From Wearables to Insurance: How Kinetic is Revolutionizing Workplace Safety

Speaker A: Budget overruns, brick devices, data breaches. Building connected products is hard. Welcome to over the Air. Sharp, unfiltered conversations with executives about their IoT journeys, the mistakes they made, the lessons they learned, and what they wish they'd known when they started. I'm your host Ryan Prosser and, and this is Bill Brock. Welcome to over the Air. Are you struggling with in house fleet management? Have your ansible scripts grown out of control? Has a Docker first deployment strategy left you needing more? Oh, it's not just you. At parideo, we work with software teams at hardware companies so they can focus on their products and relax on the infrastructure. Are you interested in learning more about our device centric CI CD solutions? Talk with an expert today. Perhaps. Welcome to the over the Air podcast Today. My name is Bill Brock, CEO of Perio, and today we have Haytham, uh, co founder and chief strategy officer of Kinetic. And uh, welcome to the show. Thanks for coming on.

Speaker B: Oh, thanks Bill, for having me. Uh, excited to be here.

Speaker A: Absolutely. Um, yeah, we're excited to have you. And for those of us who are not familiar with Kinetic, could you just give us the 10 second elevator pitch?

Speaker B: Yes, yeah, absolutely. So really at Kinetic, we have a mission of sort of trying to reduce workplace injuries and we've built a bunch of technologies, um, that can, uh, help, you know, workers, mostly frontline workers, um, avoid or prevent getting injured. And so that's been our focus from the beginning. And um, today that has sort of evolved from, you know, selling, uh, devices and IoT devices to becoming an insurance company, um, very much focused on prevention of injury.

Speaker A: So what are these very, uh, interesting background? Um, you started in hardware and devices and then migrated to insurance. So what, what is the hardware? And, and tell me a little bit about that story.

Speaker B: Yes, I'll tell you a bit about the story of sort of how it started. So I'm one of the co founders, there's two of us. And um, and really the way it started is, you know, I, I grew up with my mom, she's a nurse. And um, and she just got injured a lot. A funny sort of fun. Not, not really fun, but an unusual fact is that nursing is actually one of the most injury prone jobs out there. So it's one of the most dangerous jobs. And um, and that's just because it has a very high injury rate. And that's mostly because nurses are sort of moving patients, they're moving equipment. And so with my mom, I saw her get injured a lot and really, um, you know what it made me Realize is that when you get injured at work, it doesn't just affect your work life, it affects your entire personal life too. And so you know, how you earn money and the things you can enjoy outside of work and things like that. So I really had that problem of, hey, you know, there's a lot of people who just get injured, um, uh, and it affects their lives. And the, the approaches to avoid those injuries are still very rudimentary. So we really. I, you know, I sort of had that in the back of my head when I met my co founder. And my co founder happened to be an electrical engineer who uh, worked at IBM and he, he um, was just very interested in wearables. And 10 years ago now, you know, I don't remember, but you know, Fitbit was going crazy and first Apple watches were coming out. Um, and so really what we, we wanted to do is say, all right, could we build some sort of wearable that could help, um, frontline workers who do a lot of manual labor to reduce their injury rates. And that was really how the company started, uh, ten years ago.

Speaker A: Uh, so, um, very interesting background. Where did, where did hardware come into the mix here? So you, did you develop your own wearable? Were purchasing office shelf solutions. What, what did you guys actually do?

Speaker B: Yeah, so I mean really, you know, we sort of started when we, when we decided, okay, we want to reduce workplace injuries. Um, you start looking into what are the, what are the types of injuries that uh, employers, employees sort of, um, get. And what you realize very quickly is that there's a couple of elephants in the room, especially with workers who do a lot of manual labor, sort of frontline workers. And one of those is sort of musculoskeletal type injuries. So strains, sprains, you hurt your back, you hurt, and ankle, um, those are extremely common. And honestly, like the number of injuries doesn't really go down. So it's one of these things where it's just sort of, they happen on a pretty recurring basis. And uh, there hasn't been any, I would say, successful, real successful strategy in bringing these numbers down. So just how fatalities have gone down and other types of injuries have gone down, these ones really haven't. So we sort of realize, all right, not only are these pretty prevalent, but they're also very expensive. And so, um, that's when we sort of started out. How would we solve those problems? And most of these sort of musculoskeletal injuries happen because people are doing pretty intense physical work, but they're using their bodies in Ways that, um, put them at risk of injury, right? So if you think of you lifting a box up and you have to lift 500 boxes a day, if you use improper posture of body mechanics, um, over time, your body is just going to, to seize up and eventually you're going to get injured. Right? And so really what we wanted to do is say, all right, could we coach workers to use better body mechanics? And if you're using better posture and body mechanics, you are less likely to get injured. Your body will withstand, you know, longer periods of work time. And so, and so that's really what we set out. And, um, and, you know, if you think about it, all right, well, how am I going to measure people's body mechanics in real time and, and, and let them know that they're doing something either properly or. And that's really where the hardware came. So, um, we wanted to measure how people were moving and really just give them sort of a gentle nudge, almost like as if they had a coach on them to say, hey, you know, you've moved in an improper way. Why don't you, you know, pick up that box using your legs? Or why don't you turn your body instead of twisting your body? Um, and so we ended up, well, we ended up, you know, realizing that sensors and hardware was the way to go because it was the only way to really pick up that information. Um, and we ended up designing. I heard the. Here in my hand. We ended up designing, uh, something that looks a little bit like a pager. Um, and what it does, it goes on your belt. And so, um, it's able to sort of measure almost your full body mechanics, uh, just based on, uh, the motions of your hip. Uh, so that was really where sort of the, a lot of the algorithms and a lot of the innovation came in. Not so much sensors in the hardware because they're pretty standard off the shelf components, but it was really all right, how do we use those to sort of recreate how someone is moving in real time? Uh, that's where we really sank a lot of time in terms of technical, um, development.

Speaker A: Yeah. So what did that, uh, what did that early product development look like? Were you just wearing, uh, these things on your belt and doing all sorts of crazy stuff and, and hitting a button when you were doing something compromised or. Yeah. What. Tell me about this.

Speaker B: Yeah, something like that. I mean, so, so it was actually pretty interesting. You know, when we started, um, you know, we, we mostly wanted to measure how's the back moving? Right. Because that's really, what, what, uh, what tends to get into the most? And so we didn't start off with something on the hip like this. We started off with something that you would strap onto your body. And so I remember very, very clearly. So we, we would take one of these back braces that you typically see a lot of workers wear, you know, where they, especially when they have to do a lot of manual leverage. We would, we would put embed sensors in the back brace. But it turns out that workers actually don't like wearing back braces that much. So, so we, we got rid of that. Um, I don't know if you remember GoPros, but do you remember they. You could strap them onto your chest? So we, we took one of those and uh, we took off the GoPro and put our device on and uh, people referred to it as the bra. So we, we knew that that wasn't going to go down well. And um, and then we converted it sort of into a gun belt looking device. We're like, all right, or maybe, you know, it sort of look looks more, um, cooler in a way. And, and what we realize at the end of the day is, you know, strapping something onto people's bodies just doesn't work right. It's, it's, um, you know, you get sweaty, like, who's going to clean it? Um, there's just a whole bunch of things that happen there. And so that's where we ended up saying, all right, well, let's put it, see if we can put it on a belt, on a, on a waistline. And um, and that just made the whole problem much harder to solve, but it made the hardware component much more easily accepted by the workers. Right. And so, um, so the, the joke, uh, Bill, I like always to make is, um, uh, I don't know if you're a fan of Shakira or not, but she has a song called Hips Don't Lie. It turns out that actually it's very, it's very true that, you know, if you can sense the way hips are moving, you can actually infer how most of the body is moving as well. And so that's really what the premise of the device does. It says, hey, we, we put it on your belt and, and we can, we can sort of infer what your body is doing basically in real time.

Speaker A: Uh, is this why you moved to Columbia and just pursued the Shakira?

Speaker B: It's not the reason, but hey, it's

Speaker A: a nice, it's a nice side of me I'm seeing. I'm seeing some themes here.

Speaker B: Yeah, you know, the day she responds to my emails, uh, we're going to make it.

Speaker A: And we need, we need, we need some really high quality testing here. You have very fast moving hits. We've all seen it on tv. And yeah, Solaris is.

Speaker B: Yeah. So that's, that's really, you know, and to answer your question about like early product development as well, you're right. I mean what we ended up doing at the beginning is saying, all right, we hire, I remember hiring a warehouse, getting literally hundreds of people off Craigslist to do all sorts of tasks in the warehouse. And we would strap them up with sensors all over the body and then put this device on there. And really what we wanted to see is like if what this is measuring is actually close to what they're actually doing.

Speaker A: And what year was this?

Speaker B: This was in 2016.

Speaker A: Okay.

Speaker B: And so it was a while back. And so, so like, yeah, uh, edge

Speaker A: AI was not necessarily really a thing. You guys are probably doing a lot of cloud processing, flagging, tagging, like, you

Speaker B: know, you're absolutely right. It was, I say it was evolving at that time where there was a lot more happening, much more edge computing. So I remember actually, um, we got um, some early sort of sponsorship from intel who had come up with a chip called the Edison. I don't know if you remember that, but basically what they were doing is they had Bluetooth, WiFi, a bunch of like two CPUs on there, um, you know, great battery management. So, so they had really just come out with these chips which was sort of, you know, SOCs, uh, that, that were just really high performance. And uh, and so we were able to take advantage of a lot of those innovations to really make as much as possible run on the device. Because really the goal is we, what we ultimately do is we make the device vibrate if it detects that you're doing a high risk movement. M and not going to talk about like what, what a high risk movement means, but. And so it has to be in real time. So any delay, you know, if WI fi stops working, if you leave the facility because you're delivering, you know, boxes to people's houses, um, we don't want the ability to respond to a movement to depend on that connectivity. And so uh, we wanted to make everything as much as possible sort of work onto the device. And so we were able to take advantage of a lot of those new, new chips that were coming out that could really do a lot of the heavy lifting.

Speaker A: And what is, um, what Is battery life. What is kind of some of the compute considerations like where, you know, where are you strong? Where are some opportun.

Speaker B: It is, yeah, I mean it's, it's a really good, really uh, good question. So basically this device is a battery, right? So, so it has uh, that, that's really what has been the limiting factor. So you know, one of the things we realized pretty quickly is um, initially we spec this out, oh, eight, you know, eight hours, it has to last a shift. But um, but you realize pretty quickly that in warehouses, in factories where most of these are deployed, like people are working 12 hours, 14 hour overtime. Like it is a really crazy shift and people are working really hard. And so yeah, we needed a battery that could last, you know, 14 to 15 hours. Um, so yeah, we've really had to sort of put a big battery in there, which is what takes up most of the form factor. And so um, and you know, you know, could we be more efficient on uh, the chip itself and the algorithms we're running? For sure. It's just. Hasn't been a priority. Like we, you know, it's, it's hard enough to solve everything else. And so we're like look, if that's, if this form factor is acceptable then um, we just focused on other is outside of just sort of optimizing the device to be as small as possible or as battery efficient as possible.

Speaker A: And did you always start out with an insurance mindset or was it uh, I know you mentioned like preventing workplace injuries. Was this like the, the insurance component here? Was this a late stage revelation or do you kind of early on know this is the best way to monitor, monetize these technologies and this is how we can get it to market?

Speaker B: You know, it's um, no, not at all. I mean, you know, I didn't know anything about insurance when we started the company. Um, you know, after a while we were sort of thinking, hey, this might make sense for insurance company, this type of data. But we never really um, had insurance at the core of anything that we wanted to do. And um, and you know I always joked that like nobody as a child dreams of, of selling insurance, right? So it's, it wasn't, it wasn't like in the back of my mind it's like, hey, one of those dreams I one day want m. But what we realize pretty quickly, um, is you know, in the world of sort of worker injuries, there, there's two types of companies. There's companies that are very big, like, say, I don't know, like A Pepsi, a ups, a DHL and all these very large companies, what they do is if someone gets injured on their premises doing the job, then they pay for their injuries. So all the healthcare costs and they pay for sort of a percentage of the salary while they're out in. So initially when we started selling this product, we targeted those large companies, right? They're called sort of self insured companies. And we said, look, we'll sell you these because your injuries are going to go down and if your injuries go down, you'll pay less. So I'd say the return on investment argument was pretty easy to make for those large companies. Um, but then as soon as you go down to smaller companies, uh, that could have like 100 employees, 150, 200, um, they just wouldn't, they were like, look, I'm not going to pay for this because I pay for workers compensation insurance which costs a lot of money and so they take care of my insurance. Right. And so it was very hard to sort of get into those companies. And so at some point we realized, you know, the only way to get into a company like that is if we offer them insurance. Uh, so we could say, look, we will offer you workers compensation insurance and we will give you this for free, right? We will help you reduce your claims and your injuries which will be a benefit to us because we're providing you insurance that will be a benefit for you and your employees because you're going to have less injuries. Right. And so it felt like, hey, this makes a lot of sense uh, from a business perspective. And you know, workers comp is such an expensive insurance line that there is, there is room in there if you can reduce injuries to really, uh, to make a bit more margin. So that was where we realized that this made sense.

Speaker A: So what was that like shifting the mindset from a connected uh, product company and you're still a hardware enabled company but going from selling hardware to selling insurance. Was there like huge certifications or just a total mindset shift or you had to go get some fancy MBA CFO actuary person that you're like, it just, it's a totally, it's foundational change to the business, right?

Speaker B: Yeah, no, it really is a foundational shift to the business and thinking, you know, when we were selling to these large companies, we, we had just sort of enterprise sales people, you know, knocking on doors, um, going through a 12 to 15 month sales process to try to sell, you know, big box company a, um, you know, thousands of these devices. So even the sales motion we had was just completely different. Um, so about, yeah, in 2021, which is when we decided, all right, we are now going to try and get into insurance. And that's sort of where my insurance journey started. I didn't know anything about workers comp. Other than, you know, I had to buy for Kinetic. Um, and, and so yeah, really just became about learning what it is, what it covers, how do you sell it? And I think in the insurance industry the great thing that it has is that it has a structure that allows you to sell insurance on behalf of someone else. Right. So the best is, is a, uh, there's a very easy way to start without having them, you know, have all the regulatory compliance and all the money and the capital you need to become an insurance company. Uh, and we were very lucky that our early investors, one of our early investors was Nationwide Insurance Insurance. And so really, you know, we were able to make that transition because they were early investors, they knew the product well, they knew the impact it could have. Um, and they, and they said like, look, you know, if you want to sell this type of insurance, you can partner with us, you can sell insurance on our behalf. Um, and uh, you give these away for free. And they were very excited about, you know, seeing if this could get mass adopted, um, across small companies. And um, that's really how we managed to get started.

Speaker A: We actually had um, another company called Ting. Have you heard of these guys?

Speaker B: Hell yeah.

Speaker A: Yeah. And they uh, they were on the podcast years ago, um, one of our earliest episodes and I got a letter from State Farm. They do my home insurance. And it was like, hey, sign up for Ting. And I'm like, man, that is really cool to see this. Like, because it can be hard to commercialize hardware for sure. And it's cool to see these uh, long lasting like reduce risk plays. Find, find good monetization models with insurance companies.

Speaker B: It's very cool. Yeah. And you know you hit on an interesting point there, right? There's really two ways you can approach the insurance side. One is to partner with a State Farm. And then you know, say hey look, can you, can you distribute this to your customers? And um, you know, when we started we thought that that would be the way, right? We could try to sell into enlarged insurance companies. And um, and what we realize is, is that you know, the sales cycle is very slow. So large insurance companies, you know, really what we realize is that insurance companies are great at ah, investing the money they get in premiums, but they're not necessarily like innovative technology companies. Right there's very few of those. And so it's just very hard to get the right people in place to get them to really buy into the technology. And so I think it's happening a little bit in personal lines of insurance, like for example your home insurance or some telematics in like your car and things like that. But it hasn't really happened very much on the, on the business, like insuring businesses. So um, so that's why we realize, all right, if we're going to include this as part of insurance and really focus on prevention, we have to offer the insurance ourselves.

Speaker A: Very cool. What's um, what's like next for you from the product perspective? Is the, is the, the BOM pretty much at a stable place and you guys feel, feel good about the product? Are you looking to develop other hardware applications? What's uh, yeah. On the product side, what are you looking for?

Speaker B: Yeah, it's a good question. You know, we're very passionate about the product itself, the hardware and the software. But really, you know, what we realized as well is that um, we, we've making like the device has really had an impact on reducing musculoskeletal injury. So what typically happens is the device, you know, vibrates and tells you hey, you're doing this high risk movement. And so when someone starts wearing it, they might have hundreds of beasts to death. Right. Um, and then you start to see that over time that starts to go down. And uh, and as the number of these high risk movements goes down, injury rates start to go down as well. And um, and so we've had a lot of success sort of driving down injury rates which is really, you know, for us is very, very exciting. And m. You know, but as, as you start insuring these companies, what you realize is that musculoskeletal injuries, while it's usually the one of the biggest, um, injury types and the most expensive, it isn't their only uh, type. So for example, um, we ensure a lot of parcel delivery companies. So if you've seen my person who drops off packages at your home that you've bought over E Commerce and things like that, the number of times we see dog bites or slips and falls, especially with ice involved and things like that is incredible. And so what we've decided to do is to say look, we can't just really focus on musculoskeletal injuries only because that's just not the entire set of losses that or the tire set of injuries that these companies have. We've uh, got to sort of Create a platform where we can, you know, use lots of different technologies to, to address each one of these different types of injury types. And sometimes we'll develop them and sometimes we'll sort of bring a technology that already exists if it's in, if it's in a, if it makes sense. And really we want to be sort of that platform platform that offers this sort of menu of items depending on the type of injuries you have. And so that's really where we're going towards. Um, so we will continue to sort of build hardware, devices as needed. Um, but we're doing a lot with, for example, computer vision, um, because, yeah,

Speaker A: I saw that on the website. What's, what's happening there?

Speaker B: Yeah, so, um, so there's really two, two types of products. One is, um, that, you know, lots of these facilities, especially manufacturing warehousing, they have cameras already in their locations. So we can use those cameras sort of overlay, um, you know, machine learning algorithms and things to really extract what are your main drivers of risk. Here is it, look, um, you've had like this 40 forklift pedestrian, you know, crossings that are too close, eventually that something's bad is going to happen. Right. So we can, we can identify things like that. Um, but I would say that, you know, not every company is ready to have a third party plug into their camera feeds and really analyze their operations. Not just because of Big Brother concerns, but also just because a lot of people consider their operations as proprietary. This is my source, this is how I do stuff. And I'm not just going to hand it over to you. So the other thing that we're also doing is, um, we've just released an app where people can take pictures of their facility and literally in seconds, uh, algorithms can look at those pictures and say, hey, these are your main risks. Here's how you'd solve them. So really that's the direction we're going into is, uh, having this platform of technologies that allow us to identify what's going to potentially cause your injuries and give you solutions, um, before things get worse.

Speaker A: That's really, uh, very cool. Um, your primary customer segment, where are you seeing the most traction?

Speaker B: I would say on the insurance side, it's definitely these, uh, parcel deliveries. So anyone that does last mile delivery is actually really well suited to our device because, um, you know, somebody else might.

Speaker A: Risky. I was watching a woman deliver for Amazon in our neighborhood and we're like in a downtown, we're in a nice, great lover neighborhood, nothing wrong with it. But also like, it's still 11 o' clock at night on a Friday. And we lived kind of close to downtown and there's like a 25 year old woman delivering like big boxes by herself like after dark. And I'm like, this could be sketchy.

Speaker B: Yeah, exactly, exactly. So, um, yeah, so, so, um, from a safety perspective as well, you know, you're out, you're out there, right? So there's, you know, dogs can attack you, you can, you can trip on something, you can get into a car accident. So just lots of things can happen. And so um, that's when you know, ah, a device is very well suited to that because it looks at, you know, these strain and sprain injuries. We um, we detect jumps as well or running and things like that. So we can really identify some of the movements that tend to be, you know, a precursor of, of an injury. Um, and so that's the um. So those are, I would say the biggest, the other two big areas are warehousing. So actually you know, inside the facilities, uh, we have yet thousands of devices and sort of pretty, pretty large warehouses. Uh, and the other one is manufacturing. So we have a lot of presence in manufacturing as well. Um, and so yeah, those are, I would say those are probably the three main industries.

Speaker A: I'm picturing a feature and it's like, no, bad idea time. But the uh, you know, when you're driving and they're like, is the car, is the cops still there with the, you know, is it still a radar hotspot? It's like, is the dog still there? The angry dog still on 14th Street?

Speaker B: And you, you can't say though, you can't imagine just how it is rare that you would look at all the claims of a parcel delivery company and then they not have dog bites literally every year.

Speaker A: Oh yeah, it's, it is incredible all these, um. So my wife used to work for Lyft and she was internal communications. And I won't say much more than that because I know we were probably NDA, there's a family. But like all the things that you encounter from these like peer to peer marketplaces and how much risk those companies are taking on by allowing driver like

Speaker B: you cannot do something more risky than

Speaker A: driving somebody across town. But like, you don't think about this stuff. You're like, I just, I got my package. It was great. But like the people that are doing this are just putting themselves in such. They're so exposed.

Speaker B: They're on the world.

Speaker A: We're on our sofa. Um, it's just um, you know, there's a lot of chance encounters, so I get it.

Speaker B: It's. It's a big deal. Yeah, exactly. You know, and in that sense, like, you know, when Covid happened, something very interesting. You know, I think for. For those of us who are, like, on the sofa. Right. Um, we sort of became much more aware of that type of work. Right. You know, where the grocery stores weren't filled and, you know, we started calling a lot of these frontline workers and essential workers. And so there just became this realization that sort of, you know, our economy and lifestyle gets sustained by these. A lot of workers who are just going around, you know, delivering things, uh, making manufacturing goods. Um, so I think in that sense, it very much helped that cause because people just became so much more aware of, like, you know, um, of this demographic, this population, and some of the issues they have.

Speaker A: Um, very cool. Very interesting. Um, thank you for the deep dive. I want to switch gears, uh, directly back to Columbia. So what. What took you down there? How, like, what's the. What's the appeal? Like, have you. Have you been to Columbia before? You got family or what's. Yeah. Why. Why are you down there?

Speaker B: Yeah, so, you know, we started in Kinetic in New York. Um, you know, company was built there. Uh, we have our main office there. And really just a couple. You know, after, uh, about eight years doing Kinetic, my. My wife got transferred to Colombia for her work, for her job. And I was thinking, you know, um, does it make sense for us to do this or not? And, you know, I'd been working from home for a little while and going into the office most weeks, but I was like, oh, maybe I can get away with doing this remote work from Colombia. I'd moved here, and it wasn't the intention, but one of the side benefits has been, you know, we've hired two people who are based in Bogota, who are part of now the engineering as a data team. And honestly, I want to expand. Like, there are, you know, lots of very educated, smart folks here. And, um. Yeah, so we're excited to sort of grow out that team as well.

Speaker A: Awesome. Well, um, very good show. Really enjoyed having you on. Uh, like, what's, uh, like, when you're looking to the future, like, what's next for you guys?

Speaker B: Yeah, you know, I think right now we have both businesses where we sell, you know, technology to these large companies, and we also, um, you know, sell insurance. I think we'll, like, our insurance side of business has just grown like crazy, uh, because, you know, essentially you're selling a product that People have to buy, right? Which is this workers comp insurance. So, you know, I think we'll, we'll continue to go down that path. And really that's the idea. The idea is, all right, let's just figure out how we can prevent all these different types of injuries that we see in these, um, industries and you know, build out products or incorporate products that can solve them. So we're very excited about that because there's just very few insurance companies that think about prevention. And when you approach, you know, the policyholders of the companies who buy the insurance, um, you know, as busy as they are and as multiple hats they will have to wear, they are really interested and excited to adopt technology like this that will help their workforce, you know, stay productive, be injury free. And you know, these are folks who know their workers really well. They're, they're in their facility, they're speaking to them every day and so they really care for them. And so, um, you know, we're finding just great reception to this type of stuff. So I never thought I would tell, you know, say, drop that bell that I, that I, um, that I, you know, we're going to build the best workers comp insurance company, but I think we're going to build the best workers comp insurance company, uh, and really, you know, really, uh, stop people from getting injured as much as they did today.

Speaker A: Well, uh, it takes some time to find your, your place in the world and we don't always know where we're headed, you know, when we're like 13 years old. Um, but product market fit is non trivial and I'm really excited to hear that you guys have found a great application for what is obviously a very unique, uh, and compelling technology. So hats off to you.

Speaker B: Thanks, Mil.

Speaker A: Yeah, well, uh, with that we can, uh, wrap for today. Thanks for coming on the show and uh, we'll look forward to having you back 612 months and hear us going there.

Speaker B: That's awesome.