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Kenton Williston: Welcome to the IoT Chat, where we explore the trends that matter for consultants, systems integrators, and enterprises. I’m Kenton Williston, the Editor-in-Chief of insight.tech. Every episode, we talk to a leading expert about the latest developments in the Internet of Things.

Today, I’m talking about agile retail with Richard Newman, the CTO and Co-Founder of Reliant. During the pandemic, many companies failed because they could not adapt, but others found incredible success by pivoting to new business models. This trend is likely to continue as the retail and hospitality sector remains completely unpredictable. After all, just look at the supply chain issues. So, what is separating the winners from the losers? Well, many times it lies in the area of digital transformation, and the challenge is that many stores and restaurants are struggling to apply cloud-scale technologies to their physical operations. And that’s why edge computing is such a hot topic in the space. I’m really excited to hear what Reliant is doing with its edge computing platform, so let’s get into it. So, Richard, welcome to the show.

Richard Newman: Thank you very much, Kenton. I’m glad to be here.

Kenton Williston: So tell me a little bit about what Reliant does.

Richard Newman: So Reliant is an edge computing platform provider. Our customers tend to be retailers or restaurant operators, and among folks delivering edge computing into the space we’re among the largest. We have north of 15,000 deployments to date, and work with a lot of major brands.

Kenton Williston: And what’s your role with the company?

Richard Newman: I’m Chief Technology Officer and Co-Founder. My day-to-day responsibilities consist of really all things technology when it comes to Reliant, but I’m mostly focused on our product and how our customers use our solution.

Kenton Williston: I would say as a founder you’ve got to be pretty proud of having a company you started to grow to be so big. So, what inspired you to get into this space?

Richard Newman: Well, really, it’s been all about customer demand. We have a different story than a lot of VC-funded startups. Instead, our approach to market was really based on need. When I got started in this business, it was really by being a consultant to the retail industry. And it was very quickly apparent that there was a really significant change happening in our market, and that change really was being driven by digital transformation, by the move of applications and services to cloud and to web-scale architectures. And that was leaving something behind, and that something that was being left behind was really what was happening in stores and restaurants. There was really an inability to change that architecture, it was very legacy based. As a whole, we saw just a tremendous opportunity to try to figure out how to crack the code, find a new way to deliver applications and systems into the physical premises.

So we started working with technologies that would provide virtualization and container delivery and orchestration and really strong connectivity up to clouds, into web-scale infrastructure before there was really even a name for it. The name that the industry eventually settled on was edge computing. So we found ourselves with an installed base of edge computing deployments, and a market need that was really very apparent because we had built the solution for the market. We were not one of those situations where we had a solution that was looking for a problem to solve. Our customers were very clear on what they needed and what directions we should go in with our technology. We were just following their guide, really.

Kenton Williston: Interesting. The last couple of years have got to be especially good demonstrations of having a very clear need that you needed to follow with the retail space being so heavily impacted. So, what’s been happening there? How’s that changed the needs in your customers, and how has edge computing helped ease all these difficulties?

Richard Newman: You can see it just from a business standpoint, COVID and the pandemic—really, a lot of the industry doubled down on the requirements around digital transformation and services that were focused towards things that were contactless, whether that be payment or whether that be buy online, pick up in store, or delivery-based services and fulfillment out of physical stores or restaurants. And our customers were reacting to that. They said, “We’ve got to change even faster than we were already thinking about changing.” And what you saw from what’s happened in the market is, a lot of the older brands that were not necessarily investing as heavily in technology as they might have, had either shrunk substantially, or even potentially gone out of business.

Whereas some of the innovative companies, the ones that were pushing the envelope with things like autonomous shopping, self-checkout, tight integrations and delivery, advanced omnichannel-based order management, payment—they’re the ones that did the best coming through COVID and then out of COVID eventually. What you saw, and this is not news to anyone probably listening to this, is the percentages of a lot of customers’ online orders went up, and that business was reflected in terms of what was happening in their brick-and-mortar locations. But brick and mortar isn’t going away by any stretch. It’s really becoming much more of a hybrid model, and that’s forced the systems that are deployed in that environment to change with it as well. So you see a lot more emphasis on the types of things that really enable shoppers to be connected with their products, fulfillment much easier and simpler. And on the very far end of that spectrum, you see walk-in-walk-out-based shopping starting to make its appearance across multiple markets.

But even simple things like, I need better integration with delivery services, if you’re a restaurant operator, because a significant number of my customers now really prefer to order through an app or order online, and they just want their food delivered and they want to be able to know where it is along the way. And these changes require modernization and re-architecting of the actual physical systems. So if you take a large quick-serve restaurant operator, suddenly they’re seeing just a much larger percentage of orders that they’re processing out of their restaurants, the online base. And their current systems and the way their kitchens are configured can’t necessarily keep up unless they are investing in next-generation technologies and finding new ways to innovate faster. And on a foundational basis, doing business the same old way with relatively tired, three-tier, client-server-based monolithic architectures doesn’t work. The success that they have in the cloud they want to replicate in the restaurant, and that’s edge computing, and that’s really what’s kept us so busy.

Kenton Williston: That makes sense. And it sounds like a key element here is not just to have intelligence in the stores, to have edge computing there in the restaurant, but it’s really about having a holistic architecture, not just encompassing your own business’s operations, but even your vendors’ as well. You want to think about even your vendors’ interfaces. How do you go about creating something that’s so all encompassing?

Richard Newman: That is the hard part. There’s no magic wand or secret formula to suddenly going from what might be a technology architecture that’s been in place at a large retail or a large restaurant operator for a decade or longer. It’s an incremental approach. It’s definitely not a big bang, but edge computing provides some great ways to do this. You can combine virtualization of existing legacy systems, whether they’re systems from large, point-of-sale providers or signage providers or other systems. You can run them as virtual machines at the same time, take workloads that might be running on those systems on a monolithic basis out, and deliver those as lightweight containers, and connect all of that up much more closely to cloud-based systems and services. And that’s how you start. It could be one simple application at a time, but along the way you’ll be able to develop a much more agile architecture.

Kenton Williston: So I think that word you just mentioned, agility, it seems to me like that’s really a key element of everything you’re talking about here. And again, these ideas about virtualizations and container, all these sort of things tie together to me, that are forming a picture in my mind that for a long time, people have been moving towards these cloud-based architectures, and one of the big selling points is you’re more focused on small workloads that are very flexible in terms of where deploy, how they can scale up, how they can scale down. And this has been a very successful approach in the cloud/IT space. And it sounds like a big part of what you’re saying is that same, more granular approach to the tasks that need to be done is really one of the key things so that you can put them in the right place, physically, on the right equipment, and interface with whatever it is that they need to interface with. It sounds like breaking things down to bite-sized pieces is really a critical part of all this.

Richard Newman: And changing up the architecture, going from legacy to an edge-first-based approach provides that opportunity. And it’s not difficult to get one’s arms around it. As you just mentioned, if you’re running a cloud-based infrastructure, people think nothing of adding another virtual machine or virtual host or another set of container-based workloads in the cloud. They just take it for granted that it’s part of the cloud-based services, and they’re right. Whether your cloud is Azure or AWS, provisioning another virtual system is super easy. It’s an action that can be done in a handful of seconds, typically. So if you think about the way things used to be back when we were talking about data centers, well, not so easy. You’ve got to actually order a server from somebody, wait for that server to arrive, rack it, connect it to the network, provision it, load software on it.

In the cloud, what takes us, as I mentioned, seconds was a process that took weeks to accomplish in traditional data centers, which is why cloud has become so predominant and you’ve gotten so used to it they probably forget this huge disparity. However, when you start talking about the edge or the physical premises for a lot of operators, they’re still stuck in that same older mindset. If they need a new system deployed in their physical store or physical restaurant, they’re thinking about, well, I’ve got to order another server or another system. I have to have it provisioned. I have to have it shipped. I have to have someone show up and install it. I’ve got to connect to the network. I’ve got to load software on it. All those things.

Edge changes that. In an edge-based workload, you’ll have a foundational system, like Reliant’s platform that will sit at your physical store, physical restaurant. And if you want to add another virtual machine, you provision it and it pops up. If you want to add another set of containers connected into a docker container registry, a set of applications you may have, all those actions are done through the cloud and they’re up and running in your store or restaurant. And I can’t make it any simpler than that. I mean, probably oversimplifying it a little bit, but it’s really that easy, and that’s the big change.

Kenton Williston: So to put it another way, it’s sort of rethinking how you get work done in the physical world. It’s not like, well, I need another checkout lane, so I need to buy another point of sale. It’s not, I want to boost sales, so I’m going to deploy a standalone digital signage system. It’s really thinking about the compute elements in really more of this sort of cloud-style fashion, where it’s like, well, I will have high-performance compute equipment in my local establishment, and it can do whatever I need it to do. I don’t have to, ahead of time, figure out all the workloads I’m going to put on it or buy different specialized equipment for different specialized purposes. I can think of it more as, I’ve got a pool of resources here that I can use to do all kinds of innovative and interesting things, things that I haven’t thought of yet.

Richard Newman: Totally correct. And again, you can start off with one edge system, two edge systems, and you could add more systems to a cluster as you decide you need more resources. But along the way, again, whether it’s a singleton node or a high-availability duo-node cluster, you always start with some spare capacity that allows you to provision additional systems as you need them. One of our customers, a large quick-serve restaurant operator, I think their initial application stack started with four or five containers, and now they’re running twelve or fourteen, and there’s this new workload that they’re coming up with all the time to run on them. And as they move to add more things, they’ve got plans down the road to do applications with machine learning. They can either use what resources they have or add new hardware to their cluster, which could include GPUs or TPUs to run ML-specific workloads.

Kenton Williston: And I’m assuming here that your relationship with Intel is pretty important in enabling all this. And I should mention that this podcast and the whole of the insight.tech program is an Intel production. But getting back to the question at hand, having very flexible IT-flavored hardware, I would imagine, is pretty critical to being able to achieve these scenarios that you’re describing.

Richard Newman: They definitely are. And that’s one of the paradigm shifts that we’ve seen. There was sort of a dumbing down of the physical systems that were being deployed in the store and the restaurant, and folks were getting much more towards almost composable hardware stuff that looked a lot more like consumer-grade components. But edge, though, makes you rethink that. And you start thinking about your edge-based system as being much more of a micro data center. You want to be able to have something that’s very leverageable, that’s also going to be highly reliable, because suddenly you’re going to be concentrating more workloads running on what might be a cluster, and you’re going to want to have scalable capacity. And again, that moves you all off of what might be consumer-grade components and hardware to something that’s more data center grade. And that’s where Intel’s been doing a lot of tremendous work, and the silicon that they produce and the architectures that they’re supporting lead the industry in that space. And there’s new stuff that they’re coming out with all the time, which is just fantastic for these types of applications.

Kenton Williston: So I’m curious if you see any of your customers have any hesitation to make this move because things like uptime and making sure you can actually sell the things that you’re trying to sell is so critical to retail environments. You just can’t have all of your cash registers go down. That’s a death blow. Stores have traditionally—tourist restaurants, hospitality settings—have traditionally been, just give me something that is totally bulletproof, dead simple. I don’t want to have to train my people very much. The emphasis has been more on keeping it working than keeping it exciting, I guess I could say. Are you seeing some of that pushback? And if so, what’s your response?

Richard Newman: I’d say some of it, when you start rethinking your architectures that you’re using, these businesses can’t stop for six months to be able to do a retooling of their IT infrastructure. Everything has to continue to operate. So you end up with the analogy that you’ve heard probably before, changing the engine on a Boeing 787 while the plane’s still flying. There’s a little bit of that that goes on, but again, you’ve got to start with any of these things in bite-sized pieces.

And what often happens in the physical world, in the world of retail and hospitality, is everyone goes through various levels of hardware upgrade cycles or network upgrade cycles or major application shifts. We’re moving onto either a major new version of an existing point-of-sale system, or we’re switching point-of-sale systems providers, or we’re switching signage-based systems. And it’s at those moments of transition that you can take advantage of moving to an edge architecture instead of doing a same old, same old. And that’s what we keep trying to say to help people to do it. Take advantage of the changes you have to do to make the changes you need to do.

Kenton Williston: That’s very much reminiscent of the way the online environment has changed. You just cannot survive unless you’re constantly innovating and moving forward, you will get left behind, for sure. And it sounds like what you’re saying is that’s happened now in the physical world as well. Just doing business as usual is not good enough anymore.

Richard Newman: It’s not. But even so, what we’d also point out, and in most cases when you dig in, there’s real ROI associated with moving architectures. The total cost of ownership of edge-based systems matches the total cost of owner benefits that folks have seen with the cloud, for example. You end up with less physical gear overall, which means there’s less stuff to break and less cost associated with break fix, higher reliability, better uptime. It’s easier to support and service these products too, edge-based ones, at least. And we try to drive towards that. So again, depending on the size of your operation, you may be looking at anywhere from a couple million dollars to tens of millions of dollars’ worth of investment in moving to an edge architecture. But on the other side of that is typically positive ROI.

Kenton Williston: One of the things that I think your clients might worry about is, okay, this all sounds great. But now I’ve got all this high tech stuff that looks like a mini data center, mini cloud in my facilities. Am I going to need a whole army of IT support to make this all work? And I heard you say these things were going to be more reliable, have better uptimes. So can you speak to how that works in terms of the technical complexity?

Richard Newman: Edge-based systems should look and act like cloud-based systems relative to how you manage and operate them. You should be using easy-to-use GUI tools for configuration. You should have configuration on a highly automated basis. You should be able to use an API to manage configuration orchestration, all those types of changes along the way. And that mirrors cloud. So again, anyone that’s been through a cloud-migration project, and I suspect that most of the folks listening to this podcast will have experienced that, and sometimes that was now two, three, four years ago, they know what’s involved with doing it. They understand that there’s new technical skill sets that come up along the way. But at the end of the day, the reason cloud architectures were built was because the hyperscalers, Google, Amazon, Facebook, Netflix, Apple, you name it, they couldn’t have built their infrastructures as quickly or the size they were without a lot of automation, which ultimately resulted in a much smaller number of people supporting a lot more technology with a greater overall level of reliability and the lower total cost of ownership.

So at some point, organizations have to look at what they’re doing in their physical premises, again, stores or restaurants in our world. But it could be medical offices. It could be manufacturing facilities, transportation centers, what have you. And they’re going to say, “What’s it look like going forward?” We’re all going to evolve to accept that stuff. And along the way, there are companies like Reliant. We’re rolling up our sleeves and helping our customers achieve success. There’s VARs and integrators out there with similar skill sets. It’s not a go-it-alone type of thing.

Kenton Williston: And on that point you mentioned things that are coming next, and earlier I heard you talking some about machine learning. What are some of the key areas that you see technology evolving over, let’s say, the next six, twelve months that edge technology will be critical in enabling.

Richard Newman: I’d like to look at a time frame that’s longer than six or twelve months, but let’s just pick the most obvious and easy one, walk-in-walk-out frictionless checkout. We’ve grown up in a world where we’re used to waiting on checkout lines, having our products scanned and weighed and our shopping carts, emptied out, our products handled by cashier. Machine learning and machine vision and related technologies like LiDAR and shelf sensors and just the ability to wrap all of that around in a web-to-edge-based architecture eliminates the need for it. And there’s plenty of case studies that show the cost of maintaining a cashier in a lane versus the cost of automating to things like either fully automated, walk-in-walk-out, to just assisted self-checkout, etc. The benefits are just numerous and they result, ultimately, in happier customers. They result in employees that are able to do jobs that are involved more than just weighing a bag of brussels sprouts to try to figure out what it’s going to cost a customer.

So I think when we look at the world going forward, we’re going to see a world where there’s many more opportunities to use AI and ML to support facilitated retail, facilitated restaurant operations, etc. And some of these things are really obvious when you look at, for example, mistakes that are made in food prep. Every restaurant has food prep going on in it. But if someone says they’re allergic to dairy, yet sour cream ends up on their burrito whether they wanted it or not, that’s an expensive mistake and it’s an unpleasant customer experience. But it’s really not much of a job for a camera to be able to look at an order and say, oh yeah, that order is getting sour cream, it’s not supposed to. I’m going to stop that right now. I’m going to alert the folks involved in the food prep that there’s a problem here, and I’m going to fix it before it becomes a problem for a customer.

We keep going. And those opportunities all day long, they’re just so numerous. They get into not just order quality, but they get into food safety issues. How long has something been sitting out? What’s the temperature of a refrigerator or a cooking service? All that data can be collected, and the computer never sleeps. It never makes a mistake when looking at the data, and it’s always going to be in a position to catch mistakes or help people make smarter decisions.

Kenton Williston: That’s really fascinating. I’m wondering if you can illuminate a little bit more one of the things you talked about with regard to supply chain and just ordering through apps and having a very friction transparent means of acquiring all the things that you need. What’s happening in that space that might be new and unexpected?

Richard Newman: All kinds of stuff. Some of it’s changing the way people interact with shopping and products and services. Here in New York where I’m based, there are half a dozen or more startup companies that are competing to do less than 15 minute delivery on an app basis. So these are organizations which largely are trying to crack the code to captured inventory, where they’re maintaining what are called dark stores, and all the interaction they have with their customers is over their app, but they’re guaranteeing 15 minute or less delivery of the products and services, which is just a completely new way of doing things.

And they’re looking at it and saying, “This is super efficient. Customers are going to be happier, if they need something, whether it’s a large grocery order or whether it’s simply a pint of Ben and Jerry’s, we can get it really quickly to that customer.” But again, automation really makes that possible. And from the standpoint of what’s happening, those dark stores or their analog, the ghost kitchen in the hospitality space, is automation, is quality control, is being able to match what are complicated orders with delivery requirements around it. Making sure the right product gets to the right customer at the right time.

Kenton Williston: Yeah. And what about the supply chain side? I know that’s only been another area of quite a lot of difficulty here over the last year or so. Are these technologies also providing some new benefits in that area?

Richard Newman: Well, certainly. Edge computing can provide options for getting much smarter about what physical inventory or food products you’re maintaining in your store or restaurant. It can provide better information than having a manager run around a location with a clipboard, trying to figure out what’s actually going on, and that data can be real time. So it provides opportunities for more dynamic pricing. It provides opportunities to potentially tell a customer, “Hey, we don’t have this product at this store, but we have it at this other store and we’ll find a way to get you fulfilled.”

On longer term, of course there’s issues or, I guess, challenges with supply chain that can go all the way halfway around the world to where products are manufactured. And then of course, the technologies that we’re talking about here can provide visibility into, where is something in manufacturing? Where is something in shipping? How long is it at the dock? When am I going to get it in my store? And how can I take all this data and then optimize my ability to make sure I’m giving the customer the product or service they want at the best possible price.

Kenton Williston: That sounds really good. Definitely something that’s needed at the moment, for sure. So in all of this, we’re talking about so many different elements of QSR retail, all the rest. Very complicated businesses with thin margins, a lot of moving parts, and we’re talking about pretty substantial changes to how these businesses work. So I’d love to hear just a little bit more detail of what Reliant is actually doing to bring all these many elements together and just make sense of all this data that’s being collected.

Richard Newman: You’re getting to the core of, what does Reliant do? So we are not a hardware company. We’re not an application provider of business applications, like point of sale or signage. We’ll work with many different hardware manufacturers, and we let our customers have quite a bit of say in terms of what hardware they like and don’t like. Our customers’ workloads define how much hardware, capacity, CPU, memory, RAM, all the rest of that stuff that they need. And along the way we’re focused on making it as easy as possible for our customers to take their existing legacy applications and run them as virtual machines, or define new, container-based workloads that they want to run, and plug it all together.

And that puts us in a great position. They count on us to be smart and knowledgeable about the retail or the restaurant application stack. So we’re very conversant in payment, point of sale, signage, kitchen automation, order management, RFID—all these components which drive the modern store or the modern restaurant, and we bring that business knowledge together with their requirements on edge computing on a platform that’s as open and as agnostic as possible.

Kenton Williston: One of the big questions, though, I would imagine is this all sounds great, but we’re still, at the end of the day, talking about connecting a lot of things together. And what if those connections fail, networks go down? A piece of data is missing that you were really counting on. What happens in that scenario?

Richard Newman: Great question. And it’s one of the things, again, that drives edge computing. So no one really worries about the connectivity within the cloud for the most part. It’s just expected to run. If you’ve got applications that are running in the cloud context, they’re all running locally and they operate. In edge computing, you don’t get the same guarantee of connectivity from edge, from store, from restaurant to cloud. So one of the focuses that we have is making sure that when customers are thinking about their workloads, they end up in situations where those workloads can run even if cloud connectivity is compromised, not available at all, or just degraded. And that’s very important because, again, you’re talking about customers who might be walking into a store, walking into a restaurant, the business needs to happen. It can’t be, “Sorry, we’re not going to be able to make your burger today because we’ve lost cloud connectivity.”

“Our stove works, but we just don’t know how to cook a burger without the cloud-based systems telling us what to do.” So resiliency is super important. It’s part of what you do with edge-based computing. And then the other thing I’ll point out is that management of systems at scale also becomes both an opportunity and potentially a challenge. So you’ve got to manage all of these systems that are running in cloud and edge with a high degree of integrity. So that, as you just mentioned, key pieces of data, whether they’re configuration data or data that an application requires, don’t suddenly vanish. “Oh, this isn’t working properly. I’ve lost my application. It’s not working because I now don’t know what my IP address is supposed to be.” And that’s another important part of what we try to do, which is really open up and make configuration highly automated, and also highly visible. Whether, again, you’re looking at it through a web-based GUI that we have available through our cloud, or via API.

Kenton Williston: The other thing that I’m wondering about here, we talked just a little bit about the way shopping patterns are changing, and how so much has moved to an app-based or online-based model, but yet at the same time, physical locations matter a lot. So how does this whole idea of an edge-to-cloud platform enable a better omnichannel experience that gets people enjoyable experiences, however they’re engaging with you, and also consistent experiences?

Richard Newman: Well, again, in the legacy world, you had cloud-based systems that might be driving e-com or even app-based stuff that were then connecting into legacy point of sale or legacy order management or legacy systems in stores. What edge provides is the opportunity to flip that around and start to take steps to modernize what might have been a legacy infrastructure. We’ve seen this again and again and again, where the pace of innovation in the traditional retail or traditional restaurant system is not keeping up with the pace of innovation that’s taking place in the digital cloud-based space.

So there’s a big game of catch up happening, and I’m not talking about the sauce that goes on a burger. The catch up that we’re talking about here is, how do I modernize my in-store systems quickly? How do I start to be able to, as I mentioned earlier, look at workloads that might be running on a legacy point-of-sale system and start to move them off into containers? Whether those containers are running in cloud, in store, or in both places as part of a better strategy for, as you pointed out earlier, greater agility, I’ve got to keep up with innovation.

Kenton Williston: Can you walk me through what the actual process here would be when Reliant engages with the customer? Where do things start, and what are some of the key apps that you walk through with your customers to get them to this nirvana of edge computing?

Richard Newman: It really starts with education. We’re still in the early days of edge. There aren’t specific standards. The best practices associated with edge are still being debated. And customers naturally have a lot of questions. They may have different motivations. As I said, we’ve had customers approach us who are just fed up with operational reliability within their store or restaurant location, and they want to know how to better increase it with an edge-based architecture. Other customers are looking at the wholesale transformation of some key systems, and they want to do it the right way on an edge platform. But all those things start with just conversations. “How does edge work for me? Here’s what I have today. Here’s where I’m thinking of going with my store or my restaurant systems. Reliant, what do you guys think? What are you seeing in the market? What are other customers doing? What are some of your competitors doing? How do you react to what they’re saying to the market or to us potentially?”

All of our engagements usually start with some element of design that usually goes into lab. Nobody makes an eight- or nine-figure investment in edge computing architectures without really testing it out. So we typically start with lab. Lab is usually based on customer requirements or what applications they want to run on, what type of network they want to have on what type of hardware is going to be deployed. And they look at all kinds of things, including operational reliability, performance, etc. And once they’re satisfied that it’s taking them in the right direction, we usually typically move to a pilot.

And depending on the size of an operator, a pilot could be a couple stores, or it could be a couple hundred. We’ve got some customers who approach 10,000 or more locations. And a good pilot for them is 300 or 400 locations before they start feeling comfortable with a commitment to deploy 5,000 or 10,000 locations. So this entire exercise lab typically takes place within a single calendar year. Sometimes it can be less than that. And actual production deployment at scale will then start after they’ve reached this degree of satisfaction and the solution that’s been proven out through pilot.

Kenton Williston: What would you say to a retailer, QSR, c-store, what have you, that’s thinking about pursuing some of these technologies and just isn’t quite sure when, where, and how to get started? What would you suggest they do as a first step?

Richard Newman: Read. The analysts we work with, folks over at Gartner and we know the folks over at Forester have a lot to say on this—their fingers are right on the pulse of what’s changing. And not just from a horizontal technology basis, but they have industry specialists, too, that understand what edge is doing to retail and hospitality. There’s also just a wealth of information online. Some of that can get confusing, because you’ve got different vendors that may have different agendas to promote regarding how they perceive edge. Those visions tend to line up with their products very neatly, whether their product is a legacy, repurposed, hyperconverged infrastructure solution that they’re now calling edge, or they might be a very large technology provider that has a very specific vision of how they think the world should work, such as IBM with their Watson architectures, relative to AI or ML.

But once you get past the noise, you start to have the conversations. You start to understand more. And again, if you want to call it a sales process, our sales process always starts with education, and we do our best to try to be available to anyone that’s interested. We try to show up at all the major trade shows, addressing retail, hospitality, in other markets. And we just start with saying, “So, what do you have? What do you think? What are you looking to do? What are you looking to change? What are your points of pain today?”

Kenton Williston: Totally makes sense. So, Richard, I have to say you’ve just plowed through so much information. It’s just been amazing. I can’t think of anything else to ask you. Is there anything you wish I had asked you?

Richard Newman: Well, I want to make sure folks know where to find me. We’re at Reliant.io. That’s Igor, Oscar, Reliant.io. I’m available on LinkedIn as well as a couple other social media vehicles like Twitter, etc. But beyond that, we’re just really excited with the pace of change right now. This couldn’t be a better time. COVID has driven, obviously, a lot of work to us, as organizations have scrambled to adapt. But coming out of COVID, we’re seeing another phenomenon, which is suddenly everyone is saying, “All these projects I had, for whatever reason they’ve been on hold, now I’ve got to get going with them.” So we’re busy. It’s delightful. And I just want to keep it going.

Kenton Williston: Well, Richard, I want to thank you again for your time today. This has been an absolutely fascinating and educational conversation.

Richard Newman: Thank you, again, so much for being moderator for this. This is wonderful.

Kenton Williston: And thanks to our listeners for joining us. To keep up with the latest from Reliant, follow them on Twitter at ReliantIO and on LinkedIn Reliant.IO. If you enjoyed listening, please support us by subscribing and rating us on your favorite podcast app. This has been the IoT Chat. We’ll be back next time with more ideas from industry leaders at the forefront of IoT design.

The preceding transcript is provided to ensure accessibility and is intended to accurately capture an informal conversation. The transcript may contain improper uses of trademarked terms and as such should not be used for any other purposes. For more information, please see the Intel^® trademark information.

 

This transcript was edited by Erin Noble, proofreader.