I'm coming away from both this session today's today and yesterday's events and the research is around how what are the real problems that need to be solved, right? And so technology AI can really help with that. I think there's a lot of things out there that are like really exciting for a lot of people that are probably going to take away from from this event. Um and where I think that the future is going is a little bit of not just how is AI and are these technologies a helper and you know helping me understand the questions I already know to ask. This is one of the things that came up a lot was you know the future looks like how is AI going to help me understand questions that I didn't even know to ask, right? So how is AI >> you versus expecting you >> intelligence, right? Um things that you know maybe I don't know to query what what I don't know, right? Um and so that's I think where the future is going to >> Needs to be a lot of trust there though I would assume. >> Yeah. >> I'm curious how much interactions on the consumer side bleed over into someone's trust of systems on the business side. I don't know if you have any research on that. >> I you know I don't have anything to to make a statement on that today. >> Great idea I just gave you. David >> Yeah, I I think maybe I think if you were to ask Gemini what does a supply chain look like you get a photo of a container ship with a bunch of containers on it and you kind of that's what people have in in their supply chain. I think what I've learned over the past year in building this product is supply chain is actually much more complex than that. We have customers that deal with supply chain that could be taking building materials to a job site. That's supply chain. And if you think about kind of the steps there are vehicles, there are humans, there's the maintenance of the vehicle that has to get you there. It's not just about planning, it's actually about the full operationalizing of this. And I think what's kind of fun and exciting to sort of think about not in the long term but I think really in the next few months is how do all these things come together to really give you a holistic picture of how these organizations are running. How do you actually execute the supply chain? That could be again, you know, pharmaceutical production to hospital, but it could be GPUs to a data center, and it could be, you know, car transportation, anything in between. And so, you can start to see how, okay, how many vehicles do I need? How many drivers do I need? Which ones need maintenance? How do I actually ship this package from point A to point B? And, you know, we think packages, we think tan boxes, but we should really be thinking about so much more than tan boxes. We got to be thinking about, you know, the copper wire and all this kind of stuff. So, I basically think we're kind of at this confluence now where you have visibility on all these things. You now have this AI that can sit on top of and make sense of it. Um and so, I'm just I'm super excited about what 6 months now from now looks like as far as decision-making and just efficiency in this uh in the world looks like. >> I think that's all the time we have. You guys almost hit the zero right on the dot. Let's clap it up for my two fine guests tonight. [applause] Thank you, guys. Think Think we're all set. >> Cool.