How IoT and AI Save Money and Keep Machines Running!?

Speaker A: Hello world.

Speaker B: This is Better Tech, a podcast where we chat with some of the most successful leaders about the latest industry developments. So join us as we explore the world reliance on tech.

Speaker A: Hello and um, welcome to Better Tech. My name is Colin McCarthy here for another exciting conversation about technology. And today we have Rajesh from Energis, Energosh or Energioshio. Uh, uh, we'll talk about how that uh, could be pronounced and the background of that name in a moment and what it does in the IoT and AI industry. But Rajesh if you could just introduce yourself uh, and give us a bit of a background on you.

Speaker B: Sure. Good morning Colin. Uh, thanks for having me over. Um, so I'm Rajesh Solanki. I'm a uh, first generation serial entrepreneur. Um, this uh, Energos or Energos both are right, but Energos is a Greek word which means good environment. And that's how we coined the company with the original vision to work in the energy and mobility segment which is uh, transitioning to new energy and new mobility. We'll talk more about that. Um, about me. My first venture was um, uh, in access control and door control systems. That was a venture between Canada and India. It was a cross border. I was living in Vancouver and between Vancouver and Mumbai in India. And uh, it was uh, one of the first uh, early companies which uh, um, um, uh, made access control more software oriented from more hardware systems. Earlier the company went on to list on OTCI Exchange, uh, uh, uh, and was headquartered out of Nevada and then exited, uh, did a good exit. My next venture was in video analytics. It was started at a time when the video surveillance industry was moving from uh, analog to IP video, when the world was just awakening to things like city surveillance and mobile uh, surveillance. And we were very good at uh, some analytics for mobile surveillance where on uh, border transport, uh, uh, vehicles, uh, we used to deploy uh camera and analytics and uh, the software would detect any anomalies, ah, and any suspicious activities. We also exited that to a hardware company, uh, uh, which was like a world leader in video surveillance in 2011. Energos is um, coined from uh, you know, a Greek word called environment. And the idea was that the vision was always that energy and uh, mobility industries are transitioning. So when we say energy, the oil and gas, the power and utility which are the conventional energy are transitioning to renewables and the mobility, which is our IC engines on the road, transport is transitioning to electric vehicles and uh, you know, all the supporting infrastructure and uh, uh, these need to be maintained, these need to be operated. These are all distributed. These are uh, new, uh, infrastructure. Knowledge about the performance of these, uh, uh, industry equipment and assets is not yet known. And so there was a lot of focus, uh, at our starting point on gathering data from these assets like solar panels on solar farms and wind turbines and uh, electric chargers, uh, and wherever they are being set up. So if the EV chargers were in some instances set up on fuel stations, um, we were working on the entire forecourt, which would include the dispensers and the uh, EV chargers and uh, get in data, uh, understand how that equipment is behaving. What are the different, um, variables which affect the performance, what downtime does. And these are some industries where the, the entire performance depends on equipment uptime. So this was how Energos entered into the conventional asset maintenance, asset and maintenance management, uh, world more specifically for the energy and uh, mobility.

Speaker A: Right, right. We as consumers often forget everything that is operating behind the scenes to keep, you know, what we need as a consumer running and therefore us everything that appears in the grocery store shelves. As you talk about fuel pumps, uh, there's so much maintenance and tracking that we as consumers are just completely virtually oblivious to. Unless you're working in the industry like yourselves, obviously asset management and maintenance is vitally important. So how has, uh, Energos. Energos, Joss, leveraged AI and IoT, um, how does your platform really help organizations reduce that downtime and increase their efficiency?

Speaker B: So call it IoT is about, uh, the ability to gather data. When assets are uh, in either a shop floor or a factory, or they are distributed as public infrastructure as in EV chargers, or they are remote as in solar farms or uh, even infrastructure assets like roads and bridges. When these are, uh, you know, uh, very critical, uh, in terms of, you know, how people depend on them daily, then IoT gives you the ability to either gather data directly from equipment if the equipment is a communicable equipment, or attach some kind of sensors which gather data. So if it's a water pipeline, it could be a flow meter. It's as simple, uh, you know, as a communicable flow meter. If it's power, it could be a smart meter, if it's a room, uh, uh, uh, you know, where we want to understand the performance of H vac systems, which are heating, ventilation, air conditioning systems, then it could be a temperature and a humidity sensor. So either it's a sensor or it's a modern equipment like an EV charger, which is a communicable equipment. And so you plug in a data point and you gather data and pull it to the cloud and then uh, so that's Iot for uh, all of us. Well, AI is two things primarily when it comes to um, uh, asset maintenance, um, can either be agentic AI where triggers from those sensors can be deep linked to automated action. So for example if there is an alert from a charger or from a factory equipment, um, agentic AI would auto generate a job order for someone to go and attend to it. You don't need a person to do it. So the person the managers work would reduce. The manager could do other things. AI will take over. So that's agentic AI. The other is that AI models, which is machine learning models where data can be used to model it into building some predictive algorithm. So algorithms which will help you to predict that data is saying that this is moving towards a downtime or uh, a shutdown. And so you must intervene and do something before that happens. So that is the higher goal of maintenance. Higher goal is to have zero downtime and therefore to always be in a predictive mode. So this is where um, the role of IoT and AI in asset and maintenance management.

Speaker A: Right. And predictive maintenance is vitally important. Uh, and with a vast array of uh, IoT devices and different sensors, uh, what has been the most challenging part of integrating you know, AI into that sort of traditional asset management? Um, and how specifically do you tackle that, uh, with your platform?

Speaker B: Yeah, the most challenging thing is gathering data from legacy equipment. These are locked, right? Even if they are, they are supporting so called open protocols. These are open closed protocols, equipment OEMs and usually lock the ability to read their data even if they support an open protocol. So in the H VAC world there is a protocol called bacnet. Uh, in the industrial world there's a protocol called lawn work. A very specific kind of lawn work is adopted by the fuel retail industry or the oil and gas industry. All of these are locked protocols. So gathering data from them usually requires some minimum level of support from the oem. That is the most challenging part, getting the cooperation and then integrating and then getting good quality data. So I think the challenge really is getting good quality data. But on the other hand, more and more modern equipments have more and more open protocols. Like the EV charging industry has OCCP protocol and it's pretty much readable. So every uh, you know, every software developer like um, uh, like us can easily read uh, EV chargers which are supported by that open protocol.

Speaker A: Right, Right. So uh, it'd be good if you could get into sort of the real technical part of it. Um and you emphasize the uh, predictive maintenance uh uh, functionality in your platform and the benefit. So how does that the technology actually work and what are the tangible results that your clients have seen in terms of that uh, reduced downtime and increased asset reliability?

Speaker B: There are two key benefits that customers look for from solutions uh, like ours. One is that um, reduction of downtime. And typically customers can uh, expect a uh, reduction of 20 to 30% in their downtime which means that uh, the uptime is going to be that much higher. And also it means that there is a cascading effect on increase in the business in, in also increase in improved customer experience delivery. So these are one side of the benefits. The other is more on the cost of uh, the people because maintenance uh, needs physical people, the frontline people to go and take uh, some action. So if number of site visits can be reduced, especially for remote location or unmind unmanned, uh equipment like an EV charger is unmanned. Right? Ah, there is no one there. You and I will drive uh, in our cars and plug in. And what happens if something is not working? I had uh, um, an incident last month where I uh, was uh, in Santa Barbara and uh, I plugged in a charger into my Tesla and it got stuck and it wasn't charging and I had no idea what I'm going to do. And so I got stuck for almost half an hour before uh, the hardware decided I'm going to let this guy go. I have no idea why that happened. And I'm in the business, I'm solving the problem. Right. But then I'm living the problem as well.

Speaker A: Yeah, yeah, yeah. It's uh, you know we talked about a lot of this being behind the scenes, uh, and consumers not realizing and a lot of these industries work on just in time delivery. So with the products getting to the store shelves, they deliver just in time. I guess we also need that on the maintenance side as well. As you say, if you can have better analytics and you could do predictive maintenance on your equipment, your support personnel, your engineers can be just in time. They're in the right place at the right time to be more efficient. Uh, which then obviously is environmentally better um, and better use of their time. Uh talking about uh, the industry with technicians and keeping things maintained. Uh, you know there is often a technician churn, uh being a care issue with some of these field operations. So how does uh. Energos. Energos. Josh, I can't keep pronouncing it incorrectly. It's my mistake. You should remind us what the Greek word for it was as well, because I know the environment is a big part of the company's philosophy. So uh, how does your platform help companies train technicians faster, uh, and more effectively?

Speaker B: Yeah, um, it's one of the center parts of the solution. Uh, what we realized is that um, people who are the frontline workers are sometimes not even able to speak in English. Sometimes we saw that they are changing too often. And so we um, built some capabilities inside the platform for creating on the job, uh, troubleshooting guides. So our uh, solution has the ability for the frontline team to capture videos when they are conducting repair of an equipment, to g, to capture photos and to archive it in the app and then um, even add comments. So when somebody in the future has to go back to that equipment and if that person has changed, he or she will have the entire history of the equipment, including videos as the referrals and photos as referrals. So you will have a video history of the performance of that equipment and all the trouble that equipment had in the past. So that was a, um, you know, that's a very valuable way in which we help um, our customers, the organizations from um, having less reliance on people because people do change all the time.

Speaker A: Yes. Yeah. And it's wonderful to have that historical uh, record, um, and I think probably a lot of us do that ourselves. I know before I take anything apart at home, I take a whole bunch of pictures of it. So then I can refer to that picture to see, did the right screw go back in the right hole? Did all the wires get connected? Um, something I think a lot of us would have loved many, many years ago, building our own PCs. Um, but it's a wonderful tool now to help those technicians, um, and also the multimodal aspect of platforms and AI being able to take pictures and get analysis from it. Uh, I know I use that in AI platforms all the time to help me understand what a device is.

Speaker B: Absolutely.

Speaker A: What do you think? So we've talked to you, gave a good background of your history and the history, uh, and understanding of the asset, uh, management industry. What do you think is going to be the biggest shift uh, happening in, in asset management? And how are you going to be able to position yourself to stay ahead?

Speaker B: Yeah, good question. So for first shift, uh, is uh, the shift to mobile, uh, mobile first CMMs and asset management, uh, it has to. So in, in that way the term CMMS is a bit of an anomaly because it's not centralized uh anymore it's going to shift to mobile which means it's going to be on the mobile phones of the frontline workers. So that's the first shift, uh, that the solution while you will still have a web app but because it's a cloud based solution it's going to be a mobile first solution. The second shift uh, is IoT and AI I think there's no industry um, uh, which won't be touched by AI.

Speaker A: Right.

Speaker B: So AI and uh, IoT is linked to that because it gathers the data of an equipment specifically which in uh, our case is a very relevant use case. So these two are the technology shifts uh um, that are happening uh and which will unlock the market side from only larger enterprises doing asset and maintenance management to small and medium businesses also doing that. And especially the ones which are new age like the energy and mobility which are the new energy and mobility which are just being set up now.

Speaker A: Right, right. Obviously IOT and AI is having a huge impact uh on your industry and you can see it small and large. Uh, what one other industry do you think is going to have a uh, complete transformation with AI?

Speaker B: Smart manufacturing, manufacturing uh and all kinds of manufacturing. Right. The most obvious ones are process manufacturing. What is a continuous process manufacturing um, has huge losses if there is a downtime because it's a continuous process and therefore um, these uh industries will have a huge uh impact. What is a continuous process? Let's take an example power industry, uh, even the conventional power, even small nuclear, these are continuous operation, isn't it? Um even solar farms or wind is a continuous operation, isn't it? There isn't a time when you say okay panel, go to sleep. I don't need you to give me energy anymore. No, you need the energy supply to the grid all the time. So conventional um, um, um process, continuous process is definitely one. But then smart manufacturing which is people less factories will have uh, uh you know AI is going to have deep uh, deep deep uh impact on, on those uh, think robotics, think um, uh automated warehouses to lift material, you know those robotic forklifts, etc. So these are some of the use cases where AI is going to have a huge impact. But then having said that there's almost no industry where AI won't have an effect. But the others may have softer effect. Right. Like job uh work orders being auto created. So it could be for a building or any campus, uh, uh, any facility management, uh function. So those are softer uh effects of AI. But then the deeper effects will go into uh AI making most of the decisions of what to take where and how the process goes on.

Speaker A: Right?

Speaker B: Yeah.

Speaker A: You talked about agentic AI, those automation workflows based on a decision are really going to be changing how some of those uh, previously manual tasks can be further enhanced. Uh, and I've seen some great examples using uh, uh, Google Vertex AI uh to analyze images on a conveyor belt and be able to look at a circuit board going through and then being able to identify where there's a bad solder. Um so I think we're going to get a lot of improvements in product quality as well, um through all of uh, these things. I think ah, a lot of these improvements will be in efficiency and quality which is going to be some of the real positive parts of this AI transformation. So um, you know you've got, had a really long and established uh leadership uh and it uh, uh history in business and technology. What do you think are ah, some of the key traits that uh, really make for a successful leader in this evolving tech industry and space that we have.

Speaker B: I think this is where it gets a bit human. Um, a good leader is able to empower others in the team uh to do more than they think they can. So a good leader always um, gets uh, the best out of others and uh, I think that's one of the key traits um in my experience uh, and I have uh, tried my best to hone uh, my skills to do that uh, starting with how to learn um, to delegate. Right. Uh, as I'm speaking, I'm trying to recall but earlier there was a time when we hired a culture coach in the company and uh, um the culture coach was meant to imbibe a culture amongst the leadership to kind of own, take more ownership of outcomes etc. So that was my uh, assignment as CEO. I assigned that to the, I brought in a good culture coach. The culture coach came back and said the biggest problem is you, not others. I said what do you mean? And he said that you know, you are probably too directive in your leadership and you are directing people what to do but that doesn't get the best out of them. What you need to do is learn delegation and delegate outcomes. Trust people to deliver results.

Speaker A: Yeah.

Speaker B: And so that was a big lesson for me in leadership.

Speaker A: Yeah, yeah, that's, that's a wonderful message for everybody because directing people doesn't scale. Um, but delegating and, and pushing your staff, giving them uh, tasks, challenges, projects that are slightly outside of their comfort area, uh, so that they grow and learn, um, and Learn from mistakes as well, um, and giving them the space to do that in an environment is I think one of those great key leadership uh, skills. So it's been great talking to you for the last 20 odd minutes, um, and hearing about a part of the industry that we as consumers probably don't think about. Um, but it is absolutely vital. And now when I go around town and I, I look at establishments, uh, I look at my bank atm, I look at you know, fill up the truck with gas, I'll have some thought about you know, all of these devices and the messages that they're sending back and the signals that are being analyzed and how platforms like yours uh, are helping those companies maintain those devices. So looking ahead, uh, what do you think is uh, the most exciting future for AI, UM and IoT in operations and in maintenance? What are some innovations that we can expect to see from uh, Energos?

Speaker B: You know, Energos is growing both vertically and horizontally. So um, when you say vertically which uh, it's segment specific. So within the energy, the renewable and within the mobility, the EV charging and the mobility industry, um, we are very specialized in that and we have worked with very large companies and very small uh, companies in that space. And uh, the other is a horizontal growth that the asset and maintenance is really needed by every asset heavy business, every business which is a brick and mortar business which has equipment and assets, uh, uh, on which the business relies. And it could be quick serve restaurants and it could be convenience chains and or it could be hospitals, uh, and uh, it could be uh, uh workplaces. All these also dependent. And uh, you know we do have some customers across all these horizontal industries. Um so I think the capabilities uh, would develop in these two directions. I definitely feel that in the vertical space of energy mobility we would have very good AI models which are proprietary, which are edge models which are working and making decisions at the equipment in a distributed layout. Uh, and that is probably uh, one of the key innovations which will make sure that public infrastructure in critical sectors like energy mobility will uh, keep working for us and for consumers, um, day uh, in and day out without downtime. So that's one set of innovation that we surely do. The other set of innovation would be um, in the people empowerment across the horizontal uh, segments across various segments. Our observation is that people are changing very soon. The frontline staff is a Gen Z person. You know, it's not, you know, people born in the 90s or 80s, it's people born after 2000. It's people who are born in The Internet era or, uh, you know, they, they are very savvy. They, um, they have good, um, quality phones. Um, they move fast. They, they want to upskill themselves. And so they are not in one job, like enter this job and then let's retire in this function. No, they want to upskill themselves. Um, and so the next batch of innovation should focus on, or rather will focus at Energos on empowering them. And that could mean, um, upskilling them through training on the, on the app. Um, so I don't rule um, out the ability that if there is an electrical electrician who's a user and he um, is working in a conventional industry, but we can train him on the app to take care of EV chargers of the modern equipment, which he is not otherwise trained for, but we can train him there. So I think this is the other area where I feel that there is some exciting future where we can help people to upskill themselves and do more than what they are doing today.

Speaker A: Right, right. Brilliant. Well, I will look forward to that future. Uh, and I think uh, all of our listeners will too. And if anybody is interested to see what uh, Energos can do, just go to Energos A, uh, has a lot of information on the site. I learned a lot about uh, uh, EAM M Enterprise, uh, Asset management and CMMS M, uh, computerized, uh, maintenance management systems. So it's a very interesting world. And also the pricing there is on your site and there's a free tier so people can sign in and have a look around and explore the solution themselves. So thank you ever so much for talking to us, Rajesh. Uh, thank you to everybody for listening to this Better Tech podcast.

Speaker B: My pleasure. Thanks for having me, Colin. We look forward to bringing you the latest industry news in our next episode. In the meantime, check out our other episodes@techcell.com podcast and be sure to subscribe, subscribe to our YouTube channel so that you never miss an episode.