The CEO of Everguard.ai, Sandeep Pandya, joins Ryan Chacon to discuss how AI advances IoT use cases and how it can save lives. Sandeep begins with a sharing the backstory of the company and then dives into a high-level overview of the current state of AI and the leading use cases of adoption. Sandeep then focuses on the importance of AI and its ability to protect workers’ safety. Ryan and Sandeep wrap up this discussion with a conversation around challenges to adoption and advice for companies looking to integrate AI into their business.
Sandeep Pandya is CEO of Everguard.ai leading the way in the incorporation of wearables with computer vision, machine learning, and AI to make the world’s industrial environments safer and more sustainable. Formed in 2019, Everguard.ai stemmed from Pandya’s belief that the world is experiencing a technological renaissance and that the nexus of AI, digital connectivity, and information sharing will fundamentally reshape and improve how people and their communities sustain each other. Pandya is a technology veteran whose experience spans product introductions and innovations in semiconductors, connected devices, wireless infrastructure, cloud services, and novel AI/CV applications. His leadership has helped organizations of all sizes establish high-growth markets globally.
Interested in connecting with Sandeep? Reach out on Linkedin!
Everguard’s mission is to protect companies’ most important assets — their people — with the first proactive technology solution dedicated to industrial sustainability. They’re revolutionizing how heavy industry approaches worker safety, health, and welfare using AI technology to support companies in their missions to fulfill environmental, social, and governance (ESG) initiatives. Everguard.ai are the technologists behind Worker-Centric AI™, the world’s first artificial intelligence platform to create a conscious environment powered by sensor fusion that senses distress and danger long before a human can. Worker-Centric AI™ ties together various industrial sensor technologies using sensor fusion, edge computing, and AI algorithms to enable them to perform in ways not possible independently. Everguard’s enterprise solution, Sentri360®, utilizes Worker-Centric AI™ technology to create a Sentri Zone™ with workers at the center, continuously protecting them in the most complex industrial environments.
Key Questions and Topics from this Episode:
(1:51) Introduction to Sandeep and Everguard.ai
(5:49) Current state of AI
(9:24) Use cases leading AI adoption
(11:23) AI for saving lives
(14:43) Challenges to adoption
(18:21) Advice for companies looking to adopt
– [Sandeep] And basically provide telemetry into software that now AI software, whether it’s operating at the edge in that little camera that’s understanding that the gentleman is not wearing his visor next to the glass furnace or it’s aggregating millions and millions of data points, you get productivity use cases ’cause now you can see, you know, operational bottlenecks before they happen.
– [Ryan] Hello everyone and welcome to another episode of the IoT for All Podcast from IoT for All the number one publication and resource for the Internet of Things. I’m your host, Ryan Chacon. If you’re watching this on YouTube, we would truly appreciate it if you give this video a thumbs up and subscribe to our channel, if you have not done so already. If you’re listening to us on a podcast directory somewhere like Apple Podcast, please feel free to subscribe to get the latest episodes as soon as they are out. All right, on today’s episode we have Sandeep Pandya, the Chief Executive Officer of Everguard.ai. They are a company who has a mission at protecting company’s most important assets, which are their people, with a first proactive technology solution dedicated to industrial sustainability. Very interesting company. Definitely recommend you check them out. On today’s episode, we talk a lot about AI, we talk about the current state of AI, the role AI has in the IoT space, how AI is even playing a role in saving lives with different types of applications and use cases, big challenges that companies face when they’re trying to incorporate and adopt AI into their solution and also general advice for those looking to bring AI into their IoT solutions. So fantastic episode overall, I think you’ll get a lot of value out of it but before we get into it, any of you out there looking to enter the fast growing and profitable IoT market but don’t know where to start? Check out our sponsor Leverege. Leverege’s IoT solutions development platform, provides everything you need to create turnkey IoT products that you can white label and resell under your own brand. To learn more, go to IoTchangeseverything.com. That’s IoTchangeseverything.com. And without further ado, please enjoy this episode of the IoT for All Podcast. Right Sandeep, welcome to the IoT for All Podcast. Thanks for being here this week.
– [Sandeep] Yeah, thank you for having me.
– [Ryan] Absolutely. All right, let’s kick this off by having you give a quick introduction about yourself to our audience.
– [Sandeep] Thank you Ryan. I am Sandeep Pandya, I am the CEO of Everguard.ai. Everguard.ai is a venture backed startup located in Southern California, focused on using deep technologies like artificial intelligence and industrial IoT to make industrial workers safer around the world.
– [Ryan] Fantastic. And what I’d love to hear, if you wouldn’t mind, is sharing a little bit about kinda how this company even came into existence. So, you know, I know there’s a unique story about kind of how y’all started, but what was the opportunity you saw, what were you kind of seeing not being served in the market, what brought this company into existence and kind of got you to where you are now.
– [Sandeep] Yeah, thanks for that. So, you know, I’m a technology veteran. I’ve been doing technology product development for over three decades, mostly at large blue-chip companies but back in 2015, I broke away on my first venture backed startup, it was focused on worker safety using deep technologies but in the commercial fleet space and as president over there, I guess I was recruited by one of the investors of Everguard, which is Boston Consulting Group and then their partner SeAH, which is a large Asian steel conglomerate to basically take a similar concept of using deep technologies for worker safety but in the industrial setting, particularly steel mills which SeAH has and they were looking for an experienced executive who could take seed capital and build the team, the tech and launch the product in the company so that not only will SeAH employees be safer, but you know, working employees in all industries can be safer. And for me, things are going great at my prior company, they’re on their way to becoming a unicorn. I feel great about that but the opportunity that really excited me, Ryan was in the pitch deck from Boston Consulting Group to me, which showed that OSHA, right? The body that regulates worker safety has found through their research that the top 10 incidents that occur on the job in an industrial setting generally are the same across all industries and to me that was an aha moment, which said that, and this was the pitch from BCG to me, which is, “Hey, come and be the CEO of this company and if you can help us build a safety platform, an AI safety platform for steel, we can go to oil and gas, we can go to construction, we can go to mining” and that’s really what we’re trying to do here, is just reach more people and so to be a part of that to define worker safety in a new way, so broadly, so quickly was just something I couldn’t say no to, so…
– [Ryan] Yeah, I think the, you know, that pitch they had to you, obviously it worked, but at the same time, it’s very relevant to the companies that we’re seeing via success in the IoT space right now when they’re able to build for a particular problem but it carries a lot of weight across industries and it’s something that is a common problem, not just in one siloed vertical but across many different industries, and it allows you to have a real opportunity for scale and I think those companies who have those types of solutions, have those types of products, are seeing a lot of success in the space that we, you know, we focus on.
– [Sandeep] I completely agree. I think the superpower that IoT has whether it’s industrial or otherwise, is really it’s horizontal scaling power, to your point. Which is, it’s a lot of, you know, essentially well understood technology but it just needs to penetrate different spaces and when you kind of dial it in one or two places, one or two verticals, or market segments, very quickly, if you’re smart, you can take it sideways.
– [Ryan] Absolutely. So let me ask you at kind of a high level here, I do want to dive into more of how AI is playing a role in saving lives and so forth, but I wanted to start a little further out and discuss the current state of AI. To a lot of people when they hear AI, they hear it as a buzzword, they really don’t understand exactly what it does and what it’s doing to add value to solutions that are in the market. But if you could start off by just telling us a little bit about how you view the current state of AI in general and then also the role it really is playing or you see it playing in the IoT space.
– [Sandeep] Yeah, great question. And you know, on its own it could be a very long conversation but in the simplest terms, you know, I’ve been doing AI on and off since the late 80s and early 90s, you know, when I was in grad school and that’s when AI wasn’t nearly as cool as it is today. And it was also less mature, you know, and the utility of it was a lot less because it was rules based programming, you know, if A and B then C. And compute power was a lot lower and so you really couldn’t solve anything but what they call an academia toy problems. Now what has happened is, you know, over the last three decades and so, a lot of other enabling technologies like in the smartphone world, have miniaturized processors, cameras, location technologies like GPS and basically created a much more interesting and affordable set of platforms upon which these candidly compute intensive algorithms can run and so that’s one thing which is, it’s gotten cheaper to do really, really sophisticated programming. But the other kind of, I would say inflection point in the AI world was the advent of deep learning which is a neural network type of programming for those that may know about it, but if it sounds too fancy, it’s really just a different way of trying to write algorithms that work better for things like image analysis or audio streams or any kind of signal that’s not as simple as A + B = C, right? Our conditional kind of stuff and so really what that did is it created a renaissance in computer vision for instance or you might have a smart speaker at home, so natural language processing, it just, whether it’s Alexa or Google, it just seems so much more intuitive now and that’s really because about a decade ago, deep learning kicked in and made understanding human language, understanding human activity, meaning is the person smoking? Are they putting something in their jacket in a retail environment when they shouldn’t, you know, just those types of human behaviors much more easily understood. Now, I’m not saying that the systems are intelligent, they’re just really better at information analysis when the information is this unstructured kind of image or audio stream and so anyways, that’s a little bit nerdy, but the enabling force is because it’s become cheaper to deploy in the industrial IoT world because the processors are cheaper for instance or cellular connectivity is more pervasive. And the algorithms themselves are different than 30 years ago, that perfect storm is now made AI much more approachable and you might have a ring doorbell that can tell it’s a porch pirate versus a car passing by, right, or the smart speaker can understand what you’re saying and order the right thing, et cetera.
– [Ryan] Absolutely. Are there, as it pertains to what an AI is able to, or is enabling within IoT, are you seeing any use cases kind of leading the way in AI adoption or another, I guess another question kind of related to this is how AI is advancing certain use cases or any particular use cases that you’ve kind of seen really kind of bubble to the top recently?
– [Sandeep] Yeah, I would say even outside of the safety world, one of the powers of IoT I think is extending connectivity to places where before you just couldn’t, so whether you’re on the shop floor of a fabrication facility or inside of a bar mill or on a construction site, you know, these are really challenging environments in which to operate, right? They just are. And the power of the IoT community is to figure out how to create devices that are connected, that can do work, like maybe sense things, sense the state of a machine, sense the air quality, you know, et cetera or even human behavior through computer vision and cameras. And basically provide telemetry into software that now AI software, whether it’s operating at the edge in that little camera that’s understanding that the gentleman is not wearing his visor next to the glass furnace or it’s aggregating millions and millions of data points you get productivity use cases ’cause now you can see operational bottlenecks before they happen. Or you can see that the worker is looking the wrong way when the crane is approaching. Right. You can now create a world of what we call not just predictive analytics but what we call prescriptive, which means I actually not just am predicting something bad will happen or unintended, but I can prescribe the solution in real time, in hundreds of milliseconds and IoT is that backbone that enables that, the compute plus the IoT actually makes all of that happen.
– [Ryan] Fantastic. So I wanted to kind of pivot towards the focus area that you all have because I think it’s a very interesting space that we haven’t covered all that much and it’s around utilizing these technologies that we’re talking about to save lives and particularly as it relates to worker, that workers who work in these challenging environments, so construction, industrial manufacturing, you name it. Can you just talk a little bit about how AI is really being used to help protect workers in these environments and just kind of in a general sense?
– [Sandeep] Yeah, no, I love that question and we at Everguard have created a framework of thinking about these complex environments ’cause if anyone’s walked the floor of a steel mill or a construction site, it’s as busy as the busiest airport, right? I grew up in Chicago, we always took pride that O’Hare Airport’s the busiest airport in the world. I’m sure some people will argue with that, but the bottom line is these are highly complex environments. People moving vehicles, machines like cranes, the air quality itself, and then the operation which is not allowed to stop if it can be helped. So we have a framework that breaks it up into four buckets and AI exists at all of them. So there’s the worker level, boots on the ground, right? There’s the workspace, that is the man or woman to machine interaction. So vehicle to worker, crane to worker, machine to worker, you know, it could be machine guarding, high speed machines. Then there is the work environment. So OSHA for instance, as it relates to safety, maybe people know this or not, but it’s not just about what the worker is wearing or how they interact with the machine, but the air they breathe, the light pollution, the noise pollution, all of that have very strict requirements to keep the workers safe and so you need to monitor that with the right types of sensors and then ultimately, you know, when you have the worker, their core physiology, PPE, the workspace, their interaction with machines and the work environment like environmental sensors looking at air quality for instance, or noise or light. All of that telemetry aggregates into what we call the corporate governance layer. So as the ESG movement, as you know, Ryan, is all about sustainability and corporations doing the right thing to keep workers and their communities safe and wholesome. How do you do it? Where’s the data coming from, right? It’s using paper and pencil while people walking around manually. Well, in the 21st century, that’s crazy. But IoT plus AI, what it allows is it real time telemetry to flow up to the governance level, so the C-Suite, the board of directors, shareholders, they now know that when you have an impact report from that big operation that there’s credence, there’s credibility to it. And so we’re an enabling force, I think IoT and AI can provide that real time telemetry and then when you use it the way we’re using it, which is prevention of incidents, whether they’re environmental or worker or injury related, then you have the force going in two directions.
– [Ryan] Absolutely. Yeah, that’s fantastic to kind of break down for us and very powerful kind of as you can explain here, how those technologies are enabling things that weren’t possible before? In those deployments that you’ve been involved in and the, you’ve seen companies adopt these technologies and implement them, what are some of the biggest challenges that you’ve seen in terms of the adoption side of things? Like when you work with a company to deploy a solution what challenges are companies oftentimes running into and how should people be thinking about it who may be listening to this so that they can kind of get ahead of it when they’re planning for the implementation of this type of technology?
– [Sandeep] Yeah, I would say, two buckets. I like to think in terms of frameworks and so there’s one frame which is the maturing of the technology in your particular space and so what I mean by that is, and folks that are from an AI world or a tech world with some familiarity around AI, AI basically trains itself through additional data to get more and more precise, right? I can use the word learning if you wanna give it a, if you wanna personify the behavior but basically the more data you feed an AI algorithm, the more precise it gets. Facial recognition or you know, whatever, what have you, right? So when we drop some new use cases in, you know, to monitor PPE or the way people are interacting in their environment, even though we might have done that use case five other times in five other facilities, AI is a little bit sensitive. Meaning if the lighting changes, if the the background clutter is just a little bit different, there can be a little bit of a startup cost to retrain the models, what we call models, the AI algorithms, to make sure that the KPIs, that the key performance indicators are in the high 90%. So just coming in, it might be 70% or 80% but with a little bit of retraining to make it bespoke to your environment, it’s back in the 90%, but it needs a little bit of time. On the other hand, there’s some other technologies like vehicle to worker anti-collision systems that are radio signal based, they just work out of the box. It’s just radio technology, right? So that kind of nuance, little bit understanding of how to deploy and the patience is helpful. And we’re talking about weeks and months, not months and years, right? The other framework is the change management piece, the organizational piece, which is, some of your audience might say, “Yeah, that’s all great but you know, we’re in a union shop, the guys are never gonna accept cameras in there” and I’ve done this now for eight years after being a deep tech guy in big companies. For the last eight years I’ve been doing worker safety through AI and first in commercial fleets where drivers didn’t want cameras in their faces and you know, now on shop floors and steel mills and manufacturing facilities. What we have found since 2015, is that people, believe it or not, are more comfortable with AI, it’s less mysterious, people have a smart speaker, people use their smartphone, they have ring-
– [Ryan] They don’t think it’s gonna take over the world or any, or like-
– [Sandeep] Exactly. I like to joke, it’s not Arnold, it’s Alexa, relax. And for that reason there’s a little bit of anxiety but believe it or not, we’ve talked to some of the largest unions on different continents and they get it and they understand that this technology while it appears creepy, it’s not meant to be, it’s not smarter than it looks, it’s really just trained to do specific things, like is that person wearing a hat? It doesn’t know that they’re smoking a cigarette if you haven’t trained it to do that, right? It’s not watching you in that way. So, long story short, I would say that the change management piece seems like a barrier but it’s not really if you just train the team, talk to ’em and the two things together help us roll out.
– [Ryan] Absolutely. And I guess to kinda add onto that as one of my last questions before we wrap up here, what advice do you have for companies looking to bring AI technology into potentially even existing IoT solutions or to help solve other problems that until now really weren’t possible for them? What kind of advice do you have for them to kind of how to approach it?
– [Sandeep] I would say just very simply the technology is ready. We understand that change takes time, so get started now, you don’t have to spend a lot, there’s companies that are willing to work and start small. One thing I learned in business school is an old phrase, “Trial leads to adoption”. Do a trial or two, get everyone comfortable and then really start making your environments better and smarter with this tech.
– [Ryan] Absolutely. Yeah, I think it’s a very common piece of advice, especially with the conversations I’ve had in the IoT space when you know, start with a trial, understand how it’s gonna be incorporated into your business, into your legacy systems, your existing infrastructure, start seeing ROI so that you can then justify the means to deploy it at scale and then that’s kind of obviously where we’re all trying to get to. So fantastic advice. Absolutely. So for audience who’s listening to this and wants to follow up, learn more, dive into a bit more about what you all do, the role you play in the space, maybe follow up with any questions, what’s the best way they can do that?
– [Sandeep] Yeah, we’d love to field any questions, even if it’s just for your own edification, you just wanna learn more, we’re happy to talk to you. firstname.lastname@example.org and Everguard is just like it sounds, E-V-E-R-G-U-A-R-D.ai info@ and we’ll jump all over it and get back to you.
– [Ryan] Awesome. Well thank you so much for your time. Fantastic conversation, our audience I think is gonna get a ton of value outta this. We’ll make sure we link up all the necessary information in the descriptions and the content we push out around this when it goes live, but until then, thank you again and hopefully we can have you back at some point to talk about other topics related to what you have going on.
– [Sandeep] No, it’d be my pleasure. Thank you again, Ryan. Thank you listeners.
– [Ryan] All right everyone, thanks again for watching that episode of the IoT for All Podcast. If you enjoyed the episode, please click the thumbs up button, subscribe to our channel and be sure to hit the bell notifications so you get the latest episodes as soon as they become available. Other than that, thanks again for watching and we’ll see you next time.