Emory Sullivan with Genba.AI

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Are you doing having a good conference?

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You having a good time for me? Yes, absolutely. It's been great. Yeah. There's nobody else in that seat right there.

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Right, you're right. You're right. You come over to our house, you sit at the coffee table, and lo and behold, I'd be talking to you. Yes, it's been fantastic so far. Day one has been super busy looking forward to a great day tomorrow.

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Yeah, I'm telling you, I've enjoyed this event I've enjoyed. And I think I've mentioned it on a couple of other podcasts. And that is, it's not too big. It's not too small. It's just like, right, precisely it is. And you're able to have great conversations. And there's still a lot of activity. And I think Fluke Reliability has delivered on a really special event. All right, before we get into the topic of choice here.

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Give us a little background Emery on who you are, where you come from. And by the way, again, listeners are card has substance. Yes. There you go. Yes. Happy to be here. Thank you. So I've been in manufacturing my entire life, my entire career, I should say what?

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I am ready to go just one second.

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commercial and marketing roles. It was around that time that I became really obsessed with this problem of productivity and leaky critical knowledge for that frontline worker, I just really felt like they were largely ignored on the software side.

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And let me just sort of interrupt real quick. Did you just say leaky? Yeah, yeah. So this idea of, you know, frontline. Workers really have to facilitate a lot of critical knowledge in their day to day are really good analogies. We think of them as doctors and machines as patients. Right? So when you when you go to the doctor, your doctor has asked you, you know, Have you have you been sleeping? And what vitamins are you taking in how's your diet, they need all of this context to treat you properly. And it's exactly the same for frontline workers, and especially frontline maintenance workers, they are the doctors for those machines. And so you you know, you go out even today still and you see a lot of manual work around notebooks, scribbles on the machines themselves, emails, text messages, etc. There's really no good system available for them to maintain that knowledge. And so it's really siloed people are retiring, taking it with them. You know, everyone knows about this is going on. Here's a little analogy, just I'm not sure if this is encouraging or not. Or it takes the wind out of your sails, or it just puts wind into your sails. So I pretty much straddled the fence on that comment. Is this this issue that you've mentioned? It's been here for FERS decades want the needle to move? I know just I couldn't agree more. Right, exactly. So I was upset because in my mind, the solution was so clear, and I just like happened. No one's done this before. So I became obsessed with this problem. And, you know, started I worked on a couple innovation teams internally at Fluke to address it. We had some good concepts, but it really never went anywhere. And then I went on to be an innovation consultant at Fortive. So Fortive is the industrial 500 the parent company of the major industrial pipeline. Yes, it sounds it sounds a fortune 500 Yeah, I was I was getting ready to sound so racecar life but anyway, go ahead.

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Sorry, I'm missing my my words.

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I'm sure some of your listeners

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or the outside of the fact that it's a hard name to say. Quickly, Willa. Yes, it's Yes. Speak slow. Yes. And so especially now we're gamba a real wear brand. So it's especially lengthy and malby. But URL is available. I guarantee it is.

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So, but this was a super exciting because the vision of gamba was never to just be a mobile application. And I can talk to you about what we are in a moment. But the vision was always to have a hardware extension to the experience. So it was a perfect match. You know, it's been great. So um, so yeah, that's that's sort of how I came to to start gumbo. Yeah, listeners it is. g e n b a Genba, so just genba.ai. That is the website. So yeah, don't go to.com. Yeah, I don't even know where that is.ai got AI. Yes. Okay. You're speaking at this event? Yeah, so I gave a talk today, I'm really talking about how, you know there's a shift when it comes to CMMS. Is there there's a couple things happening. One is they're becoming more mobile centric. Right. So historically, it's really been designed as a database. It's very top down. And it's really made for that manager that's sitting on a desktop.

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Right, the word gamba actually comes from it's a Japanese term, but it's especially prevalent in Lean Manufacturing, which comes from the Toyota family. If you're a manufacturing nerd like me, so gamba actually means the real place but in terms and manufacturing, it really means where the work is done or where the value is created. So gamba we named the company thus, because we really believe that technicians are really just getting by with software that really wasn't made for them if we're using software at all. And there's a ton of value to be unlocked when you enable those frontline workers, not with just a better tool to make it easier to open and close work orders. But really, really think about what problems are they facing? What decisions are they making, from the moment they stop onto a shift to the moment they leave a shift. So gamba is a really smart, slick mobile application that enables that frontline workflow, and we integrate into the CMM CMMS. Right, we have to because that's the brain of the of the team. And we don't want to create data silos here. But we really are just religiously focused on that frontline worker, and that's where the value is there. Okay. You indicated CMMS chef's got it. Yes. mobile centric. Got it. What was number two? Yes. So now there's a push to integrate, you know, hardware into that. CMMS. So, you know, sensors is a big one. Yeah, does managers are bringing not the, you know, the sensor data, they want it into the CMMS. They typically sensors have been piping data into their own software systems, and managers are pushing their student messages to integrate with those systems. And now we're starting to see a wave.

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It's very, it's still quite early, but this idea of wearables, so having, you know, frontline workers pickers, for example, you know, throwing on like a headset, that's assisted reality headset has a camera maybe has a microphone.

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Are you guys dabbling in augmented reality type of technology? Yeah, I think the term that we're using is really assisted reality. But you could say augmented to so so you know, real well. Honestly, I have no idea the difference. All I know is that you're, you're using some sort of technology to help aid you in doing your work. And it's visual, which is important. Exactly. And that's, that's good enough for me Exactly. Right. The idea is that you have a visual in front of your face, right. It's not obscuring your vision, but it's there to support what you're doing. So we're starting to see a lot of maintenance managers and plant managers push for an integration into these headsets because their teams are starting to use it specifically for the See What I See use case, right a technician walks up to machine it's down, they don't know how to address it. So they call a subject matter expert or a manager that's off site. Maybe they're across the country, they're sleeping, whatever.

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So that we use case is already starting to happen. But we're starting to realize there's more there, especially if you integrate into the system. So imagine a technician throws on a headset and is taken audibly through their preventative maintenance workflows, or they can snap a picture and it goes right back to the CMMS in real time to that work order. So that's that

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type of integration that gamba is facilitating now that we're in the real where?

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Family, right but integrated into emaint. So we're a big, you know, happy family of free brands. And we're working to bring this experience to you, my customers. Yeah. And just so that, you know, I'm writing things down because you're just peppering me. And by the way, I see that you're looking at your presentation on your reel. Actually, I haven't had to use it much to be

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ready to say, oh, my gosh, she's just rolling in. It seems so seamless. Unlike many, it wouldn't be so seamless, but you be in a professional.

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Want to get my facts wrong. So you know, I always hear like, yeah, there's, trust me there. We have a great community of listeners. Nobody ever fact checks. I've never heard anybody say, whoa, whoa, whoa, whoa, you know that Emory girl she was talking about. Now. It doesn't work. No. Okay.

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You're You're fine and dandy. So let me ask you this question. So we have gamba. We have this wearable, we have this integration, we have all of the mobile component associated with this. And as this shift,

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fluidly legacy, all of that stuff.

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Take us in the listeners through where we're going to put that future head on, sort of paint that picture. Where we're going, um, says it's moving so fast. Yeah, that's just like it's a yes, yes. I can't keep up. No, I have, I have some juicy things that I can I can walk you through. So yes.

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Yes. So okay, so one is we just so

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we just released a really advanced analytics solution. So you know, gamba, the mobile solutions on the floor, it's making it really nice and easy for technicians to do their work that you've got that real time data, copy back into the system. Now you want to do something with it. So we are we've developed this really nice, advanced, intelligent sort of dashboard that we're starting to, to sell, actually, this month, a couple things there. One is we are beginning to trend keywords. So we're able to actually pull the technician comments and the problem descriptions apart and tell managers, hey, you have a recurring problem around a certain machine smoking frequently, or whatever the case is, right? That's a really challenging conclusion to come to without that I hate I hate to sort of the I'm like this little, little cloud, sort of, I want to understand this dashboard, and you're, you're pulling keywords, you're looking into, let's say, email, and you're looking at some key words, and you're pulling out

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sort of trends or so.

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Yes, exactly. which then gives you a painted sort of, it's like a customer profile, but you're looking at it from a from an asset profile, saying, Hey, this is what people are really saying precisely, exactly, you know, so even five years ago, the natural language processing tools, were still pretty nations and expensive. Now, they're much more commoditized and accessible. And so, you know, it's more affordable for companies such as Canva, to layer this technology on top of these systems, because Sima messes are, again, databases, but there, there's so much knowledge locked away. So you can do things like layer natural language processing on top to allow keyword trends and other things to be pulled out. Another thing that's happening is, maybe you're it's a very new thing, it's called Chat GPT. Three, it's the latest in, I'm quite familiar, yes. But I'm not gonna speak on it, because that's way out of my realm of saying same. So I'm not an expert, but what I can say is, it's a, you know, a massive step forward, it can take massive amounts of human data and human syntax form, and, you know, analyze it and serve it back to you in a in an

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in again, in human syntax form. So there's now the possibility to layer GPT, three, on top of your CMS data and query it as if it's Google. So you could go to your CMS and say, hey, when was the last time this machine went down, or something like that, and it will respond to you as if it's an assistant, and then present the work orders beneath that answer.

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You know, it's so funny, but when you mentioned ChatGPT Of course, somebody said, Hey, Scott, you gotta go to check out ChatGPT Okay, it'll go out there and I started so I know just put this in, just to see it. Like, hey, give me a call to action on something and it just doesn't Imago Yeah, I get all giddy right. Yeah. And then all of a sudden it starts to open up all of these other possible use cases that that strike there.

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I still I'm not I'm not at that level with you. But it is quite exciting. And how this this technology is

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AI, it can be a little concerning, right? I mean, it's like, I'm getting a little nervous about it, because what it can do, but then again, it opens up really some really interesting new horizons. And I never heard you're the first never heard anything about taking and layered it on top and to be able to use it in such a way that pulls that information from your CMO. Precisely, yes. So you can think of GPT three as like an a really smart but slightly over eager intern, it may give you a somewhat, it's going to tell you an answer, even if it doesn't know the right answer. So you always have to double check, right? It's not it's not a wizard, but it's really it is very smart. And it's going to get you 80% of the way there. Yeah, but it's it's going to continue to learn, it's going to continue to refine and hone and become a little bit more and more valuable, I guess, precisely. Continue. That's number one. And that's future stuff. Exactly. So that's on the horizon. In fact, we're prototyping with that technology. Now, it's already not available, but possible, and so probably commercially available later this year. There's also some really interesting things you can do taking, you know, NLP natural language processing a step further for the technician.

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Similar idea so I'm this is actually an agenda today. I'm a technician eye opener, corrective work order. Again, let's take this idea of machine and machine as smoking. Technicians are typically asking two questions when they step up to a reactive maintenance issue. The first one being what's even what's occurred on this asset recently, that's a pretty easy question to answer. You just show a history right there. It's right. The second question is harder to answer, which is has this problem happened before? And so how do I solve it? Hola. Hola. Hola. Okay, so yeah, I hate to be the speed bump in this

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parking lot of progress here. But the reality is, you're just saying, Okay, we've got the history. And it's just there. It's sort of Tabular. It's like,

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exactly, I got it right there. But you're saying, hey, I want to know, more in depth. And I'm able to sort of go out historically and then be able to pull that continuum Precisely. Precisely. Yes. Thanks for the additional context, right. So in this, this question is harder to answer because it has you have to understand so machine is smoking, how do I understand as a computer if that, if that problem has happened before, just there's some work you can do to understand what keywords in the work order are unique, right, so machine, probably not that unique is probably definitely not that unique, but smoking probably unique. So you can run an analysis on the background to identify, Okay, smoking unique keyword. And then related words to that smoke, smoke, smoking, Smokey, then you look in the CMMS, and see what other work orders talk about a problem like this, and we bring it to the surface, again, inside of the work order themselves. Because right now, the average technician spends anywhere from 15 to 30 minutes looking for information that when they're up against a problem that they don't know how to solve. So they'll either call around, go back to the CMMS, poke through work orders, or they'll just troubleshoot from scratch. So if you have, you know, a team of 20 technicians, and you have a, say, a half a dozen downtime events per day, and each of those times 20 minutes has been burned looking information. That's a lot of French time that you're not getting from the team, and it's frustrating for them. So you can leverage technology like NLP to do to analyze the keywords in the reactive English work order, and then pull forward any of the work that that's related on based on keywords of the problem. So we're doing that in Gambit today, actually, that's now commercially available. So that's another example.

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How do you with that example with that use case, shall we say, by the way, I interviewed the the originator or the guy that came up with use case. Just FYI. Oh, really? Yeah. Early 60s, he was the use case guy he didn't understand. He says like, it's just a user case. That's what he came about. And he said, I'm surprised that it even took it. Yeah. That was him. Anyway. Yeah. So

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with that capability, I understand. How do you deal with

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sort of that lexicon the difference? I might, I might use flaming, or, you know, there's some, sadly, there's some pencil whipping that can go on. And it's just like, I just gotta get this, I gotta get that information out there, bam, boom, and then it loses its value, because it's just pencil with how do you deal with a situation where maybe you I think you mentioned that but you're going to have to come up with multiple

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ways of defining smoking, so that you get that information so

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vapor, you get it, you understand what, how do I how do we come up with that? You

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that is just something that in our tech stack is done on the back end? I don't know if I have the I'm head of product. I'm not our head of engineering. And so I'm not going to have as a techie insightful answer maybe but let me let me say this isn't

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custom work. This is a technology that's available off the shelf right through, like IBM and Amazon like these, these companies sell the ability to do this type of analytical work on the back end. And so we leverage something like that in our tech stack. It's not something custom. It's cool stuff. Don't get me wrong. Do you have one more before we wrap it up one more future thing to hang our hat on.

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Um, it's not it's not a big deal. I, I really see, I guess, coming back to sort of the the vision of the ecosystem of emails and real we're in gamba, I really, really see the future heading to a technician that is completely enabled wherever they're at. So again, not being tethered to that desktop, or being tethered to a tablet, having the ability to throw in a headset. And so like, Take, for example, the the experience of having like an iPhone and an iWatch, right, and an iPad, there's this beautiful ecosystem, and no matter where you're at the experience is seamless between them. We're moving in that direction, where you know, right now, you still get some resistance from technicians or headsets, they they view them as like maybe kind of clunky or heavy or they don't want to wear them all day, they're becoming lighter, they're becoming more durable, they're becoming more useful. We're learning how to design, the proper user experience for augmented reality is just a reality. I gotta tell you, I had a conversation with somebody from Boeing, they're using augmented reality. And when building or manufacturing a play, there's a gazillion miles of cable just a gazillion miles, the old way would it be pull out the map, whatever, the single line or whatever you want to call it the map, and then look up and figure out where they need to work precise. They're using augmented reality, and they're just looking at it's like that was it precisely. Exactly. The time. I don't have to do this. It's, it's a beautiful. Exactly, exactly. So being able to bring up schematics and search them with your voice, even imagine wearables. So there's this there's this, again, nation technology where you can actually wear a wristband, and it's measuring your, how you're moving your hands. So you can even do things like swipe your thumb back and fourth, and it will navigate your experience on the headset. So yeah, that's where we're headed. I think from a frontline worker perspective. That's pretty cool stuff.

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Some people are gonna say, All right, yeah, that's just too much. I don't want them to understand where my hand is going. But I do. That's pretty doggone cool stuff. All right. How do they get ahold of you?

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Please email us at hello@genba.ai.

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Needs info.

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We're a friendly company.

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Hello, canva.ai. I like it. You were absolutely spectacular Island. Thank you so much. It was a pleasure to be here. It was, and I'm glad have a great morning at this conference is just absolutely a whirlwind. All right, listeners. If you're not, we're going to have Emory's contact information out on industrial talk. Yes, we are. You need to reach out. The future is bright, don't be afraid of it. You need to be able to sort of educate, collaborate. And of course, you need to innovate, to survive and move forward and create a business that is resilient and worn out. You Oh, great. All right, we're gonna wrap it up on the other side. Stay tuned, we will be right back.

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You're listening to the industrial talk, Podcast Network.

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