EMS@C-LEVEL

Revolutionizing Inspection with AI: Loopr.ai Founder & CEO Priyansha Bagaria on EMS@C-Level

Philip Spagnoli Stoten

Join us as we unveil how Priyansha Bagaria, founder of Loopr.ai, is steering the AI revolution in manufacturing. From her roots in a family-run electrical insulation business in India to pioneering AI solutions, Priyansha shares insightful anecdotes about tackling quality control hurdles in the aerospace and automotive sectors. Our conversation unravels how AI not only minimizes the cost of inspection and mitigates labor shortages, but also preserves the invaluable knowledge of retiring experts, ensuring the transition of expertise and adding consistency and insight.

Explore applications like IQ Inspect and IQ Verify that are reshaping manufacturing processes. Priyansha shines a light on these versatile tools, which transcend camera limitations to identify defects and verify assembly with precision. Hear how Loopr's commitment to continuous learning and customer alignment leads to solutions that resonate with real-world needs, accompanied by success stories that illustrate how initial projects can ripple into vast improvements across the board.

We also touch on the importance of the software ecosystem, touching on Loopr's partnership with Microsoft and other companies that participate in their own innovator ecosystem.

Finally we switch gear to celebrate the inspiring journey of an immigrant woman of color breaking barriers in a male-dominated landscape. Together, we reflect on Priyansha's narrative of resilience, community support, and the unwavering belief that powered her through her entrepreneurial journey. Her story is a testament to perseverance and innovation, offering lessons that echo the importance of staying true to one's vision, coupled with the excitement of what lies ahead.

Like every episode of EMS@C-Level, this one was sponsored by global inspection leader Koh Young (https://www.kohyoung.com).

You can see video versions of all of the EMS@C-Level pods on our YouTube playlist.

Philip Stoten:

from my house to yours. Welcome to ems at sea level. I'm particularly excited to have preantia bargaria from lupa with me today. Um, I've been kind of watching what's going on in the ai space and it's a particular area of interest in manufacturing, so really keen to talk to people that are doing something new and exciting in that space. So let's start, for our viewers and our audience, with a quick introduction to you and the business and kind of how you came to create Looper.

Priyansha Bagaria:

Yeah, thank you so much, philip, for having me today in your podcast and excited to share a little bit about my journey, my story. So I started Looper in 2021. I come from a family business background of manufacturing. Was the fourth-generation entrepreneur in my family business of manufacturing of electrical insulation, which was started in 1960s, so I have been born and brought up in that environment. I would say manufacturing and business is something which is in my blood. I mean, I've learned a lot from my family. You know, seeing my grandfather and my father being in manufacturing for a really, really long time and the business is still up and running and doing really, really well.

Priyansha Bagaria:

So I saw the problem of quality firsthand while I was in my dad's business and we were making this specific product where it required real-time monitoring and, as a human, the defect might happen today, but it might not happen for two days, and then you can't have someone. You can't expect someone to just stand there and keep looking at the product waiting for defect to happen and since it was a kind of a role, so the defect might go inside and it was really hard to find it later on. So you have to identify it literally when it's, you know when the process of manufacturing is going on, and that's where we we tried to look for solutions and I'm talking about 2011 and it was hardly anything that existed. And if you want a custom solution, it would have cost you a million dollars and my dad would be like you have no business sense, you know. You just go out of the factory like you don't know what you're talking about.

Priyansha Bagaria:

So that's that problem. Stayed with me and fast forward. You being in technology for a really long time, working with some of the largest CPG customers across India and Europe, I saw that problem again and again. You know just the size and the impact of the problem would differ based on the companies. And, yeah, fast forward in 2021,. Here I am, like I started the company and we are now close to four years since having the company and we've come a long way and truly trying to automate the process of inspection for manufacturing aerospace companies around the world.

Philip Stoten:

Yeah, and I think it's interesting. We started to see some AI use in inspection, particularly around the smt line and perhaps around box build uh after that. But actually to see it happening in mechanical parts, in finishes, in those kind of things, it's really interesting. Um, quick question you decided to call the company looper. A particular reason for for that?

Priyansha Bagaria:

Yeah, so Looper comes from you know the idea behind it is a continuous learning.

Philip Stoten:

So with.

Priyansha Bagaria:

AI. Every you know. Wherever you apply AI, especially as a technology in computer vision, you need to make sure that you keep retraining. You do model governance, so it is a continuous improvement, continuous learning you know that you need to take. You cannot have something that you built today and then you know you don't need to worry about it like it needs continuous learning, and that is you know. That is what looper stands for.

Philip Stoten:

It's like bringing you know you're making the solution better and better for your customers and you're bringing in more and more value uh over time to our customers, yeah yeah, so it's about the system learning, but it's about the company learning and the industry and improving the whole process. What's really interesting is you've already attracted some really high profile companies, both in the aerospace area, but also in automotive and also in some general manufacturing around chemicals and different things. Tell me a bit about the kind of problems you were solving for those customers and what that solution has looked like and done for them.

Priyansha Bagaria:

Yeah. So three reasons which I would say has played a very, very important factor in technology adoption. Something especially for technology like AI in today's world is first, is cost of quality is very high. You know we all saw that one issue you know with the largest aerospace company. It impacted them in a really really long way. So cost of quality is really really high and especially in today's environment where you know inflation is really high, everything is so expensive. You know, hiring a laborer is so, so, so expensive as it ever used to.

Priyansha Bagaria:

Especially with so many manufacturing jobs moving back to US, you need more and more people to really work in the factory, and then finding these people is hard. Finding a good welder is so, so, so hard in today's time. So the cost of quality was number one. That you know companies, you know they don't want any more recall. They want to really reduce the cost of inspection that they have to do.

Priyansha Bagaria:

The second one is you know your labor is retiring. I mean you have people who have worked with you for 30, 40 years and they're moving towards their retirement age. 25% of the workforce that exists today they are above the age of 50. So you can imagine next few years they're all going to retire. And how do you fill the gap of that 25%? You know like right now hiring even another additional resource in the company is so hard and you're talking about a big knowledge gap that's going to exist once all of these people leave, because generally in manufacturing what we've seen is a lot of knowledge. It exists in your head, it's based on your experience and it's not easy to transfer, because you know what I mean. You cannot have another John who's John has been doing this work for 30 years and now you cannot find another John who's going to be pleased.

Priyansha Bagaria:

The same experience, the same experience and the same level of delivery. Right, you cannot have that. So that's been another big, big challenge. So I think, keeping in mind all of these big reasons, we're seeing a lot of initiative across technology adoption, especially on the quality side, and yeah, I mean we're trying to solve like, for, in such a short period of time with some of our customers. Already we've got such positive feedback that with one of the customers they were able to reduce 5% of the defect escape, which they didn't even know existed. So they were really missing on that. You know that important kind of data.

Priyansha Bagaria:

With another customer. They feel that the system, you know, with two months of experiences, is doing much better results than their manual inspection today. So you know, these kind of insights really really kind of tells you how good our technology is and it's going to improve more and more with our customers.

Philip Stoten:

Yeah, I think it's really interesting. I think people sometimes think of the cost of quality as that person that does the inspection, or the cost of reworking something that they found. But it's so much more than that. You know, you look at some of the very large brands and the cost they've had recently from recalls, from brand damage. There's a whole lot of things related to that and key to having that quality is consistency. And, as you mentioned, john, even if John stays, john's only working on one shift. So if you work a two shift system, you often have this inconsistency where someone's picking up on one particular thing, someone's picking up on others, and if you can somehow synthesize that knowledge using machine learning, ai, you can get so much more from it. Talk a bit about how you gather those images, because you're installing cameras but you're not a hardware company, so you're kind of agnostic on that. Give me a flavor for what an installation might look like.

Priyansha Bagaria:

Yeah, one of what I always believe in that you know, when we go and buy a software or a new technology, we always, you know, start small and then expand from there it all talks of, I mean seeing is believing right, Like once you have something running, then it's a no-brainer, you would like to expand. So it's always about starting small. So for us, that is one strategy that has worked really well with our customers, and now we are to a point where we are expanding with every customer that we started working with. So how we go about it is, at this point of time, our solution is completely hardware agnostic. It doesn't matter to us if you need a handheld camera or your solution needs a tablet like an iPad or a Surface, or it's something which needs a network camera or endoscopic camera.

Priyansha Bagaria:

We have worked across a wide variety of customers where some of them are making extremely big parts to some of them doing an inspection using a microscope. And what we believe in we want to provide a solution that can easily adapt to really affordable hardware and where the software should be the key, not the other way around. And how we go about it that if a customer already has an existing camera, we utilize that to start collecting the data and build a model on top of that. Or the other approach we take is that we basically help the customer find the camera that works best for them and then go about collecting data installing the camera, collecting the data from that camera, training the model and then deploying it using our application.

Priyansha Bagaria:

We have two applications IQ Inspect, which is focused on identifying defects in manufactured parts. All your defects around welds I mean bent tips or welding defects, or discolored or your, you know, painting defects All of those are something that can be solved using IQ Inspect. And then IQ Verify is really focusing on assembly verification. So we're already working across trucking and aerospace companies where we are helping them in verifying critical parts that goes inside, you know, goes inside the trucks and planes.

Philip Stoten:

Yeah, and I think it's fascinating when you're camera agnostic or almost image agnostic, you can take an image of a large set of components laid up ready to assemble and you can verify the quality and produce traceability on that. But also you can use an endoscopic camera to get inside a really small space and use those images in a different way. I think that opens up opportunities that are way beyond what human inspection can do, and I guess that's important to your customers, your customers. When you visit a customer, I guess the walk around the factory, the you looking at the process, must be really important to understand where where you can add value yeah, and and again.

Priyansha Bagaria:

What we believe in is that you should always try to touch on the problems which is actually a real problem for you, rather than something you know which is, like you know, good to solve, right like you're looking for something which is a must to solve, which is like a big right now, so that now I think, after go, you know, visiting so many customers around the world, from being inside a mind to like going on a plane, to, like you know, really seeing how a truck is being made, like I've. I think I've seen a lot of manufacturing and it fascinates me every time I'm on a factory floor. It looks like, it feels like, you know, I'm, like I'm a kid in a candy store and there's so much to learn, right, like it's just so fascinating and exciting to see the process that they're doing. And what we like to do always is understand the problem statements, and every time I go, I'm amazed to see the number of problems that a customer has, and it's not just one, you know, you think it's one, but it's like a list of problems that they'll come up with that, okay, we need solution here, or the multiple places where we can help, and then we help them identify the one which has maximum business value Right, and they're really focusing on that.

Priyansha Bagaria:

And what we always do at our end is we don't waste our customers' time, neither our time. So we only focus on and prioritize on the use cases which has that impact and that opportunity to scale. So with our customer we spend time and we collect some sample data very quickly and do some tests at our end before we even come into customers. So these are some of the additional efforts that we do, because if it's something which cannot be solved, we really don't even want to start on that.

Priyansha Bagaria:

And we would like to be honest and transparent with our customer.

Priyansha Bagaria:

Like I remember very recently, there's this one company who called us and they needed our help to do some inspection of blades and to really bring down the time of inspection.

Priyansha Bagaria:

And when I visited their factory, it was very clear to me that the problem is not with inspection, that the problem is how they're gathering the data today, reading the work order, getting some information from SAP and Pitch for Chase Auto and a lot of different data sources. So they needed something which can help, which can really solve the problem of bringing together all the data sources rather than inspection. And I was very clear to them that, hey, if you want to see impact, you have to solve that problem first. Then they come to us. So it's just about you know, building relation, being very transparent and actually want to help your customer rather than just trying to do some business for the sake of business, because I always try to keep myself in their shoes and be like how would I have felt? Like you know, I mean what I would need to get out of this engagement, and that is really what I mean we do with all of our customers.

Philip Stoten:

Yeah, priyanshwar, it's fascinating when you talk about being a kid in a candy store. I'm the same when I visit a factory and my favorite thing is to walk the factory floor with the person that's responsible for ops and you know they'll tell you stuff or the operators will mention stuff as you pass by and you just learn so much from that. It's really valuable and I like this idea of proof of concept that has a clear return on investment. That has to be your first port of call. Is it typical that when you've done that and you've successfully shown that, then you can expand into other inspections, other processes within the factory?

Priyansha Bagaria:

Yeah. So with all of our customers today, like the first set of customers where we did the first pilots, we are expanding with each one of them. So they've all seen the value that we could bring. With the first pilot, even with one of our customers, there were some network issues and we went above and beyond and worked around with the challenges and still got them a solution that can start showing them value. So with each one of them, either they're expanding, they need multiple licenses of the same solution or you're also looking at what are the other problems that we can solve using our system.

Priyansha Bagaria:

So it's been both ways. But I think we've been blessed and we're lucky that we've been able to show value quickly to our customers and be expanding with every account.

Philip Stoten:

Yeah, and once you do that, once you start to expand and you're getting regular data, is that data something that they can then synthesize and look at? Hey, how can we actually improve process rather than just catch the errors?

Priyansha Bagaria:

Yeah, yeah, yeah, and the way we think about it, like this can be an additional data source to their existing MES systems or, like you know, all of them have like a big QMS MES systems and this can be an additional data source that can be incorporated as part of your system. So you don't need to worry about something which is like a standalone application in long term, but this can be easily embedded to your existing system that you have in your factory floor, because then it just becomes part of just one application for you. It makes it so much easier the kind of analysis that we've been able to do for customers with such limited data set. It's mind-blowing. Like I said, that 5%. It also specified what part were the biggest issues, what time of the day these issues happened. All of those information we were also able to gather, along with, you know, the percentage of defects. So these are super helpful, right for a supervisor or for a plant manager.

Philip Stoten:

At the end of the day, if he wants to increase his yield or he wants to have, like you know, better production rates, he needs to have an understanding of where the issues are as of today yeah, no, that's really interesting and I think when you think of actually, rather than just making sure escapes don't occur, you're actually able to improve process and able to improve performance. That's really important. And you mentioned being part of kind of a software ecosystem. You're part of the Microsoft ecosystem. How important is that in being able to connect to everything else?

Priyansha Bagaria:

Yeah, and Microsoft has been a really, really, you know, a great partner for Looper so far and we have worked on a couple of projects together where we use a lot of Microsoft services in our system and in our application and it really helps because, again, you don't need to reinvent the wheel when some of these technologies exist and they've done a brilliant job with the tools that they have created which we can easily use inside our application. And we are working closely on accounts across manufacturing and aerospace companies. In fact, our solution is live right now at Microsoft's demo center, where there's a handful of partners whose solutions are there and we had the privilege to have our solutions, which is being seen by, uh, by, like you know, two to three, fortune thousand companies every day.

Philip Stoten:

So that's kind of the kind of community we're talking about with our solution yeah, that's really important, it's really valuable and and I think it just gives everybody that confidence and understanding that the looper software plays nice with all the other softwares. What I think is really interesting is the speed at which the application of AI and machine learning is going, particularly with the combination of vision as well. And when I look back almost a decade ago, we were equally excited about industry 4.0. We didn't really get to have that digital dividend that we expected. It didn't move at the speed that we hoped and I think maybe it was overwhelming. But I wonder if some of the ingredient technologies were not there, and maybe AI is one of those Do you think AI is something that will push us through that barrier of that fourth industrial revolution?

Priyansha Bagaria:

Yeah, so I would say that vision has been around now for close to eight, nine years. It's not a very new technology I mean AI and vision has been around but the advancements that this technology has, now it's like it's. It has come to a point where it can actually be built in a product like it was initially in. You know it was in a prototype stage where it was just something you know, where people were trying and playing with it and trying to see how they can use it. But now it has got to a point where the technology has matured over time and now it's ready to really bring in the value that you know the companies were perceiving, or they're trying to perceive, like 10 years back. So it is, it is much more mature now.

Priyansha Bagaria:

Also, the reason, like I mean, we all know manufacturing and aerospace are slow, so slow in the technology. It's. It's like, you know, the mind, it's the, the change in mindset. It takes time. You know it's not going to happen overnight. It's it takes time and but with all the recent problems that started from post-covid and from covid to post-covid, these are real problems and we know that when there is, you know you don't have an option. You need to. You know you, you need to evolve and you need to uh change your process, and that's I think it's a perfect time now, where the market really needs you know, has these problems that needs a solution, and then the technology is also mature enough that it can solve those problems. So it's a perfect time, keeping in mind those two important topics.

Philip Stoten:

Yeah, no, I absolutely agree. I think it's. I think the timing is. The timing is impeccable. You have the technology there that you can do it, but I think what's really important is you have that really interesting combination of understanding AI and what can be done, but also really understanding manufacturing and what needs to be done, and it's the combination of those that's important. I just wanted to switch gear slightly just for a couple of minutes to explore your journey Woman, immigrant, woman of color. Has that made this whole process more challenging, or do you think your understanding and your ability has just shone through and you've been able to push through? Or how do you see those things? I think you know at the moment we're in a period of political turmoil in the world and and some of these issues have become much bigger than they. Perhaps they, they perhaps should be, but I'm just curious whether that's made your journey more challenging.

Priyansha Bagaria:

Yeah, it's funny. When I got into this, you know, in this starting a company and entrepreneurship, I remember this saying that exists, pay Yale males and I. You know, there's a very common thing that if you have, if you are, these three, it's just so much easier to raise funds, it's so much easier to start a company. And and I, you know, I wouldn't believe in all these things, because for me it's like, um, I mean, looking at my journey, right like from where I come from my dad, he never differentiated between me and my brother, so for me it always felt like, you know, though, that it's, it's gonna be same opportunities for everybody. And I came, I literally I mean I came from that mindset and for me it was a, it was a awakening call that yes, I mean I would, I will be very honest that it has not been an easy journey.

Priyansha Bagaria:

Of course there's been a share of struggles, if it be it with fundraising, be it with, you know, finding customers, especially like even now, when I go to a manufacturing company, in a room I might be the only one with 10 other male in that room and it's interesting, right, it was hard in the beginning but then it gets better and better over time. But I would say that it's been a great learning and, having said that it's been harder, I have come across some amazing people who have supported me and been a part of my journey, being my first investor who, you know, who came out of nowhere and like really holding my hand and be like hey, I'm here to support you and I would like to make this company big and work with me.

Priyansha Bagaria:

So I would say it's even whatever we've been able to achieve in last, you know, last three to four years. There's been a lot of people who have really added a lot of value. And you know it takes it takes an army to really make it. Yeah, of course, it's never one person thing, so I would never, ever. You know, my team has been a big support. I have some amazing people who believed on my you know my ideas and really make trying to make that idea tune to real vision. So it's been uh like, um, I would say, you know, a lot of support and a lot of help, including, you know, my family. But yeah, I mean so they've been a share of both.

Priyansha Bagaria:

I would say, you know it's been hard sometimes like super hard and you'll be like why are you doing this? But then the second moment you realize that this is the best thing that you know you could do, especially when you see the value that you're bringing in.

Philip Stoten:

Yeah, no, absolutely. And it sounds like you know some people that have inspired you on the way, starting with your father, who had that belief that you should all be treated the same, which is a great starting point, that you should all be treated the same, which is a great starting point, and it feels like there are more young, dynamic women in the industry now than we've ever seen before and maybe that pale, male, stale generation is kind of working its way through the industry. And you know, I think the industry is the better for it and more exciting for it, and I think if we can focus on talent and ideas and, you know, kind of drive and passion, then we'll get to where we want to get to. Priyansha, such a pleasure to chat to you. Such a pleasure to learn about Lupa. We'll speak again soon, but in the meantime, thanks so much.

Priyansha Bagaria:

Thank you so much, Philip. It was a pleasure to be here and talk about my journey. Thank you so much.