Creating the Internet of Things | Charlie Key from Losant

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Charlie Key 0:00
And so saving them hundreds of 1000s of dollars a year on a relatively inexpensive solution to get them a ton of value very quickly. And we’re talking months, not years.

Alexander Ferguson 0:16
Welcome to UpTech Report. This is our applied tech series UpTech Report is sponsored by terribly learn how to leverage the power of video at Teraleap.io. Today, I’m excited to be joined by my guest, Charlie Key who’s based in Cincinnati, Ohio. He’s the CEO and co founder of Losant. Welcome, Charlie, good, have you on. Thanks. Thanks for having me. Now, listen, it started in 2015. And it is a development platform for IoT products and services. So basically, people can build on it, or off of it. Beyond there, so I hope you understand that, like,

wow, what was the problem you saw and set up to solve? When it comes to I guess IoT development?

Charlie Key 0:53
Yeah, that’s a great question. You know, I started this company with two other co founders, Brandon and Michael and Brandon and, and Michael and myself, we’ve known each other now for close to 20 years, we met at college at Rose hulman in Indiana, where we got different engineering degrees and, and have done a couple companies along the way. And so right before lo Sant, Brandon, myself had a software company called modulus which we ended up selling to progress software public software company based out in Bedford, Massachusetts, so right outside of the Boston area. And while we were there, we started to see a lot of companies start to think about IoT. And at the time, you know, IoT was very much starting to get to be like, a very high B kind of word. And a lot of people were starting to dip their toes into what that actually meant. You know, in the industrial space, you had this whole machine to machine M to M kind of thing that was IoT before I was IoT. But, you know, we started to see some of our customers while we are progress start to think about this. And mainly it was they wanted to track, I remember when very specifically, they wanted to track all of the snowplows in their city to keep track of which streets had been plowed in real time, and be able to provide that data back to the city. And then and then back to the citizens. And so you can see exactly what had been plowed and what hadn’t been plowed. That was very, very early one. And I remember seeing that. And, you know, we started to see a couple other ones pop up. And we have always spent our time in the development world. And so we got very interested in it. And how are these people building these products and services and, and, you know, we started to dive in a little bit. And after diving in a little bit and spending some time in this space, you know, Brandon and myself decided that it was time for us to jump out of progress and try a new adventure. And that’s what became low SAT, you know, and we spent really the first couple months, just trying to understand what the market was doing, what tools were people using, what challenges were they having, you know, we had an idea of, of the problem that we wanted to try to solve. But we wanted to find out from people that were in the market, trying to build this stuff today. And so we talked to everybody from the pn G’s of the world to the small end industrial companies and, and so that kind of led us down the path of what we wanted to do and how we wanted to solve it,

Alexander Ferguson 3:32
you sell it your first venture, you’re but you still see this opportunity, like Alright, we got, we got to jump into this, we got to solve this ourselves. Now. If I remember from our previous chat, your history of your family is actually in manufacturing. So the future of IoT and industrial, you actually were seeing that already from then and start that passion.

Charlie Key 3:52
Oh, man, it was crazy. You know, you think about all of these conversations about, you know, industrial 4.0, or the new industrial revolution, or whatever people are calling in at the time, industrial IoT. But, you know, yeah, I grew up on a shop floor, my family has grown up here in Cincinnati, you know, helping manufacture parts for jet engines. And so, you know, really saw a lot of this kind of firsthand and in my my father, who was big influencing, you know, where I’ve gone from a technology standpoint, and even how I think about industrial IoT, and some of these things, you know, I remember we were having a conversation, I think it was Thanksgiving time. And he was saying that, you know, they have all these machines all over the place, they hundreds of machines that are manufacturing stuff and, and they know if they broken down obviously or something’s wrong, but they don’t know a lot of this before it happens. They don’t know a lot of this, that 30,000 foot view across all of their equipment they don’t know across all of their plans all at the same time and, and starting to peel back some of those layers, you know, Now we talked about digital transformation. And all of this is fairly obvious. But even five years ago, it’s still early. And it’s still early today and in the industrial sector, and so a lot of these things really started to open my eyes and the kind of create this thesis around around what low sand was going to be and the problems we were trying to solve and what we why we thought it was a big problem to solve, right?

Alexander Ferguson 5:24
You mentioned this this Yeah, this the hype around 4.0 industrialization and it’s coming with IoT, what’s the gap that has been existed that has has prevented this wonderful growth of, of innovation?

What’s this gap?

Charlie Key 5:40
Yeah, well, I don’t know how much time we have here. But we can dive into, you know, the top ones, I think, you know, some of it is organizational, some of it is operational, and some of its technology, right. From an organizational standpoint, we have many of these companies, especially we’ll call mid tier manufacturing. And so when I think about that, I think of you know, a manufacturing company, maybe it produces a couple 100 million, you know, in revenue. And so that’s a large operation. But in the manufacturing space, now, it’s, it’s, it’s kind of middle middle of the road, and we’ve got a lot of those in the Midwest, we’ve got a lot of them here in Cincinnati, but all these companies are run operationally to churn out the products that they’re manufacturing, you know, a lot of times, it’s a couple of different skews of products, and they turn them out as fast as they can, you know, with a lot of emphasis on making sure the equipment is up and running that moment, and not a lot of forethought into how are we strategically going to innovate our selves, our business, over the next three years, five years, it’s a very reactionary world, and in that space, and so that organizational structure is hard to break, right? Like we, a lot of the times, you can take the company to $300 million, you know, manufacturing company, they might have three it people for it, people, they don’t have, they don’t have software people sitting around, you know, maybe they’ve got a database, you know, engineer who’s overseeing Oracle, working with their SAP, but they don’t have a ton of people sitting around, to try to solve some of these highly technical, but different, different technical than what they’re used to doing day in and out. So that organizational challenge has been a big part of it, you see this like last year with the pandemic, that that mentality, and that shift of focus for technology may is coming? I think so I think that we’ve already seen it in certain parts of all industries, right, you know, the pandemic, brought out this idea of, you know, and we talked about digital transformation. And again, one of these giant buzzwords that, who knows exactly what it means, you know, in my world, when I think about it a lot, it’s how to replace a clipboard, you know, with a digital form, how do we replace everything that we’re trying to manually do with something that is a digital representation. And this doesn’t always mean that we’re replacing people, right? Like, people talk a lot about how automation is going to replace people, you know, AI is going to remove a bunch of jobs. But right now, we have a lot of inefficiencies in these processes that would allow and enable our current people to do more and be more efficient and produce more creating more margin per day. And so that is what I’m seeing right now. We’re seeing all of those process and efficiencies across a lot of the different parts of the business become very relevant and day in and day out. Not to mention that a lot of people just can’t physically get into spaces. So remote monitoring is becoming more important. But all of this is this shift that we’re starting to see.

Alexander Ferguson 8:47
Yeah, are you seeing when it comes to like, this definition of IoT? So I mean, that’s part of what you’re studying, like, the Internet of thing? Is this is that just part of this digitization? This goes to help me understand further, like, specifically you guys like what is the space that you’re playing and trying to enable them for? industrialization?

Charlie Key 9:06
Yeah, absolutely. And that’s a great question is, you know, where is loss? And where are we spending our time and, and efforts in this industrial revolution will say, and really, for us, it comes around understanding what’s happening with our equipment out in the field, what’s happening with our equipment day in and day out, from a remote standpoint, and this enables so many more value added opportunities for these organizations. You know, if we’re producing 10,000 compressors a year, and we don’t know what’s happening with those 10,000, compressors out in the field without putting a person there, or having a person standing in front of a SCADA system. That becomes a huge drain on our product, our productivity and efficiency, not to mention, our support capabilities in our in our adjusted service to our customers

Alexander Ferguson 9:58
does like more visibility on On the assets that you have and what they’re doing or not doing,

Charlie Key 10:02
yeah, that’s step one, right? Like, if you think about it, it’s a journey for each one of these companies. So step one is, let’s start pushing that data from those pieces of equipment into a semi centralized system, right? Like, let’s start grabbing all of that information, pushing it up, visualizing it, starting to report on it, understanding it. This is this is before we even get into, you know, the world of AI and machine learning and all of these other things, you know, if we can start just producing data around what’s happening with our stuff, and giving ourselves visibility to that data anywhere we want it, we have a lot of value. Right there, right? Like, that’s step one,

Alexander Ferguson 10:42
can you just to be able to kind of give a real world example, I had clients that you are working with right now or have worked?

Charlie Key 10:49
Yeah, absolutely. So you know, I remember one of our very first customers is this company in Australia, that national pump and energy, they have large pumps at Goldline sites throughout Australia. Like literally in the middle of nowhere in the outback, they have these large pumps there used to pump out these goldmine wells and, and they have to continuously re, they continuously run for six months plus at a time. So these prompts will be, you know, and are extremely important to process. So before they started remote monitoring and understanding and adding, you know, some other things we’ll talk about, they were literally on a scheduled maintenance, people were flying on planes out to these remote sites, checking on the equipment, making sure that it was working, doing the, the scheduled maintenance, and, and the preventative maintenance. And that was how they just did things, they literally had to fly people all over the place all year long.

Board, they now have connected these machines. Now, they didn’t have to add a ton of, let’s say, additional hardware. So you know, all of these compressors, and pumps, they all have controllers on them, those controllers usually have access to that data, you know, through one method or another. So step one is let’s connect to that controller and start sending that data back, you know, in their case that goes back all the way through cellular back to the platform, and starts bringing to light all of this interesting information that they have. That’s step one. Now they know if something’s breaking, right, like they now can base everything on the current condition of the asset. So now they’re they’re doing instead of preventative maintenance, and they’re down doing condition based maintenance. Now, what they were able to learn about this data is as they continue to analyze it, as they continue to look at it, they started noticing that there were a couple instances where as these variables, certain variables started to come back and looked, they tell that it was a trend that a certain part of the pump was going to break had not broken yet. So now they can create some relatively simple algorithms that will tell them predictively, that they’re going to have a part break on this pump. And it’s a period of time that they can now preemptively go repair and fix that issue. And so this is a journey that all of these companies are working through to get there. And so saving them hundreds of 1000s of dollars a year on a relatively inexpensive solution to get them a ton of value very quickly. And we’re talking months, not years, as a a platform IoT platform, how Madison like, the tech stack itself, like how does it work are effectively the different companies that come in to you. They’re just building on top of it, their own software folks are doing it, like Help me Help me walk. Walk me through that? Yeah, absolutely. So if we think about what I call is like a typical IoT solution. So you know, you think of it as a stack, right? We have, we’ll call it their asset or their piece of equipment. You know, that’s the hard hardware, creating the data, we have sitting above that maybe some additional sensors, or a gateway. And that gateway is connected to that piece of equipment and pulling the data from it right, like, so that’s kind of hardware sitting on that gateway, we actually have software that can sit on that gateway, and help collect that data, help do some edge analysis, collection, check for things, right, almost any hardware out there, connect with a large variety of hardware out there. And and so now you can do some edge thing. And you can think about this as a way to, you know, reduce all of that bandwidth of data that we might have to send send up so we can start checking some of that at the edge, do a little bit of analysis, make sure everything’s running, and then send up, let’s say every five minutes every 10 minutes every 15 minutes, instead of sending up every second all of this data. So you have that. So that’s sitting there. So we have software that sits there and then you have connectivity. So cellular Wi Fi landline, whatever, whatever is appropriate, you know, Laura, and all of these other technologies are coming out as different connectivity options. So that sits there, and then the data will flow up into the cloud. And the cloud is, you know, in our case, we run on top of Google’s cloud. For most of our customers, now our customers can choose kind of where and how they want to run that. But it will just say Google for the moment, the data flows into our platform inside of Google. And so we’ll collect that data at that point, we’ll store that data for our customer will start to process it. And so you’re going to have two different things that kind of happen in parallel at this point. One is we’re going to present it, give it up in nice dashboards. And those dashboards are where their folks will come in and configure them and choose what those dashboards look like. they’ll choose what data they want to see how they want it broken down. So do I want to see the average temperature over the last 12 hours and show it next to, you know, the my vibration data, whatever that looks like those are all configurable. So that’s where that user is going to go in and do that. And that’s a very easy kind of drag and drop interface. And in parallel, where we’ve spent a ton of our time is, is allowing our customers to process that data. And what we call our workflow engine. And our workflow engine, if you think about it is a low code drag and drop interface for designing the logic and processing that happens on this data. So this is again, where that customer and their technical folks are going to come in and design that process and that workflow. So it’s triggered when a data point comes in, maybe they want, again, maybe they want to do a little bit of running average against that data. Or maybe they want to check that data. And then if it’s bad, they want to pull a record from Salesforce, grab the customer record, figure out who they need to contact inside of the workflow, and then send an email and a text message to the appropriate sales or service rep. And so that workflow is all designed by the customer built inside of our platform, delivering that process of what should happen to that data. And then all of these, both of these kind of culminate in what we call an experience. And you can think about that experience is as a web application, for the most part and an API, where that interface where the customer, our customer, the equipment manufacturer, their customers will have access to that data, hopefully, and have access to the reports. And that experience is how our customer, the equipment manufacturer will deliver that to their to their folks. So they get a fully branded experience to deliver to their customers on all of this data, and add a ton of ton of value, or even a new revenue generating product. And so, you know, that’s kind of the stack that we play in

Alexander Ferguson 17:45
your your use, you mentioned that your customer is, is the the hardware Person person that’s trying to build that a solution for the end customer is that

Charlie Key 17:53
a lot of time. So if you think about it again, and in like, national pumping energy, so national pumping, and energy has these pumps, their customers are the people running and buying these pumps from them and running these pumps all over the place. And so they’re delivering a solution to those customers, right? You know, we think about it as like B to B to B, right? If we’re going to the business, the business is going to another business and and you know, our platform enables all of these complex scenarios, and hierarchies of that, you know, both the customer but also the data, data access to data security. And so that’s really where we play and treated very well. You know, another nother one of our customers is Verizon, and they use it very similarly. But they provide those new products and services. So one of their products is a shipment asset tracking solution. They have their own hardware that they’ve built with a hardware partner, it’s a GPS tracking multi sensor device this big, and you can buy that from them. And when you get it, you’re going to go to you know, Crikey, last tracker dot ryzen calm, I don’t actually know if that’s the URL or not. But once you go there, you’re basically logging into, you know, a website where you can see where your tracker is, and see the condition of those sensors on the tracker. And that’s all built inside of our platform. So that entire application and that entire experience is all built in our platform. So the software that we deliver enables all of those components and and their team can go in and and change that or customize it or configure it differently. And so they can deliver it to their customers in a very unique way, in a very branded way for Verizon or whoever the customer is not

Alexander Ferguson 19:40
the being that white labeled solution and then business or you know it exists actually exists. But you’re powering that that whole solution I’m fascinated with. There’s actually this growing trend of whether they’re API’s or platforms are basically a layer in between of software and another software to make it happen. And I think it’s fascinating. We’re in a space now, in a time where we can make applications faster and easier because we have solutions that you don’t have to be when you say I want to build a solution, you don’t have to be an expert in all the different slices. If I per se,

Charlie Key 20:17
yeah, no, you’re 100%. Correct. I think you just pitched our product. So you, you’ve nailed it. I mean, you know, our whole goal in life is to make it as easy as possible and as fast as possible for our customers to get those solutions built, get them delivered out in the market, lower that long term cost of ownership for them lower the amount of expertise they have to carry on house. And and you just mentioned that, and that’s important, right? All we’re not, we’re not asking every company to be an IoT expert, what we’re asking them is to choose the right IoT experts and partner with and that’s that’s the, that’s the big shift. And a lot of this is, is just like you mentioned, they don’t have to be no all of these different components to get a solution in the market. Now,

Alexander Ferguson 20:59
you mentioned earlier, the the edge computing, and I think it’s a fascinating kind of future, we’re a lot more can be happening at the edge. Can Can you speak more to that to that concept? And what you see is the future to mobile computing?

Charlie Key 21:13
Yeah, you know, we see all over the place. First of all, I mean, you see, especially and we talked a little bit about the industrial sector, and that, that that space is going to continue to accelerate their needs and the mobile edge computing space and you define it, let’s actually start there just Can you define mobile edge computing. So if I, the way we talk about it internally is there’s multiple layers to like that edge computing. So if we think about, you know, the machine itself, now, technically, that’s right, at the very leaf, right like very, very, very edge, that absolutely is going to have some of its own process, I think it’s going to do some of its own pieces, you know, one step away from that, it’s going to be that local environment, you know, maybe a small gateway baby computer that’s doing some processing. And so, you know, this is really where people start to think about that edge, right? Like, you know, that that is that very edge piece that maybe is collecting data from five or 10 different machines from there and here and, and bring them together and do some interesting stuff with them. And then this, there’s this very big trend of what’s happening in the telco space. And, and the software defined network and software defined storage is this mobile edge computing, which I think about it is like one layer above this, right, like, you know, you think about it for a whole facility, we have now a full set of capabilities for computing, which, you know, we would have called like VMs, you know, 510 years ago, we to call VMware, and they had a rack of stuff. Now, we have mobile edge computing, and it’s a rack of stuff, but it’s a rack of different stuff. But it brings a whole nother layer of computing capabilities, because we’re taking a lot of these services people have come to expect at the cloud level, and starting to bring them down. So the first part of that is important is, you know, we’ve come to expect a very great level of service from cloud providers, and cloud service providers, and a lot of compute capabilities there, whether it’s, you know, storage, or image recognition, or video processing, or, you know, storage breakdown, and all of these different things, you know, we’re bringing those down a layer to a facility to a campus, and that’s that mobile edge compute layer that is becoming very important. And you’re going to combine that with, you know, private networks that are layered in with that, to enable a whole nother set of solutions. So you can think about, you know, stadiums, when I have some, some good friends who are doing some excellent stuff and video for sports. And but all of that video is coming from the athletes, you know, wearing cameras or whatever else. And running back to a mobile edge computing system inside of the facility to process all that because it’s a massive amount of bandwidth. It’s a massive amount of compute needed. And so that, that encompasses a lot of this need, you know, we’re gonna see it also because of data security and data privacy concerns. So if you’re, you know, a large amusement park, maybe you don’t want all of this data going to the cloud, about where people are and what they’re doing inside of your parks at all times in every moment. And so maybe you push all that to the mobile edge, where you can process that pull the data out that you need to provide the insights back up to the cloud that you need to and the processes to come back into the part that you need to and so those are the all the pieces that are going to driving this forward.

Alexander Ferguson 24:47
What do you see if you’re kind of looking at the future here of both edge but I just IoT in general when it comes to the use? I guess you’re mostly focused on the industrialization and manufacturing space, but what do you see is As the future of like, what’s coming up? What are you guys working on? And what do you see overall the industry? Yeah,

Charlie Key 25:05
so you know, this edge piece is very important. And I think it’s both moving down layers to make it easier to program, the microcontrollers, the real time operating systems, the low cost, because what we got to do, I think about the things that we need to do to make IoT successful across the entire all of the industries is, we’ve got to lower cost of hardware, that lower cost of connectivity got to lower the cost of compute storage. So if we can make it easier to program, the real time operating system chips, you know, what’s sitting in your cell phone, what’s sitting in your watch all of those things, we can lower that cost, that lowers the cost of rollout, we can lower the cost of connectivity, we’re gonna see all these things come down, it’s part of one there, because a lot of these are becoming commoditized, you know, from a connectivity standpoint, from a process compute standpoint. But also new innovations in technology are making it easier to do these things. So that’s step one, we’re going to continue to see that and IoT is going to continue to see a ramp up off of that. The second part is, we’re going to see a lot more standardization on value added use cases, right? We I think we already know a lot of what they are, but people are still trying to figure those out, right? asset tracking, indoor asset tracking, and building and managing our buildings better. Right, one of the big things that is coming out of this pandemic is we’ve got so much space that is not being utilized correctly. today. Because one, we haven’t been able to have people in there. But to those buildings are running their h backs a lot more than they need to they’re running their lights a lot more than they need to the amount of energy waste that we’ve had over the last year and will continue to have is massive, it’s so IoT is going to be a big part of understanding and automating these systems, better processes. So those are two big areas, I think telcos with 5g are going to really start to figure out over the next two years, where those IoT solutions are that are very important for them and their customers. And so we’re gonna see that shift, you know, they’ve they’ve invested massive, multi, multi, multi billions of dollars and the infrastructure for 5g, and both, not only from the public standpoint, in the cell phones, but also and how do we bring it to our enterprises. And so you’re gonna see a lot of drive there. And so there’s, those are big components. And then we haven’t even really talked about the machine learning and AI stuff that is all going to change the world and, you know, turn the robots on, and our trucks are going to, you know, take over the world.

Alexander Ferguson 27:43
Personal drive themselves, and they’ll take over now, just just for just for fun, Charlie, let me let me know, what if you could wave a magic wand and have a futuristic sci fi solution come into existence? What would that be? If you just had to pick something pretty open ended? What would Yeah, um, you know,

Charlie Key 28:04
I’m gonna say one that I’ve, I’ve talked to multiple people about, just because we think it really interesting, if you think about running a factory floor, and, and the amount of daily manual processes, we’ve, we’ve got this view, and I’ve talked to my father again, about this is like, he wants to be able to put on like, an augmented reality, you know, headset and manage and run an entire shop floor, and all of the machines, you know, from a single single view, you know, it’s like, it’s the more friendlier version of Ender’s Game. And basically, you know, we’re running a bunch of machines that are helping, you know, build and change the industrial landscape. And I think that maybe not that so much, but I think a lot of these things are going to enable us in the US to put back a lot of the manufacturing work that we really want to have, as a society and as our economy. I think it’s important for a lot of these technologies to bring this to light and here in the

Alexander Ferguson 29:10
States, so you can see easily a world where a worker is putting on AR glasses or a headset and they’re controlling the machinery and etc. That’s around them just just using their hands and through the augmented interfaces. You know,

Charlie Key 29:25
I think we’re ways out but yeah, I think I think we’re not as far as people think we are from from the at least technologically being able to do some of these very interesting things.

Alexander Ferguson 29:36
I actually just did another interview recently with a company called Mira and they are for in manufacturing AR remote in and then you can interact with the worker what they’re seeing. So for training and interaction, it’s getting there but not quite controlling. Right. I don’t think you’ve integrated money on controlling and and using the equipment.

Charlie Key 29:55
And I think, I think Well, I know one of the challenges is is security and privacy

And that situation, right? Like if, if you’re telling me I can have a single headset slash controls to control every machine and, and a Ford factory, for instance. I mean, you know, that just even if it was technically possible today to try to convince the CIO of, of, of, you know, a large company they might do as they say that was okay. Right. So, you know, we’ll get there. Yeah, but I love I love the future that you paint and a lot of it is based off of just continuing to connect all the technology pieces that we have a hardware to the software to be able to control and know what’s going on in our different places. Thank you so much, Charlie, for for the insights and what you’ve been sharing. For those that want to learn more they can go over to Losant.com. That’s LOSANT. Yeah. LOSANT.COM and sign up for a free trial. Is that a good first step for folks? Yeah, absolutely. So I’d say there’s two great first apps, sign up for a free trial, which is our sandbox, it’s always free, you can jump in, you can do anything you want in the platform, you know, and then the second one is we have an online training course called low St. University, low sand comm slash University. And it will walk you through and teach you all about the platform and how to build IoT solutions. And so I think that’s a great starting spot for folks to train and learn and get going in this world. What’s, what’s the typical person that would make sense to go to that university? Because it sounds like like, what’s the skill level or, you know, what we say? What we say, and what we tell our customers is that anyone that has a small technical knowledge, so understanding of basically if this, then that type knowledge can start and start learning. If you are a web developer, you’re going to be highly successful in the platform. I mean, that it’s a pretty low bar to be pretty successful. We’ve had everyone from marketing folks build pretty interesting stuff. Very cool. Well, thank you again, Kelly, for being on the on the series. It’s pleasure. Thanks for having me. Yeah, I will see you guys on the next episode of UpTech Report. Have you seen a company using AI machine learning or other technology to transform the way we live, work and do business? Go to UpTech report.com and let us know