Podcasts > Technology > Ep. 067 - Data streaming for mission critical field assets
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Ep. 067
Data streaming for mission critical field assets
Matt Harrison, CEO, WellAware
Tuesday, August 04, 2020

In this episode, we explain how data streaming mission critical data for remotely monitor and control physical assets works. We learn how to simplify business model and connectivity for asset management, all with the backdrop of Covid-19’s impacts on industrial digitalization trends.

Matt is Co-Founder, Chief Executive Officer and a member of the Board of Directors of WellAware Holdings, Inc. At WellAware, Matt drives the overall business and product strategy while also leading the day-to-day execution of the company’s vision of connecting people to the things that matter.

WellAware empowers organizations to be efficient, safe and sustainable by streaming mission critical data to their employees, so they can remotely monitor and control physical assets.

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Automated Transcript

[Intro]

Welcome to the industrial IOT spotlight your number one spot for insight from industrial IOT thought leaders who are transforming businesses today with your host Erik Walenza.

Welcome back to the industrial IOT spotlight podcast. I'm your host. Erik Walenza CEO of IOT one. And our guest today is Matt Harrison, co founder and CEO of WellAware WellAware empowers organizations by streaming mission critical data to their employees and partners. So they can remotely monitor control and automate physical assets. In this talk we discussed well-aware as opposed to simplifying the business model and technology deployment process for edge connectivity and asset management. We also explored the impact of COVID-19 on industrial digitalization trends. If you find these conversations valuable, please leave us a comment and a five star review. And if you'd like to share your company's story or recommend a speaker, please email us at team@iotone.com. Thank you.

[Erik]

Matt. Thank you so much for joining us today,

[Matt]

Erik. Thanks for having us. We're excited to be here.

[Erik]

And so Matt, I'm really interested in kind of getting into the business and the technology behind well-aware.You know, I talked to a lot of companies that are very, very horizontal, and so it's very interesting to speak with a company that has more of a vertical focus, but before we get into the business and the technology, I want to understand a bit of your background cause you actually have, I think, a very interesting background quite, quite varied across healthcare and the energy sector. Also you're an investor. Can you just give us a quick run through of your background and then what led you to found or co-found well aware in 2012? Yeah, you bet. I'm happy to share a little bit of, of myself. I hate talking about myself, but we'll we'll at least provide a little bit of the, the breadcrumb history on, on how we got to where we are. It's probably tied back to my red hair more than anything.

[Matt]

I think that just kind of made me come out of the womb with a little bit of a fiery DNA, but I've always just been a problem solver naturally drawn to problems, got an electrical engineering degree at Texas a and M never necessarily practiced in engineering. Always wanted to apply that from a business perspective and using technology to solve problems. And so that's really what my career has been made up of is understanding problems and you know, trying to really understand those better than most. And I think that's that's been a huge feather in our hat as we're understanding well aware and understanding what true industrial IOT convergence looks like and then trying apply, you know, some of the latest it technologies to help our customers solve problems. So I've been very fortunate to work with some amazing people here at well-aware and in my past roles, I've had a lot of incredible mentors and investors and board members.

So I really count myself blessed to just be kind of leveraged up by a lot of people along the way. But you know, if I could kind of characterize myself, I had to say, you know, we, we love to compete. My my whiteboard has one quote on it from pretty decent baseball player named babe Ruth. And it says it's really hard to beat people who never give up. And I think that just, that really kind of characterizes well-aware and the people that we try to bring into the company so that we can work really hard to help solve problems for our customers.

[Erik]

It's a good model for the time right now, right? This is a challenging time, but there's always opportunities and challenge. If you just keep moving forward, there are. And, and you know, one of the things I, you know, just to add to that, that I would encourage the listeners that are in IOT to, to really hold onto that we found to be true is, you know, a lot of times, even our customers don't know exactly how big of the problem they're trying to get addressed is how difficult it is to solve. And so we really have had to lean in and, and work a lot with our customers to not give up on them. When they've said, Hey, look, I'm this IOT stuff is too tough. It doesn't work. Like I thought it would, we had bumps out of the gate. You know, we really have, have had a lot of success just locking arms with our customers and, you know, really kind of dragging them to the outcome. And we've had a lot of customer outcomes now that they've appreciated that journey. And so this is hard. This is not an easy space. It is the future, you know, giving machines a voice is obviously one of the most exciting things we could be working on, but it's not easy. And I think the twenties are going to be the decade for IOT. For sure.

[Matt]

Yeah. And you could say right now because of the COVID-19 background, it's on the one hand never been more important than ever. And on the other hand, it's maybe never been more challenging just because getting people out there to actually deploy sensors getting budgets allocated at a time when companies are seeing revenue go down, this is all more challenging, but on the other hand, the need to be able to remotely monitor and control and understand your operations is increasingly important. I think it's very interesting for people to have a bit of a snapshot on what the industry looks like, what growth looks like, what, you know, what deployments look like at this time, how is, let's say Q two and maybe the, for the Ford outlook for Q3, how are these looking for a well-aware, you know, especially if you're in an industry that's quite impacted.

[Erik]

Yeah, absolutely. Absolutely. Well, we're in a global economic situation that none of us have really faced before with the, you know, a pandemic that, that created a lot of the uncertainty. And, and so, you know, to your original point, we've got tremendous amount of jobs that have been lost, lots of top line revenue at our customers that has been lost. And so immediately they've got to go in and cut expenses or, you know, find ways to drive additional profitability into their businesses. Well guess what, the, one of the things that didn't change is the number of machines out there. There's still the same number of machines, even though there's fewer people. And so there's just a huge need and we've actually seen it come through in our commercial revenue growth and in our pipeline opportunities for the rest of the 2020, this is the time where people are really going to start placing huge bets on, you know, moving full stock to industrial IOT.

[Matt]

Yes, you have to have a platform that's reliable. Yes. You have to show your customers outcomes. They're not interested in tools or widgets. They want to actually help you. They want you to help them understand what the data translates into in terms of outcomes for them. But this is the time and, and, you know, for well-aware I, you know, we'll probably grow over a thousand X from last year to this year in terms of just our recurring revenue base. And it's just it's fascinating because I think a lot of people need help. Part of that growth is coming from our, our own globalization, both outside of the U S but also, you know, we really built the company in oil and gas. And so we've begun to now naturally expand into other industrial markets and applications. And so that's really helped our company see new opportunities and, and grow. And lastly, we've got a really incredible partner channel that's starting to build. So there's big companies, big telecommunication companies that need help with IOT solutions, big cloud companies that need help with IOT solutions. And so we've been really fortunate to to really begin to be on the front end of a lot of those relationships driving some growth,

[Erik]

Right? Well, let's get into the business then. So as you said, you, you started in oil and gas, but now you're expanding outside of that vertical into other areas where there's, I suppose, heavy, heavy assets, a complex operational situations, what would you be, or your value proposition. And maybe you can also talk to whether that's shifting as you're moving into new verticals or whether the same value proposition applies.

[Matt]

Sure. Yeah. Well, our, our mission, which is really our value proposition, as well as we exist to connect people to the things that matter. And so things are clearly machines and sensors, but as we've talked about already, there are obviously outcomes as well. And the way those outcomes usually translate for our customers, three big buckets. One is operational efficiency, usually cost savings. And we get those, those metrics accomplished in a number of different ways. The other is improved safety. So we're just eliminating a lot of mileage and trucks and we're telling workers before they go onsite, what to experience what they're going to experience. And so it helps them do their jobs in a much more safe way. And then the last one is environmental and regulatory compliance. And so we're, you know, we're really helping our customers reduce their carbon footprint, deliver some ESG wins, which at the board level is always, you know, very interesting and something that people want to tout and just help them with, you know, a better economic or a better environmental footprint.

[Erik]

And so those are kind of the main value propositions that we're, we're delivering to our customer. And our mission statement is we're just, we're here to connect them to their critical infrastructure, their machines and their assets. And we make that easier. We work across pretty much any application. We work across lots of different manufacturers. I would dare to say most if not all manufacturers. So it really doesn't matter what kind of pump you have or gen set you have, or sensor you have well-aware as a unifying platform that can allow you to collect data from very hard to reach places and get it into a actionable format that you can really move the needle on business outcomes. And so that that's, that's been hard to build. It's a, it's a very full stack solution. It's taken us seven years to do it. We started in oil and gas, which I would say was, was really kind of the best and the worst decision for us.

[Matt]

It was the best decision because it presented the most difficult environment for us to forge the platform. And so very remote, you know, very hazardous environments, power is a luxury communications is a luxury. And we also had a very highly varying user base. So a lot of our users had very little technical competency. And so that presented a very, very difficult set of circumstances for us to build our technology and our platform and our user experience in a way that we just made it easy, easy to install. And so I think it was the best from that perspective. It was difficult because, you know, it's an industry that's very slow to change. And so there's a lot of headwinds on existing installs, existing infrastructure. Hey, we've done it this way forever. So existing operational patterns, and it's, it's been fun when we begin to see the great shift change, you know, some more technology oriented folks taking on some higher level positions where they say, Hey, you know what? I should be able to operate my business the same way I operate my thermostat in my house. I can change the temperature land from bed in my house. Why can't I optimize my remote gen set or my pump in my business operation? And the answer is you can, and the old legacy operational technology approach that's been owned and built by some very large industrial players over the years is very right for disruption.

[Erik]

Yeah. And before we get into the technology, I want to do out here a bit on this topic of of the people that are involved in these technology adoption decisions, who are you typically working with? Cause I guess you have, you have headquarters that might sit, you know, if we're talking about Total, it sits in Paris maybe, but then they have operations around the world. So are you talking to headquarters or are you talking to the, let's say the local general manager of, of some facility that has specific pain points that they understand, and then are you talking to the, you know, you have the, also the split between the OT guys and then maybe the it infrastructure and before those were maybe kind of separate technology to mains, they didn't interface too much, but you're right at the crux of that, right. You're, you're kind of bringing those two ends together. And so I suppose you have, you have decision makers, you know, people that might allocate budget, but also people that might want to control the deployment or the operation of a system sitting in both of those organizations. Can you talk to us a little bit about, you know, on a, let's say local versus headquarters, and then it versus OT, who are you typically talking with? Who are the decision makers, who are the influencers? What is this perspective look like for well-aware?

[Matt]

That's a great question, Erik. So, you know, the way it works or has worked for us is with a few exceptions, I'll say, so we do have some large enterprise deals where the customers have decided that they are going to define and fund a very large IOT implementation that has typically C suite and budget approval behind it. And so it is very much a different pursuit than when you're actually building the opportunities themselves. So when you're knocking on the door, trying to create leads, so the enterprise level deals, a lot of times, those are RFP based. Again, you know, the, the stakeholders attached to those are usually your PNL managers. They may have some internal technology or internal internal technology guidelines that they want you to adhere to. They may want you to leverage some of the CapEx and the infrastructure that's already been put in place.

We love that because again, we work across anything that's out there. And so well-aware is really ideal to help customers leverage the existing investment they've already made. And we just make it so much better. We also, a lot of times we'll, we'll collaborate with existing SCADA systems existing SCADA teams, it teams that handle historians and handle data analytics, predictive analytics, et cetera. So the set of stakeholders, if you will, is really kind of across the board, I could list all of them for you across our, our opportunities when we're creating opportunities. When we're, you know, sending messages out and creating leads, we're looking for people who have a P and L budget and responsibility, and usually need to save money or improve safety, or, you know, their environmental regulatory compliance. And when we find those opportunities and we show people, those are typically the stakeholders that have budget and can move fast. And a lot of times the business owners, they don't necessarily mandate a specific technology approach. They just mandate that you get it right. And they do like you to check the boxes with the CIO and the CSO and, you know, make sure that the field teams all agree that yes, in fact, this is a great, you know, secure, safe technology implementation, but those are our most successful opportunities are when we're, we're working with P and L managers, business managers that need to solve a very specific problem.

[Erik]

And then you mentioned that you're moving into new verticals. I see in the, your company introduction that healthcare is one of those. And although you can think of them both as as industrial, I think the, let's say the, you know, you would also say, well, energy and healthcare are somewhat dramatically different in terms of the operating environments, right? As you mentioned, energy is remote healthcare. You're in a controlled facility, you have different con in both, you have safety and privacy concerns, but from very different perspectives, have you had to evolve your business significantly in order to move to this new vertical? Or do you find that the basic challenges that companies addressing are fundamentally the same? What, what, what, what are the adopt the, the evolutions that are necessary for you to move into a new vertical,

[Matt]

The healthcare space? Erik has a little bit of a misnomer. It makes it sound like we're, we're getting involved in medicine. We're really not. We're really doing exactly what you just suggested, which is we're taking our proven platform that works across pumps, motors, compressors, power equipment, and we're applying it in the facilities management or building management aspect of a big hospital. And so what we're basically doing is we're ensuring that that hospital systems, that their hospital buildings are ready to operate if you will, right? So we're not doing anything that's taken care of patients inside. We're not in the or suites or the ICU, or even the patient rooms. We're sitting below the, usually below the actual ground level in the chillers and the basement rooms. And we're controlling the HVAC systems, the pumps, the lights, the power equipment. And we're ensuring that all of those very expensive assets are optimized with how they're being run, that they are extending their useful life because healthcare an industry right now obviously is in very, very difficult position.

It's historically been an industry that runs in very, very tight margins and the global pandemic has pushed it over the edge. And so they are very much looking for ways to save money. And so they're building management facility management expenses are high, and that we're helping our customers dramatically reduce costs associated with maintenance of a lot of these critical assets. So they either don't have visibility into these assets, or they have very limited visibility from some very old antiquated enterprise software solutions that are, you know, like a building management system or a building automation system, just legacy, expensive software platforms. And those are typically very OEM specific. So they work great for train or they work great for, you know, Emerson, but as you know, all of these, these installations in these systems that are made up of many different manufacturers, pieces of equipment OEMs.

And so having a single platform that has visibility across everything is really being well received by our customers. And so that's, that's how we're doing it. And in healthcare we're doing the same thing and public utilities, the same thing, and manufacturing logistics shipping. We're starting to really get the opportunity to, to leverage the common platform that we've built and get it installed on lots of new machines. And then every time we bring a new machine on that's, that's really a new skew. It's part of the well-aware family. At that point. We just keep adding to that base every day, every week. So it's a lot of fun.

[Erik]

Okay, great. So that, that makes sense. So in all instances, you're dealing with legacy asset basis, somewhat conservative industries with a lot of also legacy software that it's not very well suited to modern needs. So I can see why this would not be really a critical change moving into these other, other markets let's then go into your your tech stack here. So, you know, at least what I've seen, you're covering, I didn't know if you would frame it as a pass or a sass, but you're providing this kind of data management layer. You're doing the data and gesture, and I believe you had your own hardware and then you also do managed services. And it seems like it's a fairly full stack solution. Can you kind of walk us through what the architecture would look like and then what would be the elements that are central and which, which are the elements that are maybe optional or a case by case basis? Yeah.

[Matt]

You bet happy to do that. Yeah. Let me start with the business model. Cause I think that's the most important one and it took us some time to kind of finally iterate to the place where it seems to be making the most sense for our customers, which is all that matters. So we're in this with our customers, Erik, meaning we only charge a monthly fee for the data service, that's it. So we do have our own hardware. We do have our own software. That's all included as part of our monthly implementation for our customers, no CapEx required. We handle everything, hardware, software warranty. We ensure that those data collection platforms work for the life of the contract. The easiest way I would, I would kind of draw a parallel or analogy to it is as like subscribing to direct TV. You know, they send you a hopper, you don't necessarily pay for the hopper.

You just pay for the monthly, you know, TV subscription to direct TV or to dish network, whichever one it is. And so well-aware is doing the same. We're providing intelligence edge equipment that goes out and is installed on the machine and that, that equipment we retain ownership to and we manage it, we provision it, it's an extendable platform. So it's got intelligence on the edge. We handle all the, what we would call the OT protocol interfaces. So how, how our edge equipment actually talks to the machine, the ability for us to kind of get x-ray vision into the machine. So we look at any IO opportunity we have with that machine or that sensor. We also look at, you know, the OT legacy protocols, we support pretty much all of them, mod bus, canned bus J 1939, number of other, you know, backnet and some other things as well.

And so where that Rosetta stone that kind of connects to that legacy OT protocol infrastructure that machines might talk to, we unify it on the edge. We add intelligence on the edge, which is processing capability right there, where we can run local ML and digital twin technologies and things like that. We've already begun to do some of that. We have storage on the edge and then this is probably most, most cool. We put a very rich user experience on the edge. And so our, our edge hardware wirelessly communicates to mobile devices and we use our customers, mobile devices, whatever they may have an iPhone or Android. And that becomes the user experience for our customers. And that's a very, very rich user experience platform that we didn't have to build, but we can leverage over time. So that's just the edge. The second layer is pulling the data back from the last mile, wherever that might be right out in the middle of nowhere or in a basement or, you know, on a large factory floor, we bring that data back either via cellular satellite.

And in some cases, wifi, once the data is brought back, it's stored into both of our cloud partners, which are AWS and Azure, and then we have a normalized dataset. And so, you know, for those interested what a normalized data set means is it's time synchronized and it's, it is aware it's data aware. So meaning we contextualize what that asset is that we're, that we're monitoring in the cloud. So it's not just a, you know, call it a data tag with a voltage or a current it's actually a company or it's a Cummings gen set, or it's a, you know, Baker Hughes, ESP pump, or, you know, whatever the case may be. And so it's contextualized as a thing. And the data is normalized, meaning it's time sinked and it's high resolution, and that's all landed in the cloud. And then once it's in the cloud, we have kind of a fork of how the data can move.

And so the data can obviously be consumed through our user experience. We talked about the mobile before, but the well-aware mobile app, which is extremely handy if you're in the field with devices or if you're at home and you want to take a look at any critical infrastructure or receive alarms your mobile platforms, a nice way to do that. And then of course, we have a web based platform. That's got charts and a much more rich user experience for notifications, reports, dashboards, and some things like that. The data though is also made available through API APIs for our customers to consume in any additional user experiences. So some of our customers use Spotfire some use Tablo, somewhat the data pushed into another historian like OSI PI. We do that for many of our customers today. So it's, we've just really tried to make it simple.

If I think about what well-aware is excellent at, it's really the data collection, the provisioning and the data orchestration from the edge. We really solved the last mile across any machine where a little weaker on the predictive analytics and a lot of the really, really advanced machine learning. What we do provide is excellent data sets for those engines. And, you know, it's like anything in life, Eric, if you're, if you've got a predictive analytics or an AI platform and you feed it bad data, yeah. It's going to give you a bad result. And so well-aware is a great partner for really advanced AI ML platforms. It's that particular area of the stack is not something we've chosen to invest in. And we really look to partner there more than anything. So that's kind of how that's a little bit of a walk through the, the full stack. Obviously it is a huge part of every element of that. And we have, we believe one of the best security platforms out there. And so we can make it easy to deploy, very simple to our customers from a business model perspective you can get going for as little as 50 bucks a month for a machine and it's secure.

[Erik]

Okay, great. So, so thanks for the very comprehensive walkthrough. Let me follow up with a few, a few questions on some of these elements of your business model and your tech stack. So going back to the business model, you just mentioned as low as 50 bucks per machine. So I suppose this is a, a per machine per month fee, but then you would have different tiers maybe based on the complexity, the number of connections for a machine or the amount of data. Is that the case? Is there any aspect that's related to the volume of data usage system integration? You mentioned ML. So if there's a need to develop a predictive maintenance application for a particular machine, you know, I guess somebody has to actually put some labor into that, whether that's well aware or a system integrator or a customer. So maybe you can, you can just walk through a little bit more in detail, the the business model, what would be the, the elements that would determine what this monthly VR

[Matt]

Yeah. You bet. Well, the 50 bucks a month is really based on an entry layer solution and it's all inclusive. So it includes all of our edge hardware. It might include some some sensors depending on what kind of application it is. And it's, you know, it's going to be a fit for purpose solution for the value that we're creating. And, and so yes, there are scenarios where we have to, you know, rapidly develop some apps if you will, or some, some customization tailoring station for our customers. Everything that well-aware does is platform based. And so we don't, we don't really ever build anything for customers that the customer owns. We will tailor our solution though for customers. And so, you know, depending on the application, the machine and the value attached to that machine, that's really what determines you know, the ultimate price point for our customers.

And so, you know, we, we have applications where we get 50 bucks a month for our solutions. We have application where we, where we get hundreds of dollars a month for far solutions. And, you know, those, those include different layers of sensors and hardware. That's all included under a very simple flat, you know, subscription model. So it, it really is just application dependent. You know, if it's tank level monitoring, it costs one thing. If it's pump monitoring and control, it costs another, if we're controlling a, you know, $350,000 train HVHC system with a lot more data, a lot more complexity, a lot more value than it might cost a little, a little more so that that's, that's how it's set up. It's it's really value based. We don't waste a lot of time with customers in every case. Our customers ROI is typically orders of magnitude more than what they're paying well aware. And we're in a growth mode as a company where we don't want to be stingy and focus on extracting every pound of flesh possible for our customers, from our customers. That's not our goal. Our goal is to keep delivering value and case studies and keep getting the word out because, you know, look, there's 25 30 billion machines that need to be connected out there. And we're just beginning to scratch the surface.

[Erik]

Yeah, well, and I was going to ask also about connectivity, you know, satellite costs. And I assume those are, those are all wrapped in. And I like this model because, you know, as opposed to maybe the more traditional model of pushing either a fixed license or a, a, you know, kind of large CapEx asset investment which is kind of one time, and then you can walk away and then the customer gets to deal with the operations here. You're really well aligned, right? You need to be delivering value consistently. Otherwise the customer at some point will cancel the contract, right? And you've invested a lot of time in building the solution.

[Matt]

That's exactly it, 100%. I mean, we are, we are being paid to deliver TV service. So if I want to watch ESPN, I subscribed to a TV TV service, well, awareness business model for IOT is the exact same. We are aligned with our customers on business outcomes. And what we find is that they really like to reward us when we work with them and we prove and show them the value that's been delivered, they will stand on the mountaintop and proclaim the value that we've helped them to capture and use more of us. And so that's, that's a win, win scenario,

[Erik]

A mobile application. So this is an area where at least in my experience, the requirements can shift. You know, whereas the, let's say the fixed, maybe you're using satellite, you have some sensors, you have a particular kind of connectivity environment around the edge. Those can be fairly fixed in the longer term, but the requirements around how users are using that data different. So we see this kind of shift towards more of a low code development environment, trying to allow users that are nontechnical to, to make some modifications. How do you approach this right now in terms of the, the end user application?

[Matt]

Yeah, it's a great question. So, you know, we, we've standardized on some, you know, some pretty baseline functionality that I think gets our customers. Like I said, 80, 90% of the way there, there's just a lot of you know, core feature functionality that exists that is all configurable, but it's configurable, you know, in the platform by our customers. So they can, they can set up assets, they can set up taxonomy, they can set up names and, you know, they can configure charts and they can set up notifications and alarms. And all those things are, are, are meant to be very user managed and manipulated. And so that took us a while to get that dialed in appropriately. Probably one of the things I'm most excited about as our our, our true edge intelligence platform. We are building an open developer environment, Lennox based environment on the edge, and it is going to allow our customers to, you know, write their own apps in low code Python, scripting, whatever the case may be, and, you know, really make it very easy for them to write new apps, deploy new apps and manage it on the well-aware edge platform.

And so the, the example that I'll, I'll very humbly use here, Eric is, is, you know, we really love what Apple did for, you know, building an end to end developer community and the app store controlling the edge platform, which was the iPhone or the iPad or the iMac, and really owning that into end user experience. And I think Apple's obviously been very successful and doing that well aware is doing the same thing, but for machines. And so we're, we're taking that edge platform and, and in the 2020s over the next decade, it's, it's our intent to continue to build that out and provide a full environment where customers can contribute to what they're doing on the edge. Third party application developers and communities can be built around it. It's all an open platform. It's safe, it's secure and it's proven and reliable. And so, yeah, we're, we couldn't be more excited about, you know, what the future holds in terms of, you know putting control algorithms or, you know, enabling new widgets on the edge. So it's, it's, it's already happening today. We're just in the front end of it. But it's something that we're all very excited about here at malware.

[Erik]

Yeah. Fascinating. Fascinating. I mean, this is one of our beliefs also is that the companies that are going to be very successful in the longterm are the companies that figure out how to create value by incentivizing other individuals or organizations to to engage in development of their platform. You know, in some way, right, as you said, this is, this is kind of the Apple model, but going it alone and trying to do the full stack yourself. That's probably not a winning proposition for the complexity of the industrial environment that a company like well-aware is trying to serve. So we wish you the best in executing that next stage of building out your platform.

[Matt]

There's a lot of foundational infrastructure that's been built that we want to make available to the market and allow for much rapid, much more rapid deployment of solutions. And so, you know, we have a limited set of developers and our customers in the market doesn't have a limited sense. So we're, we are in the process of opening that up and making it a full, you know, shared open community platform, which is exciting.

[Erik]

Let's say if customer a build something for a particular type of asset, you would then be able to say asset assess somehow that the algorithm or the source code in order to deploy that for another customer, is that the case

[Matt]

We'd be able to certify it and make sure that it is functional. And then, you know, there's, there's an opportunity to potentially leverage that, that code environment, if that customer contributed contributes it to the open environment, then yes. There's other customers that could absolutely leverage that. Yes.

[Erik]

Okay. Great. One final question here. Is there also a monetization aspect for the developers? So I guess if it's a, if it's an oil and gas company, they're maybe not worried about monetizing this, but if it's a, an ML company that maybe wants to use well-aware to build an algorithm, what do you have an aspect where somebody that develops code could then monetize through well-aware

[Matt]

That is the ultimate intent. Yes, we are not doing that today, but I don't think we're very far off at all. That would be a 20, 21 milestone achievement for us.

[Erik]

Okay, cool. Let's go into a one or two case studies here. So it'd be, it'd be great to have a end to end perspective from, you know, who did you first start talking to at the client? What were the, you know, did you do a pilot for them and then, and then kind of walk us through two operations,

[Matt]

A couple that come to mind that are, that are some of my favorite ones. One of them is with the largest steel manufacturer in the U S so I'll start starting a non oil and gas application. So we're installed on us steel. They've got a very large, very historical plant in Gary, Indiana. It's 10 square miles. So it's a very large plant. And it's been around for over a hundred years is actually originally a Carnegie site. So it's, it's again, it has a lot of historical reference and relevance to it. We were contacted by us steel through one of our partners. And they basically were really struggling because the infrastructure of that plant had become pretty aged, pretty antiquated, a lot of the original sensors and infrastructure they had put out there had also become antiquated. And so they were having some pretty catastrophic negative outcomes associated with gas, distribution and power substations across that 10 square mile plant of which there's a lot of, both of them.

And so what they wanted to do is, is get a much more high resolution monitoring and control capability across all their gas distribution, and also across all our power substations. And so we began talking to them, we went out there, we installed on a, on a pilot location for gas distribution. We were hooking into an existing gas sensor. And so I'm going to get into a little bit of detail here cause it's fun. And it'll show you how the platform works, Eric. But we were told when we showed up on site, that the sensor we were going to connect to was a pressure sensor. Okay. That would be very straightforward for well-aware. You go through all the certifications to get on site. You go through the onsite orientation to actually physically step foot on a, you know, an industrial location like us steel. Our team goes out to this first proof of concept and we walk up to the sensor and we realize, gosh, that's not a pressure sensor.

That's actually a gas flow sensor. So any of our competitors, any of the old legacy players that are out there today, they would have packed their bags up at that point and headed home. They would have kind of probably yelled at everybody and said, Hey, you gave us bad information. Well, that's just what real life looks like out in the field. And so while we're used to that, we have a lot of scar tissue. And so we made a mobile configuration right on, on the spot. We changed our edge device to be able to accept gas flow instead of pressure. So we made the install, got the mechanical and the electrical connection. And all within a matter of five to seven minutes showed our customer standing behind us. We had a little bit of an audience. We showed them the gas application. So we were monitoring real time gas flow.

And unfortunately one of the guys behind us said, Oh, that's not what we wanted to see. We're not interested in realtime gas. We're interested in accumulated gas flow. So you see right there on the display on that old sensor, it actually accumulates the gas flow for us. Well, the problem is there's not an electrical interface or there's not an electrical output from that legacy sensor that would give us an accumulated gas flow. So right there on the spot, we had our team in the cloud build a gas accumulator. So within a couple of minutes, we were taking the real time gas flow that we had just tooked into. We had built a gas accumulator in the cloud that gas accumulator was then giving them the customer complete totalized via the guests. They loved it. Now we had one problem in order to get that level of resolution.

We had to back haul data every second. And so that would be very expensive, obviously. So within two days, our team wrote an algorithm that could reside on our edge intelligence, pushed it over the air and updated our unit, which was left behind with a localized gas analyzer. That's pretty cool. So us steel loved it. They rolled it out across all their guests distribution. We did something very similar for their power substations, which they had very little visibility into. They were having leaks into their power substations, which was causing the substations to go down. And then they were having very expensive downtimes in their, in their factory floors. And so that's one example that I, I love it kind of speaks to a little bit of the versatility and the flexibility of the well-aware platform. And now we've got the opportunity to continue to expand that across many, many more of not just that customer sites, but customers very similar.

Another application, another case study, this one just actually came in Saturday night. I'll just share it with you. I got a panic call from one of our companies said, Hey, look, we're in the city of Houston, there's a water management water treatment facility here. We believe that we're potentially going to be dealing with chlorine gas emission. So we need real time monitoring of air filtration platforms associated with ensuring that we don't get chlorine gas releases. And when he well-aware to come help monitor the equipment, monitor temperatures, et cetera. So literally took that phone call on the 4th of July Saturday night. And then that was successfully installed on multiple locations this morning. So all within 72 hours, there just aren't people who can do that. Eric. So that's, that's the platform being built and being forged and being tested, being highly configurable and being remotely provisional that just allows us to move very quickly with our customers.

So, you know, Houston is the fourth largest city here in the U S will now have the opportunity to expand out across a lot of their public utility infrastructure. And so just, just another example, outside of oil and gas that you know, that we just recently did over the weekend. One other one that, that I, I love to point to is we do work with the largest upstream midstream and downstream companies, helping them optimize their asset integrity programs. And so we work on pretty much every major upstream, midstream and downstream operator. In some capacity, we work in partnership with a variety of different service providers and we're ensuring for those companies that they are getting the right amount of chemical treatment to ensure that they're not experiencing corrosion, that they're not experiencing scale buildup, we're controlling pumps, we're monitoring tanks. We're doing real time control algorithms on the edge in the field on changing variables because that's, what's required to get to a, an ideal treatment solution.

And you just can't get that accomplished by sending a person out there in any frequency, which is the current state of the industry today. And so well-aware does that across thousands and thousands of thousands of sites here in the U S and increasingly now and in other countries. And so, you know, we're, we're learning as we go. It's not perfect. We've always had issues. And I like to say we have a lot of scar tissue along the way, but we've been very fortunate to have earned the trust of some of the largest fortune 100 fortune 500 companies in the U S and I think we've got the opportunity to expand that now both States side and internationally as well.

[Erik]

So it sounds like the deployments are quite quick, actually they're pulling the timelines and these two examples very, very quick, but I assume that there are also, I mean, there's a fair amount of customized need. What would be the, maybe for the two examples that you just gave, or maybe more generally, what would be a typical timeline from, let's say a first site visit towards having operational deployment across the facility.

[Matt]

There are absolutely exceptions some faster, some slower doing multiple sites and less than 72 hours as fast. And so that was something that was very, very fresh on my mind and something, I was very proud of our team for doing it. It was a safety issue and one that I was really proud that we responded to, but I would say typically, particularly for larger installations, hundreds of sites, it takes us, you know, between four to six weeks to, you know, once we receive an order, once the customer has provided us with a general idea of what the infrastructure and the machines and the sensors look like that we're going to be installing on, which by the way is many times absent of some detail. And so we get out there and when we start installing for them, one of the value adds for our customers is just really getting the well-aware inventory of what they've got out there.

And so it's an asset inventory solution in addition to everything else, but typically it takes four to four to eight weeks. We carry, you know, buffer inventory and stock Aero electronics, which is a very large company, is our manufacturing partner. And so we can scale up very quickly with them and, you know, they build units for us edge equipment and we get it provisioned and we get it out there. So that's a typical timeline. It really just depends on the machine, the application, the customer, the location, but you know, very seldom does it take longer than eight weeks.

[Erik]

Gotcha. And you're doing all of the hardware deployment by yourself. The integration work.

[Matt]

We have authorized technicians. We also like to train our customers. And so a lot of our customers become their own installers. We have a client success team that has incredible training and tools and videos on how to set everything up, how to configure everything. Our customers download our mobile app, which has set up wizards and provisioning wizards built into it. So we've really made it pretty straightforward and simple, a simple for customers. And that's how you get to those, you know, weeks of install, time versus, you know, what the industry is used to seeing, which is months and sometimes years. You know, so again, Eric, it's, we're tired of watching these, this very painful bloated, you know, value chain that exists of legacy automation, equipment customers, having to feel like they have to build their own telemetry networks and manage those and maintain them and buy enterprise software for SCADA and nother enterprise for workflow and ticket management, another enterprise software for historians, we're just compressing that very legacy and bloated value chain and, and our customers really appreciate it. Now we're also working with whatever existing installs they have. So they don't have to throw the baby out with the bath water. We're going to come in and work with what they've got. And, and usually when we show them how easy it is and what it looks like, then they like to give us a little bit more opportunity to expand

[Erik]

Great. Matt, I really appreciate taking the time to walk us through the business. I think this is a fascinating company that you're running this, this trend towards, let's say away from kind of isolated, you know, functional software towards more flexible software is, is a trend that we're paying very close attention to because I mean, you've just kind of given us a good walk through of the challenges that companies have in managing the cost structure and the complexity of these isolated products. Is there anything else that you wanted to quickly share with the audience or, or discuss before we call it a day? Look, I appreciate you guys

[Matt]

As having us on. And, you know, I am in this with every single person that's stuck with us this far to listen to the podcast. And if you're working in the IOT space, building solutions, I'm going to encourage you to tell you to do that. I think the opportunity is substantial. It has been hard for, for well-aware. And we're starting to see really the rewards from a lot of the work that we've put in. So I just encourage you to, to hang with it for the customers that are out there, partner with your vendors, partner, with your suppliers, share your outcome information that you're trying to get to upfront. So that together you guys can work on projects that are successful. You know, I always walk around well-aware, which by the way, is the third name of the company. Erik, it's the only one I didn't name, but I love the name.

So it just means informed. It works extremely well for oil and gas, obviously, but it just means informed. And so it really fits our, you know, our ethos and our strategy, our mission, but, you know, we're here to connect people to the things that matter. We are here to make it easy. And I'll tell you, it's, it's funny if I just think through the history and the last seven years of well-aware, you know, I used to talk about our hardware and our software, a lot, our widgets and our things. And it's taken me a while to realize our customers really don't care about that. They really just want, they want the outcomes. And, and I've also learned that it's very complex to make things simple. And so, you know, it takes time. And so we've been working on this and we've, we've been learning through, you know, doing some things, right, doing some things wrong.

And you know, I think now we're getting to the point where it's it's, it's just simple for customers. And even the business model, as you've heard is, is getting much more highly simplified. And I think that's what we're going to need to really get the industrial IOT market adoption to the place it needs to be. I hear people talking about IOT in a state of pilot purgatory that's because people are selling tools and they're saying, Hey, good luck. You know, go, go implement, go figure it out. Our experience has been when you partner with your customer and you're in it for the long haul and you're incentivized along with them on the outcomes, it's a much more successful experience. And so I think we're all working in areas that are very exciting. And I just want to encourage everybody to keep pulling and keep developing and really want to thank you again for, for having us join you. It's been a wonderful conversation. You've asked some great questions. Great. Well, Matt really appreciate you taking the time and I wish you, and WellAware the best in the future. Thank you, Eric. I appreciate it. Take care.

[Outro]

Thanks for tuning in to another edition of the industrial IOT spotlight. Don't forget to follow us on Twitter at IoTONEHQ and to check out our database of case studies on iotone.com/casestudies. If you have unique insight or a project deployment story to share, we'd love to feature you on a future edition. Write us at team@iotone.com.

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