00:00As global manufacturing faces pressure to boost efficiency and remain competitive in an AI-driven
00:06world, companies are turning to new technologies to deliver results. One of the leaders at the
00:11forefront of the current industrial transformation is Sar Jaskovic. He is the co-founder and CEO
00:16of Augury. Sar, thanks a lot for being here today. Good to have you.
00:19Thanks for having me.
00:21So for viewers who might be new to your company, a bit unfamiliar with what Augury is all about,
00:26tell us how you define the company and what problem are you solving for in manufacturing?
00:32So at Augury, we work with the largest manufacturing companies in the world to make their production
00:37lines more reliable, more productive, more sustainable. And we basically help them bring
00:43all the goodness, all the innovation you see in the AI world today into the production lines.
00:50So how do I increase the uptime? How do I make sure my machines run correctly?
00:54And then how do I optimize for quality and yield, et cetera?
01:00How do your AI sensors work on an actual factory floor?
01:04So we have two parts to the business today. We have what we call machine health, where we
01:09physically listen to the machines. We have sensors that we install on the production line.
01:14We pick up the vibration, the magnetic emissions, the temperatures of the machines.
01:19And based on the noise, we can tell you what's wrong with them before any catastrophe happens.
01:25So today we've monitored over 600 million hours of machines in the wild.
01:31And we have the largest malfunction dictionary, basically.
01:34So if you have a pump or a compressor in your factory, we don't need to build a model for your
01:40specific machine because we've seen 20,000 pumps before. We know exactly what the different faults
01:45look like. And then on the other side, we have process health, where we build a simulator for your
01:53production systems. And we can predict if you change the temperature of the oven, you can increase
01:59the quality, you can reduce the waste, you can reduce the environmental impact, energy, carbon
02:04emissions, et cetera.
02:06You mentioned analyzing more than 600 million machine hours. Your tech has also saved companies
02:12more than a billion dollars. Can you share with us any kind of favorite case studies or use cases
02:18where you've been able to find success here?
02:21Yeah. So one of our larger customers is one of the, let's call it the top two food and beverage
02:27companies. Last year, we helped them avoid over 4,000 hours of downtime, which equal 10 million
02:34pounds of the beautiful snacks that we all love to consume. And for them, you know, that ties
02:41directly to top line revenues. So they can attribute their work they're doing with Audrey, both to
02:46their top line, bottom line, as well as the talent upscaling, which we'll talk, I'm sure, a lot about
02:52today. Yeah, I know you work with about 10% of the Fortune 500. What's driving adoption? And is a lot
02:58of it, are you in sort of word of mouth territory with regards to, to getting more people to work
03:05with?
03:06Well, we talked to a lot of senior executives of these manufacturing companies, and I think they
03:11all, they're all aware that whatever tools they used to have in their toolbox are no longer
03:16available, meaning they can't just offer to China anymore, because of geopolitical pressure. They, you
03:23know, they have a huge talent shortage, and it's called a silver tsunami, there's a generational gap, all
03:30the experts are going to retire, and the next generation is not coming in. And then they also have the a
03:36sustainability cloud hovering above their business, right, both from a regulation
03:41perspective, from a consumer demand. And they know that they have to fundamentally re-imagine how
03:46manufacturing is being done, right? So if you're going to onshore kind of bring manufacturing back
03:51to the US, you can't imagine building a factory today, the same way you used to build it in the 80s
03:58or 90s, right? So how do you re-imagine the use of using the use of modern technology, like like
04:05connected sensors, the whole IoT in terms of things, bringing AI and sophisticated automation to the
04:11production line as well? Help us better understand what those main pain points are for manufacturing
04:18the production line. I'd imagine costs, labor shortages. Talk to me about the ways that AI is
04:23helping manufacturers tackle a lot of those pain points. So manufacturing today, if you look at it,
04:31hasn't really changed in the past 30, 40 years. So the frameworks from the Toyota production system,
04:37lean manufacturing came about in the 80s, roughly, there was a huge wave of automation in the 90s. But
04:44since then, not a lot has changed. And today, we call this shadow factories, we had a large cement
04:50manufacturer, where we help them improve their efficiency and productivity by 2%. They have 100 factories,
05:00that means that they can avoid building two new factories, just because their 100 factories are
05:07working much more efficiently, right? So we have this captured efficiency, which we call kind of shadow
05:13manufacturing. And today, we believe it's to the tune of two to 5% of every manufacturer
05:20can just kind of unleash this into the wild, just by working more, more smarter, basically using new
05:27technologies. How do you see AI boosting resilience and overall supply chain, especially in a high tariff
05:36policy environment, especially one where tariff policy can change seemingly by the day?
05:43Yeah, I think that the goal for tariffs, one of the stated goals of tariffs was to bring
05:48manufacturing back to the US. I think the result, at least initially, is just causing more confusion
05:55and paralysis. So if you had a big project coming up, maybe you're not as quick to release the CapEx
06:03funds in this uncertain environment. If building a factory will take three to five years, depending
06:09on the industry, who knows what administration will look like in three to five years? And what would the
06:15regulations be back then? So and at the same time, the cost of steel and aluminum to build the factory,
06:22the cost of all the production lines, the production machines, which all come from Europe or Japan or Asia,
06:29has gone up by 10-20%, right? So the cost of building a factory is 10 to 20% more expensive today.
06:36And there's a risk analysis, right? Is it worth it for me to actually kind of create more production
06:44lines? So at the same time, I have all this existing production lines, how do I make them more efficient?
06:49How do I drive productivity there? And that is through the use of modern tools and frameworks
06:55and technologies like ours.
06:58And how do you see the role of human workers evolving as AI continues to expand? And how do you
07:05feel Augury maybe fits into that future?
07:07Yeah, so I think when you talk, there's a large conversation and justifying so about white
07:15white-collar work disappearing due to generative AI, etc. In our world, the blue-collar workers,
07:22the big shift already happened in the 90s, right? The introductions of automation, of robotics,
07:28and today there is a huge shortage of workers. Our customers are not able to hire fast enough,
07:33and that's what's limiting their production capacity today. So they're not looking to replace people,
07:40they can barely keep up with the bleeding of knowledge because, as I mentioned earlier,
07:46all the experts are going to retire in the next five to seven years. So there's an expected 3 million
07:51people that are going to leave the workforce in the next few years, and the next generation is just
07:56not coming into this industry.
08:02Asar Yaskovic is the co-founder and CEO of Augury. Thanks a lot for taking the time to come by
08:06and help us better understand what it is you're all about, and congrats on all the success, Sar.
08:11Thanks a lot for being here.
08:12Thank you, my pleasure. Thanks for having me.
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