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Ep 6. AI for Zero Waste Fabric, Sustainability and Traceability in Textile Factories with Gilberto Loureiro
356 Plays9 months ago
On this episode of the 'No Ordinary Cloth' podcast, we welcome Gilberto Loureiro, the co-founder and CEO of Smartex, an innovative startup leveraging AI and machine learning to transform the textile industry and modernise it's factories.
Gilberto draws upon his life experiences, growing up in a family where everyone worked in the textile business and witnessing the substantial wastage and outdated practices in factories. This became his motivation to set up Smartex - a company building an eco-system of solutions to bring textile factories into the 21st century, eliminate waste, and enhance traceability and sustainability. They are truly revolutionising and shaping the future of textile factories.
He talks about the challenges faced by startups and shares lots of valuable resources and advice for others who might be building a startup. He highlights the importance of mentors, being humble and enjoying the work that you do to be successful.
Furthermore, Gilberto elaborates on the sector's future, identifying technology, shorter orders, increased automation, and reduced human dependence as primary factors leading the charge. Our discussion unpacks the enormous potential AI and machine learning hold for not just improving efficiencies but also for combating the significant sustainability issues within the textile industry.
Connect with Mili Tharakan
Insta: @noordinarycloth
Cover art: Photo by Siora, Photography on Unsplash
Music: Inspired Ambient, Orchestraman
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Transcript
Podcast Introduction
00:00:05
Speaker
Welcome back to another episode of the No Ordinary Cloud podcast where we bring you insights and experience from the leaders in the textile and fashion landscape who are transforming the very way we think about, make and use fabrics.
Meet Gilberto Lurero and SmartX
00:00:20
Speaker
Hi, my name is Millie Tharkin and I'm thrilled to bring you Gilberto Lurero on the show today. Gilberto is the co-founder and CEO of SmartX
00:00:30
Speaker
a very young and upcoming startup that is using AI and machine learning to minimize waste and boost sustainability in the textile factories.
Challenges in Textile Factories
00:00:40
Speaker
When we think about fashion, we have such a glamorous picture in our mind of runways and designers and trendsetters
00:00:47
Speaker
But we rarely get a glimpse at the other end of the spectrum, the factory floors where these fabrics are first made. And Gilberto really opens up that world for us and today he shows us how many of these factories are in so many ways stuck in the past and hasn't modernized as many of the other industries have.
Growth and Achievements of SmartX
00:01:08
Speaker
He discusses the three pain points he has identified in the factories, especially the circular knitting factories, and three painkillers, as he calls them, that he's developed to solve these problems. He's also an incredibly inspiring startup founder who has grown his company quickly and in just under five years really built out a team of 150 and is growing fast. He has a lot of valuable insights for anyone who has a startup, whether it's in textiles
Role of Mentorship
00:01:36
Speaker
or not.
00:01:36
Speaker
Gilberto has raised $40 million in investment, which is extremely impressive because I know how difficult it is to get investors in the fashion and textile sector. He talks about the importance of learning from others and leaning into mentors, particularly he discusses his investor, Tony Fadell, who developed the iPod and iPhone. You might know him as the father of the iPod, if you're old enough to remember the iPod.
00:02:00
Speaker
and he has many others who guide him in this journey Gilberto is passionate and he's on a mission to transform the textile factories and he's unstoppable so let's dive in and learn more
00:02:12
Speaker
Hello, hello, and welcome, Gilberto. It is absolutely wonderful to have you on the No Ordinary Ploth podcast. I am looking forward to learning so much from you today. I'm particularly excited about hearing about Smart X and how you're using AI and machine learning in very practical ways.
Gilberto's Background and Motivations
00:02:31
Speaker
But the fact is, if you say AI to anyone today, they think chat GBT. But you're using AI in textile factories to reduce waste and increase transparency. And the impact you claim to have is quite incredible. I mean, in the short time that you've been running as a business, you say that your technology has saved over 961,000 kilos of fabric. That is mind-blowing. That is fascinating.
00:02:57
Speaker
So I can't wait to dive in and find out more about your journey to creating solutions for the textile factories of the future. Are we ready Govardha? Thank you for the invitation and we need more content like this because indeed the textile industry is
00:03:12
Speaker
probably the largest industry in the world that still is untouched by internet in many ways, especially in textile factories. So let's dive in. Let's go. Great. So before we hear all about your work, I would love to just get to know you a bit, Gilberto. I know our listeners want to hear where you're from and where you grew up as a young boy. Tell us.
00:03:32
Speaker
Sure, so I grew up in the north of Portugal in a textile hub. It is actually the second largest textile hub in Europe after North Turkey. Because of Inditex, you know, Zara, Massimo duty, all of these brands in north of Spain, they still have lots of factories in the north of Portugal. So I was born and raised in a very, very small village in the middle of nowhere. And all my family works in textiles since then.
00:03:57
Speaker
They are humble people, textile workers from textile factories. And then my parents, my cousins, my brother, like everybody works in textiles today. And that's part of the story how I stumbled in many of these textile problems in factories.
00:04:14
Speaker
because I actually used to spend a lot of my weekends and summers working in textile factories to get extra cash in school.
Educational Path and Career Choices
00:04:21
Speaker
So that was the moment that I was like, oh wow, this is really manual, right? It's like all the processes are manual. You have pen and paper everywhere next to the machines. You have people inspecting fabrics day and night, like human inspection for quality control.
00:04:36
Speaker
We have tons of waste. So that was my moment of like, hmm, this is a lot of room for improvement here. And because I was eventually a textile inspection worker, I decided to run away and I promised to never get back to textile factories because it's really a horrible job. So that was the motivation to leave to college. Right. Okay. And what did you want to go and study in college?
00:05:00
Speaker
So I was very good at math and physics. I was a bit indecisive, but someone taught me my first rule of life, which is always make the choice that will open you more choices later. Was a finance mentor I had. He was teaching me about real options. So he was like, always choose the door that opens more doors.
00:05:19
Speaker
And physics is this course that was like, if you want to go to engineering later, you can, or to mathematicians, or to finance. So physics was like this mega course that you can choose more or less what you want to do later. So that was my choice. Brilliant. Going back to your family, I understand you have a brother. Yeah. Yeah. And how did you guys spend your summers?
00:05:42
Speaker
So we used to work a lot again because he was also working in textile factories. So very humble people, humble beginnings. We used to be very close and living in a very small house in the village. And in the village, everybody knows everybody, you know, like this very little
00:06:00
Speaker
village with a little church in the middle. So that has been our lifestyle. Although when I went to college, I was the first person in our family to go to college. I went to the city, which is in the south, more south of Portugal. And then eventually life started going on. I moved to China. I moved to the US. I moved to Turkey. So I lived in many countries. And now once in a while, I still go to the village to visit them. But I've been living in many other places now.
00:06:28
Speaker
Incredible. And your family still has the textile business. Yes. Yes. They still have a small textile warehouse.
00:06:35
Speaker
So you sort of rebelled against all of that, went away and then sort of almost landed back in the same place. I'm sure your dad's very proud of you. Yes. I promised to never get back to textile factories.
Industry Connectivity Issues
00:06:46
Speaker
I was really annoyed by the whole thing, you know, like lots of family businesses, lots of discussions. After the fashion world, you have like 10 different stages of the textile industry. You have like the garments, the dyeing, the finishing, printing, embroidery.
00:07:03
Speaker
then you have weaving, knitting, right? It goes deeper to spinning yarn and then you have fibers. All of these guys, they live in a different galaxy than the fashion brands. Like these worlds, they are disconnected. And this world here, like these textile factories world, I was really shocked with the processes, the inefficiencies, the people, like nobody used like smartphones, like nobody used like
00:07:28
Speaker
There was pen and paper everywhere. So it's funny because now I see lots of companies, especially other startups, talking about this AI, AI, AI, which is amazing and blockchain and traceability. But then you go to a textile factory and everything is in pen and paper. So good luck with the blockchain. That's not the problem here. The problem is we don't even have data from factories.
00:07:49
Speaker
That's the two galaxies that I have been describing. I saw that in the first person. So I wanted to run away. But then, yes, in college, when I was studying physics, and then later on, finance, all the things came back. And I was like, well, this machine learning thing is an inflection point in humanity. This was 2016, 2017. The first machine learning models were public, like Google and Facebook, PyTorch, these type of models.
00:08:15
Speaker
And that was the trigger that we were like, maybe we can do something here to help the textile factories. So that was our first spark. Yeah. Yeah. Actually I was reading through your modern textile factory report and we'll get more into that further into the, into the discussion, but it's just, it was such an eye-opener to see how the textile factories are stuck in another age altogether. And so, I mean, I'm really hoping we can shed some light onto that today. Yeah, definitely. We have a lot of talk on
SmartX's Technological Solutions
00:08:44
Speaker
that front.
00:08:45
Speaker
I am, I'm extremely passionate about textiles. I'm a textile maker. And I also believe in the connections that we have with textiles as a material, whether it's a garment or a piece of cloth. So I'd like to get a little personal now, Gilberto. Is there any fabric or textiles that you hold some very personal connections with some intimate memories or stories that you have?
00:09:08
Speaker
I have a lot of memories in textiles, but more related with the machines and the processes. Interesting, yeah. More than the materials itself. I have lots of memories of the first knitting needles that I've seen and touched. So a knitting machine has thousands of needles. And those needles, they have a little latch, a little tongue that opens and closes like thousands of times per second or something like that to catch the yarn and knit the yarn together with the neighbor yarn.
00:09:37
Speaker
to build the knitting structure. Those memories I still have from teenage wood and I traveled there a few times even today of the first time I've seen the engineering behind the knitting process and the weaving process. It's really fascinating to see all of those yarns and needles and air jets and things happening. So in terms of mechanical engineering, actually the industry is very evolved and there are amazing machinery builders, especially in Germany, in Belgium, in Italy, also in India and Japan.
00:10:05
Speaker
There are amazing engineering companies for textile building.
00:10:09
Speaker
When I talk about these two galaxies and the industry is not being connected, it doesn't have to do with the mechanical engineering of it. It has to do with the software part of it. I used to tell my investors that this will be the last industry to be fully automated compared with all the others. Why? Because it's so difficult to have robots or machines manipulating textiles. It's such a complex product.
00:10:35
Speaker
is flexible, is breathable, is subjective. A defect for you might not be a defect for me. What you find beautiful, I might find not so beautiful. There are so many variables to make a garment that is so difficult to automate it and especially to compete with the prices because garments manage to be cheap.
00:10:55
Speaker
Like, since the 90s, they keep more or less in the same levels. And all the other industries, they somehow managed to increase their prices. So all of these makes Textile super challenged to be fully automated. So that's also why we came up with some initiatives there.
00:11:13
Speaker
I've never heard anyone speak so passionately and beautifully about the engineering behind textiles. And it is so true. We forget how complex the processes are for making a piece of fabric, you know, just a shirt or we just think, oh, it's a piece of cloth. But the amount of advancement in engineering is mind blowing. Thank you for just bringing that to our attention.
00:11:34
Speaker
You mentioned a mentor earlier. Is there someone that you could share with us who's been a role model for you, a mentor that has guided your path? Sure. I try to be absorbing knowledge from everyone. I try to find coaches everywhere I go. I have lots of mentors. I can point out one of my investors, Mr. Tony Fadal, the inventor of the iPod and iPhone and Google Nest.
00:12:02
Speaker
He has been someone really important for me in managing the business and helping me managing and growing the business. But I find mentors everywhere. I have textile mentors, I have business mentors, even like spiritual meditation type of things. I try to find and drink knowledge from everyone around me. I have strong opinions about people that are coachable, like absorb knowledge from anyone.
00:12:27
Speaker
and humble, right? And humble to be asking questions and not play as the smartest guy in the room. And work hard, work an extra mile, like those guys fast answering emails, work an extra mile on the weekends and nights. If you have these three things, I really believe that you can do in three months what a normal person does in one year. When you are 30 years old, you can have as much experience as a 50 years old average person. I really believe that. And that's something that I try to put in people around me as well.
00:12:55
Speaker
And how do you sort of gather all these mentors? Because I can see that's a really important part of who you are and what you've built. It is, especially being a first-time founder, right? And I've never run a business of 150 people, right? Like I'm running now. So it's better for me to be surrounded by people that have been doing this. Thankfully, we have a huge ESG impact, a huge sustainability impact. We can go there in a minute. And also a social impact as well in the industry.
00:13:22
Speaker
We are improving a lot of lives on the contrary of some people say, oh, you guys are replacing jobs. No, no, no, no. That's not exactly like that. So this type of mission, which is such an inspiring mission.
00:13:34
Speaker
Many times attracts these type of investors and mentors and coaches. Sometimes it's not even the monetary part or the stock of the company. Of course, we compensate some of them. We give them stock of the company. We try to bring them closer to our company for them to help us. We are very generous with stock in general. I think it is a mix of all of these things, plus having fun with them, that we can attract these type of guys. And I'm always asking for interest. So I don't ping people randomly on LinkedIn. Sometimes I do, but usually is asking for interest to others.
00:14:04
Speaker
That's a great tip. Thank you. Okay. Now we're going to jump in and talk about your company or your baby, I would say SmartX, right? You are the founder and CEO of this incredible company. So before we jump into what SmartX does, paint us a picture of what the textile industry is like and what was the problem that you saw and felt like this has to be solved right now.
00:14:28
Speaker
Yeah. So we identified a first pane that was very specific pane for a very specific client, which is the knitting and weaving factories. They are transforming yarns into fabrics and they are producing some wastes in the process, some defects, some quality control issues, some folds. And this waste most of the times goes to the supply chain until the garment stage or close to the garment stage.
00:14:54
Speaker
and it becomes expensive waste later on in the chain. That was the first initial pain that we found. That's how we started with a camera system for quality control, inspection, and so on. But then we have been stumbling in larger and larger problems since then. For example, we started installing these cameras inside machines a few years ago. I remember in Italy, in a big factory in Italy, and I asked the Italian owner
00:15:20
Speaker
Hey, can you give me the password of the internet so I connect my cameras so then I can see it's remote and so on? And the Italian guy, he was like, what do you mean by internet in a factory? I don't need that. My workers will be on Facebook the whole day. I don't need that. So that was the moment when I was like,
00:15:39
Speaker
Holy fuck, this is much bigger than just textile inspection. So we started also deploying in the factories, routers, access points, cables. We started putting little screens in the machines so we can track workers, production orders, planning. So we started putting a bunch of other building blocks to create this smart factory ecosystem. And later on, now we are selling a solution. We can go there in a minute about fact, core, loop. We are selling a set of products to make the factory of the future.
00:16:07
Speaker
which we call the modern textile factory. That produces no waste, that is connected, and so on and so forth. And more recently, we are stumbling now in the traceability issue, which is another big thing and legislation is pushing for that. So since we are the only company that has hardware connected in the factory and we have the routers and access points and the connectivity, we are in a privileged position to get that precious data and transport it for traceability reasons and for legislation compliance
00:16:36
Speaker
and all that stuff. So that was the pain that we started and the pain that we stumbled on.
00:16:42
Speaker
And so you created this whole ecosystem basically that you needed to create it because your solution alone wasn't going to work in a factory. Exactly. Imagine Uber without the iPhone, right? Uber needs the smartphones to exist, right? But we need to build the phone, the app, you know, the internet network. Absolutely. We need to build all the build blocks. Yeah. So the SmartX system, you mentioned the core fact and loop. Yeah. Could you explain each of these and what they do?
00:17:07
Speaker
Sure. So Core was the initial product that I mentioned. So with cameras that we install inside any machine, we are focusing a lot in circular knitting machines that are weaving and knitting. We are focusing on knitting to start. And these cameras, they inspect in real time the fabrics. They stop the machine if necessary. So we can avoid waste at the very beginning of the process. Because if we don't stop that waste there, it will propagate until the end. So that's pain number one, defects and waste.
00:17:36
Speaker
painkiller number one, cameras, and stop the machine. So we avoid that.
Future Expansion and Challenges
00:17:41
Speaker
Second one is FACT, which is the platform, online platform, that I can see all the machines in real time. I can see the pictures, the role maps. I can see performance of machines and workers. It's like a digital factory dashboard. And so the production manager can access from home and see the machines in real time, see the workers, and have planning and management and all that stuff.
00:18:02
Speaker
there. Actually, he uses this platform to find problems before anyone else. He's like, machine number two is producing more defects than machine number five, or as an oil leak, or things like that. That's fact.
00:18:13
Speaker
And because fact exists, we have there precious information. We have roll number, machine number, production order, worker, yarn composition. We have lots of precious information there. And that's why we created Loop is a set of QR code systems that are impossible to remove from the fabrics.
00:18:32
Speaker
It's like a heat press QR code. And this QR code transports all of this information through the subsequent stages. The industry is very fragmental. There are like 10 different factories to process a textile role, like the knitting, the weaving, the embroidery, printing, dyeing, finishing. There are lots of processes there. So if we have QR codes tagged to the role, this QR code will speak for the role. By the way, fun fact, today they use paper, pen and paper, sometimes attached to the role.
00:18:57
Speaker
Super easy to cheat the system, super easy to swap roles. This role comes from China, this role comes from India. You never know where it was made. All of the industry now works with pen and paper and human audits and human certifications. We can go there as well if you want, but it's a billion dollar industry just in human audits and it's also super easy to cheat the system.
00:19:17
Speaker
So when you talk about defects, what is a defect at a production stage? We can go philosophical here, because a defect sometimes for Gucci is not a defect for Zara. And sometimes they are producing in the same machine. That's why I believe machine learning is so powerful, because it can really understand like a human nuance and subjectivity of fabrics. So our systems, they look at the piece of fabrics.
00:19:41
Speaker
And they look at the last few meters of production. They look at a billion of image database and understand this little line here is a yarn knot or is a contamination or is like part of the pattern because the pattern is like kind of crazy.
00:19:57
Speaker
And it attributes a score to that particular fabrics, like from zero to ten, you know, and then we teach our clients to see like ten is a defect for sure, five is like you can accept it or not, maybe Gucci accepts, Zara doesn't accept, like a zero is like perfect clean fabrics.
00:20:15
Speaker
So we have this system of subjectivity with machine learning that is really powerful. But to be honest, most of the times, like 90 percent, we are talking about defects that are really like broken needles and create little holes on the fabrics or contaminations in the yarn that creates little white dashes in the fabrics. And these are usually defects that if nobody stops, they will continue for 100 meters.
00:20:39
Speaker
500 meters, one kilometer, and all of that pharynx goes to the garbage, or somehow it's destroyed, somehow stolen. These are the types of defects we are talking, but there are many, many types, hundreds of types.
00:20:51
Speaker
So how are you training the system to identify defects? You mentioned it briefly, but it'll be nice to just go into that. Any machine learning company depends on high quality data to label things. So if I'm building a self-driving car, I need a bunch of pictures of cars, bicycles, sidewalks, and I need to have these pictures very well labeled. That's why they put people working for them. This is a bicycle. This is a sidewalk. Here, we have also billions of images of textiles.
00:21:19
Speaker
in multiple wavelengths of light, in multiple light conditions. We have these conditions of light. And then we have particular defects that we train. We don't trust anyone else to train. Actually, inside this company we only have three people that we trust.
00:21:37
Speaker
to label images. Because labeling textile images is more a philosophical discussion than a yes or no. It's not like bicycle or no bicycle. No, no, no. It's like, this might be a bicycle. Hmm, what do you think? Maybe Gucci would like this to be a bicycle. Maybe Zara wouldn't like this to be a bicycle. So we need to start giving weights. And that is a really very complex problem to solve. We also tried to outsource labeling, like many machine learning companies do. Never went good. We also tried synthetic data.
00:22:07
Speaker
Many machine learning companies tried and it worked for their applications, didn't work for textiles. Textiles are really complex monsters and this industry deserves a special treatment even for software architecture. We do it very specifically for textiles because of all of these things that we mentioned, right? The subjectivity, the flexibility, the transparency, all of these variables, so infinite variables.
00:22:29
Speaker
So I'm guessing this database is constantly being updated and it's being refined over time, the more information you collect as well. And we apply it to our clients as well, because the clients that bought our system two years ago, they get new models every two weeks or every month. So they are feeling the benefit of also sharing some of the data with us. Of course, now we are becoming more and more
00:22:51
Speaker
careful with these data things, especially in Europe. So now we have a set of clients that we use to train models and most of our clients we don't touch their data.
00:23:00
Speaker
Is there any reason why you started with circular knitting machines? Is there a lot of waste in that specific industry or it's just where you started? It was more because of the family background. Usually knitting and weaving, they don't mix up a lot. Usually you have factories for knitting and factories for weaving. So for the audience, knitting is more sportwear, t-shirts, socks, and weaving is more like suits, shirts, home textiles, and usually the world splits into 50-50.
00:23:29
Speaker
50% of the fabrics is needed and more or less. So we started in knitting because of that background, but also we got the opportunity many times to go to weaving. We did some pilots in weaving factories and so on, but strategically and also being a startup, we decided to kill it here, be like the best one in this segment. And then once we are inevitable here, we go for other segments. I have seen too many startups dying from
00:23:56
Speaker
trying to do everything at the same time and not focusing. So let's focus in one thing is very challenging, especially in this industry that everybody is asking you for teachers. Right. It's tempting, isn't it, to run in 10 different directions. It's super tempting. There is no other technology. So they are like, hey, dude, can you bring me like a planning system, like a tablet screen, a television to the factory? So everybody wants new tech. But we need to focus and really be good in our segments. And then maybe later on, we can think about all the possibilities.
00:24:23
Speaker
This system can clearly be expanded to other textile processes such as weaving, but then you'll have to train the models again with woven fabrics then. Exactly. That'll be a whole different system at that point. Are you allowed to share with us about some companies or countries where you have deployed SmartTech successfully?
00:24:40
Speaker
Yes. So we started in Portugal is our sandbox. Also, the Portuguese industry is very resilient and they kind of survive to the Asian hubs because they are closer to Europe. So we usually faster on deployments and also they specialize a bit more in the high end fabrics. But still we find the whole supply chain here. So Portugal is our sandbox, but it's a small market.
00:25:01
Speaker
Our largest market now is Turkey, is where we have most of our deployments. But we also have a few clients in Uzbekistan. Lots of clients now starting in Bangladesh, like at least 10 deployments already. Thailand, Indonesia, a few clients. And we are starting very strongly in India. And we are opening our first clients now, and we have a big trade show now in March in Coimbatore. Also, Egypt, a few deployments there, one deployment in Brazil.
00:25:31
Speaker
So we are going and chasing the early adopters, the factories that are the best factories of their hubs, the ones that are willing to try new things, the ones that are willing to change their processes. For example, the industry always has production, inspection, production, inspection. And by the way, sometimes the inspection happens two times for the same fabrics, because you have exportation, exportation, inspection. So before you ship, you need to inspect everything.
00:25:56
Speaker
And then the other guy on the other side, he will inspect again
Startup Growth Insights
00:25:59
Speaker
the same fabrics to receive it, to double check if you are not sending. And sometimes they don't agree. Sometimes one sees more defects than the others. It's an interesting discussion there. Sometimes there is a third-party inspection, by the way, the referee.
00:26:13
Speaker
So we want to work with companies that are willing to change the status quo, willing to change and challenge this really thing. Like, do I need to inspect this twice? Can I use a machine learning system to track this, even if it is expensive and can cost millions of dollars to implement the full factory, hundreds of machines. It is expensive, but these factories, they are willing to change the status quo and really challenge them.
00:26:38
Speaker
the waste things, the quality control things, the human inspection things. And the ones that are willing to do that, they find a good ROI. Sometimes like in less than two years, they have the systems paid and profed, but they need to be willing to change. So you seem to go directly to the factories that have the machine set up and running already. Are you working closely with manufacturers of machines itself and to integrate it at that stage?
00:27:01
Speaker
Yes, as well. The OEM business, as we call it, is very strategic and important for us. Although, if we really want to make an impact in the world, while I still don't have many gray hairs, we need to go after the existing park of machines, because these machines last forever. These machines have like 20 or 30 years old of lifetime.
00:27:22
Speaker
So we have like the new machines in the market represent like 1% per year, or maybe not even that. So we are targeting both sides, but mostly the existing park.
00:27:33
Speaker
What are some of the challenges or resistance that you have faced when you try and approach factories with this technology? Many, okay. We are having tough skin here. And that is nothing easy on this business. Inside Smart Text, we have like four companies. We have a machine learning company, software. We have a hardware development company. We need to develop our own cameras, sensors, lenses, LEDs, PCBs. We have a logistics company, shipping stuff, installing stuff.
00:28:01
Speaker
And then we have a software business like to create these platforms and so on. So software, hardware, logistics and machine learning. These could be four different companies. So we have like 30 people flying around the world to install our system in existing machines in very tough places. We are not going, when we go to Brazil, we are not going to Rio de Janeiro.
00:28:20
Speaker
going to the jungle right to the middle of nowhere where we go to Bangladesh we go to Dhaka four hours driving from Dhaka in the middle of tough places you know and so I got lots of food poisoning and all the experiences of traveling in these places
00:28:35
Speaker
But that's on the personal side and on the travel side. On the business side and tech, this industry, because of what you mentioned, doesn't have much technology in. Typically, we are talking about family-owned businesses, people that are really skeptical about technology, and it's like businesses that come from the grandfather, the father, the son. Usually, environments like this are not the most tech-savvy environments. Super price-sensitive.
00:28:59
Speaker
Sometimes we are negotiating discounts of 0.5%, like a deal breaker, you know, if I don't do me the discount, I don't close the deal, you know. It's very price sensitive. So all of these ingredients combined, plus the fact that we are talking about these countries very far away from each other.
00:29:16
Speaker
with lots of challenges politically. You see Turkey, for example, the Turkish leader inflation crisis. You see Bangladesh crisis on the banking industry. They cannot take dollars outside. All of these systems, all of these complex variables combined that make us
00:29:31
Speaker
our life really challenging as you can imagine. And then tech wise, we need to be training and teaching people to use a very complex system that we try to simplify it as much as possible, but we need some basic interactions. Sometimes our workers that cannot read, illiterate people. So we are putting machine learning, state of the art tech in the hands of people that never have seen a computer in their lives. And they are interacting right there in the factory floor and we need to train them.
00:30:01
Speaker
And this connection, when it happens, is magical. And it's something that really gives me a lot of energies to see these skeptical people using it. And when they see the machine stopping with a defect, they are like, wow, did it just stop with a Lycra defect? Lycra defects are invisible. Everybody knows that the Lycra defect is invisible. But it's like, it's there. And that's really magical.
00:30:24
Speaker
Oh, that's amazing. You know, how do the employees feel about this? Because again, as you mentioned earlier, when you hear AI, everyone's like, oh, I'm going to lose my job. What has been the response from the
Sustainability and Social Impact
00:30:35
Speaker
actual people on the floor of the factory, not the CEO, but the guys on the floor? Are they feeling threatened? They are in the first moments.
00:30:43
Speaker
But we tried to put those cards in the table right in the beginning when we are training them. It's like, hey guys, no one here is going to be fired because this will make your work to be like twice as more productive. We see that a lot in Europe and Turkey and now even now in Bangladesh in these first deployments.
00:30:59
Speaker
we are seeing that, in general, the world is having lack of people to work in textiles. Like, nobody wants to work in a textile factory, right? People usually want to go to other jobs as soon as they can. So the ones that, so that is that pressure, that is lack of people to work in textiles. So we need to make the few people that are there much more productive. So instead of being eight hours looking to an inspection machine, that same guy can inspect 10 times more rolls
00:31:27
Speaker
just with a computer next to him. And even sometimes he is going to inspect visually again. Sometimes he finds in our platform, this rule number three looks very weird. Let me inspect that one. And he goes straight to rule number three. So this guy's job is not threatened. He's actually much more productive now. So we see many times our clients, we have now more than 100 clients. But the ones that are really deployed and really using the system in the full potential, they remove sometimes some people from the inspection machines.
00:31:56
Speaker
and they put them working in other parts, mostly in the machinery, in the production. They can produce more with the same resources. And by the way, when we do our ROI calculations to convince them to pay a big amount of money, the main variable there is the savings due to raw material. Yarn or cotton that you are not going to waste. That's like the biggest saving. If you fire your inspection team, that is not even in the same order of magnitude.
00:32:23
Speaker
Wow, Gilberto, you've managed to do, like you said, it's four mini companies sitting under this umbrella almost of SmartEx, isn't it? And you only started in 2018. Tell us a bit about that. How did that come about? What's the journey been for you personally to found a startup and then grow it so quickly to where it is today? Usually founders tend to sugarcoat at this stage how awesome it has been. It has been awesome. It's really awesome. And I've been learning from the best of the world.
00:32:51
Speaker
But that is nothing easy here. It is tough. No vacations, no weekends, no Christmas. Of course, I try to manage the family and life and everything, but the sprints are real and the stress is real and having tough clients, sometimes insulting in your face, you know, things is really tough and chasing investors and all of these things.
00:33:11
Speaker
But somehow we found a cycle here that we can attract clients, attract investors and have a lot of fun in the middle. Because in the end of the day, life is about the people you work with and what you do, the products we build. And these two, we couldn't be more proud of the things we are building because they create lots of benefits to the world. And the team that we work in is like super fun to work, super smart people.
00:33:35
Speaker
We have 17 nationalities here in the office, Canadians, Americans, Brazilians, Turkish. So we found a way to have tons of fun so it doesn't feel like work. But it's really, really challenging. And we got some luck strikes, some talented moves that we have done to be able to get here. Because if you think about it, there were no
00:33:56
Speaker
computer vision companies that were able to scale in the textile industry. You have a few players in the market, but usually they deploy some tens of devices in very specific situations. Nobody has even sold thousands of devices in two years like we did.
00:34:12
Speaker
Wow. We believe we cracked here a pricing problem and we cracked a tech problem with machine learning. So that's really, really, we are really proud of that. And that makes us feel even more energized to the many challenges that are away. I used to say to my team, we will laugh that we started as a defect detect. This is much more than that. It's like the whole industry operative system is in our hands and we can do it if we want.
00:34:36
Speaker
I mean the ripple effect of your technology is mind-blowing. Could you quantify that a bit? How the impact that your technology has had? Yeah, so because we are building the plumbing system of the textile industry, right? We are building the pipelines for the data to flow, right? We are doing a dirty job, so then in the future software companies can run their systems on top of our
00:34:57
Speaker
infrastructure, right? We are kind of the Amazon logistics things behind things and then other companies can come on top of us and do traceability services and do like stock management. Imagine in the future fashion brands will have as little as stock as possible, right? They will be selling on demand. You start seeing that trend with Cheyenne with some other brands. They are selling on demand online or in shops and they are producing almost in the same time and the factories will be much more much more
00:35:26
Speaker
This thing of producing a thousand t-shirts, small, a thousand M, a thousand large. This won't be the future, right? Because you have debt stocks and a bunch of waste. The industry is going into this trend. Everybody wants to catch this wave, but first things first. Let's make sure the factories don't run independent paper first. Let's make sure we have cameras and sensors and things connected to the machines that can speak with the outside world. Because today we are light years away from that reality. And that's what we are building.
00:35:55
Speaker
You did mention that textile and fashion industry is extremely price sensitive. Everyone's trying to lower their prices. Brands want production to be done at lower prices. How did you navigate this to reach a business model that makes sense? Yeah, super challenging, super, super challenging and education of the clients as well. We believe that this company would only be possible now. If we were 10 years earlier or 10 years later, it wouldn't be possible. And let me explain you why. 10 years ago,
00:36:24
Speaker
the hardware would be much more expensive, cameras, sensors. Now, especially because of the smartphone industry and the mobile phones, it's much more democratized. We can find electronics and cameras, high resolution cameras with much more affordable prices. That's actually why we chose to have Tony Fadal in our, one of our main investors, because of all his experience with hardware at Apple, at Google, he's helping us a lot in that front. Now, 10 years ago was not possible. Now it's possible to have
00:36:51
Speaker
a full system with 10 cameras, high resolution at a very low price, so then we can make an interesting profit in our sales. That's first. Second, machine learning is now democratized. Everybody can do a machine learning model. Like three kids in college can launch machine learning models in an Amazon machine. So that's much more democratized now.
00:37:09
Speaker
Third, there are much more talent. There is much more talent in the world, right? I mean, 10, 20, 50 years ago would be much more difficult to find software engineer. Now we have like people from everywhere in the world, amazing talents, connected, we can work remote. So it's much easier to create a technology company and scale it.
00:37:27
Speaker
than before. So because of all of these factors, this is a cocktail, an explosive cocktail that makes possible for us right now, and not just for us, for many companies. I really believe that who is not in tech in 20 years will suffer. I used to tell to my doctor friends, my accounting friends, my lawyer friends, guys, find a way to go to tech. Even if you want to be a lawyer, find a way to be a lawyer in the tech world, because this is a cocktail that is exploding now.
00:37:55
Speaker
What happened in the 90s was just at the tip of the iceberg. Now is what we are seeing in the world connected. Plus, there has never been so much money in the world invested in technology. And a guy like me, based in Europe, I can attract funds from Silicon Valley and build a company, a software company, a very cash capital intensive from Europe. That would not be possible 20 years ago. I needed to be in Silicon Valley to do this.
00:38:19
Speaker
And again, hardware, it's really, really difficult to get investors to invest in hardware startups. It's a big challenge. How did you crack that? Yes. And that too in Silicon Valley. Yeah. We were very sales oriented in the beginning because we got lots of clients to sign that's like, I'm interested in this. I want to buy this to show that initial traction before we even had the product.
00:38:42
Speaker
That was a very good move and investors love that move. But indeed, you are right. There are many investors that they don't really open the door to speak with me just because we have a strong component of hardware. We cracked that problem somehow because our business is first hardware. We need to sell and install hardware. But our main product and our main strategy is the software that runs on top of the existing hardware that we deploy. It's like Apple. Apple deploys iPhones around the world.
00:39:09
Speaker
But then they make their living from the services that they charge on top of the phones. And then we have a Mac, the AirPods, the iPhone. You are locked. You will never leave, right? If you lose your phone, you need to buy another iPhone because you have the whole ecosystem, your photos, your memories.
00:39:25
Speaker
So we are trying to become Apple of textiles in that sense, that we deploy hardware, but then we create something bigger on top of the hardware. And that's usually something that is much more big picture and attractive to investors. Of course, the path that we need to make to transform this industry is not just about the hardware, although I don't want to push water up the hill.
Industry Complexities and Opportunities
00:39:48
Speaker
If my clients want to buy hardware and then we wrap up software services on it,
00:39:53
Speaker
Let's do it. I don't want to be a fundamentalist SaaS founder that just sells subscriptions. We need to adapt to the world that we are. So that's why when investors talk with us and they are very, very obsessed about SaaS, SaaS, SaaS, usually that's not the right investor for us. We prefer to have investors like H&M is a good investor of ours, Tony Fadal, Lightspeed Ventures.
00:40:16
Speaker
Bombic's capital, also textile focus. You might find some good speakers for your podcasts there. Brilliant, yeah. Because these people are more focused in the big picture of the industry, how we are going to really transform it and impact the world than with SaaS software metrics.
00:40:31
Speaker
You produced the modern textile factory report and that was quite an undertaking where you had input from factories, policymakers, brands, companies, companies who were introducing innovative tech into textile factories. What was your motivation to compile this report?
00:40:48
Speaker
I feel, and we felt a lot, me and Max, Max was the author, we felt many times that fashion brands and the startup worlds, they were living in a different galaxy as the factories. And when you ask a fashion brand what they really want for the future, traceability, sustainability, ESG, digital product passport, I want to know all the information about this garment. How much water did it consume?
00:41:13
Speaker
Where was it made? Is this China cotton or is this Turkish cotton? Where are the materials from? And which process has been true? All of these questions that everybody wants to have the answer, they depend on the factories and the machines. And nobody knows, and sometimes even inside fashion brands, nobody knows exactly which machines are used, which processors.
00:41:34
Speaker
Where are these factories? Again, not their fault, not their fault. The industry is very complex and fragmented. The fashion brands, they buy garments from the tier one, but tier one has a thousand of possibilities to buy finished fabrics. And the tier two has thousands of possibilities to buy yarn and so on and so forth. So it's really complex. Nobody knows how to crack this problem. Who says they know? They don't know. And we have lots of brands that they say identify, they have everything mapped.
00:42:02
Speaker
But it's so easy to sleep. So we felt the need of showing the world the importance of textile factories before we ask for the beautiful things that the fashion world wants. Because we need to solve A to then go to B.
00:42:19
Speaker
And that's exactly what it was. It was such an eye opener for me to read through this report. And there was an interesting quote in there by Ken Pucker. And he said, if you were able to turn back the clock about half a century and visit a tannery or a cut and sew factory, much would look the same apart from the address. And that really hit me.
00:42:41
Speaker
Yeah, it is. The mechanical technology, the machines, they generally became faster. They produce faster, they are better, they are more electrical, and so on. But the process itself, because of the complexity of materials, is really the same. And we believe that is a massive opportunity here. Trillions of dollars are being generated without access to internet. And we can be the ones connecting the world in that sense. So it only depends on us. That's what really excites us.
00:43:11
Speaker
And by the way, for other startups that might hear this podcast, we are constantly looking for bridges, to build bridges with all the technologies around, like all the traceability hubs, traceability startups. I used to mock a bit on the blockchain platforms because it's like, dude, why do I need blockchain if I don't even have data to put in the blockchain? But I'm more than happy to collaborate with these guys because I really believe this won't be one company solving the industry. We might solve part of the meeting, maybe weaving, maybe tier two.
00:43:40
Speaker
but we need to have more bridges to the other sites. I'm very excited about chemical traceability, for example, for the fiber or other types of traceability that we can use.
00:43:50
Speaker
As you said, the textile industry is so complex and you need as many hands on the deck as possible to try and align the supply chain. Definitely. What was a couple of the most surprising insights that you learned from the report yourself? So, because we had so many different people on that report, we have people from factories, but also from the brands, also from like fibers, like renew a sale.
00:44:16
Speaker
When we put all of these people in some sessions, and we had a few sessions, we had like 10 sessions or five sessions, we had some sessions together during the year to discuss particular topics, it's interesting because I am obsessed with the factories and with the factory processes. But seeing all the perspectives, like Christine, she used to work with Pangaea and Gucci and Balenciaga as a sustainability director there, she was much more focused in other things that usually we don't see lots of people caring about that in fact.
00:44:46
Speaker
Like, oh, I want to know more about the salaries of the people, you know, like the wages and stuff. It's interesting to see that that trend is there, although my point still remains, which is, for example, if I want to know more about the salaries and the people, I need first to know at least where is the factory, the name of the factory, right?
00:45:04
Speaker
Is Mr. Gilberto factory in Portugal or Mr. you know, I need to know at least locations where the fabrics is made. And that's the first step that we want to solve with technology, because then once we have that building block, we can start collaborating with other startups for social and labor, securities and their interest ability and ESG impact measurements. Then we can do a bunch of cool stuff on top of infrastructure.
00:45:28
Speaker
Could you briefly explain to us about the five pillars of a modern textile factory that was mentioned in the report? I will share the report in the show notes if that's okay. I think it's absolutely fascinating for everyone to read it, but if you could just summarize the five pillars. Yeah, there are many angles there, I guess.
00:45:46
Speaker
We can summarize it in one big pillar to summarize, which is the data. Having access to data, I guess, and everybody that agreed multiple times, is like, yes, I've been working with two or three traceability platforms. Yes, and the factories, they need to pay for five different certifications. They need to pay to SGS certification guys to go to the factory once a year to write a beautiful report.
00:46:12
Speaker
Then they pay to another, to God's certification, they pay to many other certifications. It's an investment that the factories need to make, to have a few flags at the door.
00:46:23
Speaker
And in the end, when we were looking to all of these challenges, everything goes around data, having reliable data from the factory. For example, the guys that come from SGS to do a beautiful report about compliance and stuff, they go through the invoices, they go through the machines, they see the fire extinguishers, they see, and they write a report about the general safety of the factory, the general production, and so on.
00:46:48
Speaker
All of this could be done with technology without needing to fly a person from Zurich to Dhaka. All of this can happen if you have things monitored in the factory, if you know that that textile roll came from that factory and was dyed in the other and was gutted in the other. If you know the locations and you can prove it with QR codes, cameras, tech, you can pass a bunch of these manual processes in front.
00:47:11
Speaker
So data is, I would say, the main words of that report. And then it goes to all the other pillars. One of the pillars was the social thing. Another pillar was the automation, data-driven decisions, to take decisions to become more efficient, to avoid waste. All of this comes from the same source, which is having reliable data from what the hell is happening inside that factory, which many times even the factory owners don't really know very well. So let's solve that problem first, and then all the other ramifications will come from there.
00:47:41
Speaker
When I look at your website, you quantify the impact that your technology has had. And as I mentioned in the beginning, so 961,000 kgs of textiles that were saved. How are you kind of getting those numbers and what are some of the other facts that you can share with us about the impact of your solution?
00:47:57
Speaker
Yeah, very important there, because we are stopping the machines in real time. So we are avoiding those defects to propagate to the front. So you can tell me, how can you say that you saved 1,000 kilos here? Because you stopped the machine in the first one. You don't know how big of a disaster it was going to happen after you stopped, right? And that's a very valid point that we have that explanation also in our website, how we calculate.
00:48:24
Speaker
We base on that same factory, that same machine a few months before. We usually install our camera systems and we let them be there for a few weeks or a few months, so we have a baseline to subtract. Of course, this is not exact science, you can argue with me. How can you prove that the factory was behaving in the same way
00:48:47
Speaker
before and after I mean we can go into the details and we can go into greenwashing conversations and really squeeze it and it's like oh maybe they are exaggerating here we can do that exercise it's it's it's fine but my I'm not so much concerned in getting into the details of the numbers I'm not more concerned about like hey look at this factory 2% waste before 0.1 after
00:49:08
Speaker
might not be 0.1 is 0.2 or it was not 2% was 1.5 but I don't really care about those data it's like we made this difference here now we know the average water per kilo water usage to dye one kilowatt fabrics and you might say but how do you know that because you need more water to dye black fabrics or white fabrics it's like sorry my friends is an average I know the industry is not ready to have
00:49:31
Speaker
that traceability at that level. Actually, that's one of the problems we are trying to solve, is having the exact traceability. For now, just with the defect inspection and detection, we can say machine by machine how many kilos we save per month. Then we transform kilos to energy, kilos to water, kilos to chemicals, based on the factory consumptions, the country where they are, and things like that.
Personal Growth and Company Evolution
00:49:55
Speaker
And you might ask, how important is this? We don't obsess with these numbers. We need to get to 100 milliliters of water. We don't obsess with that. It's just for us to have an order of magnitude of the impact we are creating here. Because that's also more and more important for
00:50:11
Speaker
for everything to attract talent to attract investors to even for our own mission goals and to like measure our impact in this world and sometimes we are doing so many efforts like I will become vegan I will never drink in plastic straw I will have like we start making so many efforts but when you look to the order of magnitudes of what you do like oh my god looking in smart x I can
00:50:34
Speaker
I have so much more impact working in SmartEx in my eight hours per day than being vegan the whole life and driving electric cars and things like that. It's just for us to have an order of magnitude about how much impact we are creating. And it's really insane, especially given that we started selling two years ago. It's really insane.
00:50:51
Speaker
Honestly, Gilberto, it's really, really mind blowing what you've managed to achieve. And this is where I'd love to hear your sort of personal journey in sort of evolving with the company and the new hats that you've had to wear every, you know, so quickly as the company grew and expanded. And what's that been like for you personally?
00:51:12
Speaker
It has been quite a journey. And indeed, you are right. We need to evolve as CEOs, as founders. I always have been the sales guy, but now I'm evolving more into more leadership type of profile. And I have my sales team that helped me a lot in the field in trade shows and so on. Although I still go a lot to clients and travel a lot. So I have been evolving with my co-founders as well, because we are first time founders. And that's why we hang so much in these mentors and coaches.
00:51:40
Speaker
because they have been there, they have done that, they have grew companies from zero to IPO. So they have seen these challenges before. That's indeed a big challenge. And I'm always thinking a bit of this, how do you call it in English, imposter syndrome type of thing. You're like, I'm not good enough for this. I'm the first time founder, I need to improve more. So maybe that gives me extra motivation to always be working more, always be like fast answering, flying around the world, working on weekends, working on vacations.
00:52:09
Speaker
I guess that's a good thing and bad thing in terms of stress. But in general, we try to convert it into positive energy and have lots of fun. And we have lots of fun. Yeah, because a lot of founders tend to burn out after a point, especially when their company starts to grow, which is when they need to read their sharpest, but they've already burnt out by that point. So you need to look after yourself as well.
00:52:32
Speaker
Definitely, definitely. And having fun and doing things with people you like is half the way through. Sometimes I'm so much impressed. Sometimes I interview a lot of people, like job interviews. And it's so impressive how many, the percentage of people in the world that doesn't like what they do, or they don't like their boss, or they don't like their team, or they don't like their mission.
00:52:52
Speaker
but they live like that for years and it's really impressive because sometimes it's not about the money, it's not about the salary, it's not about sometimes when you just squeeze it is about those two things I was mentioning in the beginning is the people you work with and what you are building, like the products you are building. If you mail these two and you are good at these two, the rest will kind of sort out around the money, the growth, the experiences. If these two are there, if you optimize for these two, you'll be unstoppable.
00:53:19
Speaker
Before you founded SmartX, you were working as a researcher at the Center for Nanotechnology and Smart Materials, CENTI, right? Where you were involved in developing SmartTextiles. That's totally my cup of tea. Could you tell us briefly about the work that you were doing there?
00:53:34
Speaker
Yeah, so in physics, when I was in college, I always have been in this interception between technology, but because of the family background, I was always looking to textiles, conductive yarns, touch pads in fabrics, magnetic coatings or antibacterial coatings and things like that. And when I saw that research center, which is also in north of Portugal, they support these companies to become more sustainable with the chemicals that are good chemicals and things like that.
00:54:02
Speaker
When I saw that they were doing an internship position, I was like, oh wow, this is like my micopathy, right? It's an intersection between textiles and tech. And it was amazing years. I actually worked there for quite a few years because I was an intern, then I started being a full-time. But it was amazing because there are so many things to explore other than factories, right? Materials, which I guess is most of what you are more interested in in many ways.
00:54:30
Speaker
Like the coatings, the functional textiles, the functionalities you can put in garments to be more breathable, to have sensors embedded on it, is really a huge universe that I guess unfortunately didn't take off yet, despite some projects like Google Jaccard or some other projects, but I can't wait for it to take off and maybe be kind of part of it.
00:54:54
Speaker
You were part of the Fashion for Good accelerator program. What were some of the big learnings and takeaways that you had from this experience? Yeah. Again, asking for help to random people. That's how we got into Fashion for Good. I was living in China in that year. It was 2019. I was living in China in Shenzhen. I was prototyping hardware, electronics, soldering stuff.
00:55:14
Speaker
And I remember I was asking all of my investors, because my first investor, he was American, but he had an office in Shenzhen to help his startups doing robots. So I was there. I was constantly asking them for introductions to fashion brands. And they were like, dude, you have nothing to sell to a fashion brand right now. And I was like, yeah, you are right. Indeed, I don't have anything to sell to a fashion brand, not even to my clients I have.
00:55:38
Speaker
But I want to know what they're looking for so I can at least build my product to try to go in that way. Because all my clients, they always say, the profit is in fashion brands. If you want to maximize traceability, whatever tools, it's with fashion brands. So I was always with an eye on that. And they connected me with fashion for goods.
00:55:57
Speaker
based in Amsterdam. I was there in some events speaking with some fashion brands and we ended up being accepted in their acceleration program, which is basically a program that we went to Amsterdam a few times during the year to have a few sessions with fashion brands and some pilots that they would overview and help us getting through it.
00:56:16
Speaker
was more about the friends and the mentoring and the people around. We still go there quite often to other events and to help other startups because I really believe more things like these are needed, podcasts like this are needed to have this intersection between innovation and textiles.
00:56:32
Speaker
Fashion for Good as well. They ended up being our investors as well. Fashion for Good had a small investment fund. They invested in our capital as well. So all of this is needed and I would say much, much more is to be done because there are very little cases of success in the tech world with textile.
00:56:53
Speaker
What would be some advice that you would give other people who might be starting off in the textile industry as a small startup? It's a tough one to break into, you know that, but you sort of had some history and connections already with your family in the business, but how would others go about it?
00:57:09
Speaker
I see essentially three types of innovation going into textiles, or at least we can divide it in three buckets. One is materials, new materials, alternative letters, recycled fibers. That's the whole world there. Then I see the middle being more or less where we are, machinery, textile fabrics being produced more efficiently, softwares, to the supply chain in general until the garments are made and then shipped, dyeing with better chemicals, things like that.
00:57:38
Speaker
And the third bucket would be retail, like 3D type of fabrics, 3D experiences, retail returns, which is also a big problem. I would divide in these three buckets for simplification. I hope nobody gets mad with me. But for the bucket number two, I would definitely advise to do exactly what we do. It's like signing a bunch of clients even before you have a product, interviewing a bunch of clients even before you start laying the product.
00:58:04
Speaker
and being obsessed with the clients for them to implement and to pay. Sometimes you forget that last part. We just implement a pilot and the pilot never closes because actually what we are doing there is useless and nobody cares. Let's make sure somebody is putting the skin in the game and be obsessed with that in the early days.
00:58:24
Speaker
You don't need to be like a 20-people team to do that. You can be like a three-people team to do this stage. And then raise your pre-seed or raise your seed round. And there are many, many books with this playbook. I would suggest the book Build by Tony Fadal. I would suggest a lot the book The Great CEO Within by Matt Mochari. I would suggest the classics, the classics Zero to One, like the classic startup books. Hard Things About Hard Things from Ben Horowitz.
00:58:53
Speaker
There are a lot of great books to go to this journey, but I would suggest that. On the other two buckets, I don't want to be here telling what to do because there are really different challenges there, but this thing of being client obsessed and identifying a pain and a painkiller from the beginning and very specific and kill it there, I think this applies for most cases of companies and with some exceptions, but I would double down there.
00:59:22
Speaker
Is there something you would have done differently if you were to start your business today? Oh, yeah. Many things. Oh, yeah. That is one of my favorite books is a book called Thinking Fast and Slow by Daniel Kahneman. And he has an entire chapter about the fallacy of planning. Everybody fails planning by orders of magnitude. This is insane. And indeed, the unknown unknowns of building a new product because you have technical risk.
00:59:48
Speaker
in the new markets, because you have market risk. In a new country, in new geographies, you have political risks. The amount of unknown unknowns is insane for any startup, but specifically in textiles. So, of course, I would do many things differently.
01:00:05
Speaker
For example, one of the classic mistakes founders do at this stage is because we are cash constraints. We are always frugal. We tend to hire more junior people, which is great, as long as they are machines, they are A-players, they have the energy. I love to work with young guys, but we need to have the right mix with very senior people as well.
01:00:24
Speaker
We try a lot to bring external advisors, investors, very experienced people here. But maybe if it was now, I would hire a bit more senior folks from the beginning and avoid some technical debt.
01:00:38
Speaker
Now it's easy to say because we raised a bunch of money. We raised $40 million. But a few years ago when we were like sleeping in the same bed with my co-founders, it was a bit more difficult to say this, but yeah.
Future Vision for Textile Industry
01:00:49
Speaker
Your mission has been to empower factories to produce zero waste and have full traceability. How do you envision that in the next five to 10 years for SmartEx and for other companies? So the mega trends in textiles are about shorter orders on demand.
01:01:07
Speaker
much more automation, less human dependency, less paper dependency, right? These are the trends like paperless factories, robots everywhere. We are covering these mega trends for the next 10 years. So I see SmartX being a part of it in some different ways. One is with the computer vision stack. As far as we know, we are the only ones with such a complete computer vision stack for role to role production.
01:01:32
Speaker
and scaling that in thousands of units, that will be for sure part of this factory of the future because you will need to be looking at digital twins of textile roles and to do all of that stuff. So cameras will be needed everywhere. Like if you go to a car factory or electronics factory, you already see that, right? It's not like this guy is a genius. He's like brilliant. He's seeing what others don't see. No, it's like just look to all the other industries. It's just that this one is more complex to automate because of the complexity of the materials and the price point, right?
01:02:02
Speaker
So let's just look at the other industries and see what is working very well there. So is that automation paperless cameras and computers and everything? So I believe SmartEx can be really an interesting part of that future by having a bunch of cameras deployed as much as possible.
01:02:17
Speaker
a bunch of routers and access points and infrastructure things that will be part of the backbone of the industry. Like IBM used to be for banks, you know, like the systems, the interconnected systems. And eventually, if we build that pipeline, that plumbing system of textile industry, we will be able to welcome other startups and other companies to build things, cool things on top of us.
01:02:41
Speaker
So that's my vision for it, and that's what we have been working in the last few years, day and nights, to achieve. So we have the capital, we have the big market there waiting for us, clients paying. So if somebody fucks up, it's on us. It's on me. But do you feel there is a market pull for new technologies like this, or are you still trying to create awareness and convince companies of what these new technologies can do?
01:03:08
Speaker
Another mandatory book for any founder listening to this is a book called Crossing the Chasm, especially for B2B companies. Once you close your first few deals, that book is mandatory because the world usually divides in like 20% of the people. They are early adopters. They like to test the new iPhone. They like to be the ones driving the new Tesla in their city. They like to be the ones exposed to some risk in exchange to be the
01:03:35
Speaker
the new guys having a new tech. 80% of the world hates that. And it's like the majority of the world is risk averse. They don't want to be the first ones driving the first Tesla. They want to be the last one driving the first Tesla. They want to be when enough people are using Teslas, they are like, okay, now my fear is not being too early. Now my fear is being too late. So I want the Tesla as well.
01:03:57
Speaker
So most of people they will operate like this. So we need to find the first 20%. And those ones, definitely they are folding. We feel them, they're calling us, they are insisting, they are paying for it. And that's great. The second one, and it's really a sharp division there, the book is called Crossing the Chasm because the chasm is the space between these two groups.
01:04:17
Speaker
The second one is really, really difficult to crack and that's actually where most startups die. So I believe that the textile chasm is a huge challenge for us. We didn't pass it for sure. We still have many clients, some clients that are
01:04:32
Speaker
in the second group that they tried our system, they are not in love with it, to be honest. They don't want more. The first group, the 20%, they love it. They want more, they can't wait for the new releases, they help us developing and stuff. I would divide my answer in these two groups. The first 20% are loving, the second 20%, 80%, we are not killing it yet.
01:04:54
Speaker
It's very honest, I love that. And now coming back to where we started, which is your family and the factories that your family has. Now the big question is, are they using your smart technicians? Let me tell you exactly what my parents do just to justify this.
01:05:12
Speaker
My parents used to work many years in textile factories, like textile workers, machinery operators. More recently, when I was a child, like eight years old, my father decided to start his own business in textiles with a small warehouse, a small middleman trading. There are many of these around the world. And he works with my mom and with my brother.
01:05:34
Speaker
And the wife of my brother, so he's like a four people company type of family business, you know, very small, but self-sustainer and so on. So they don't use my system because they don't have machines or production. But it's really interesting because now we have these QR codes in our factories and they start seeing rules going by in the trucks and in the vans and the containers. They start seeing those QR codes and they're like,
01:05:59
Speaker
Huh, what's this smart text? My father called me one of these days. Hey, I saw this QR code thing. I love it. But why do we need this? And I was in the phone and I was thinking, damn, we didn't think about this. We didn't think about what the middleman will think about the QR code. We need to have some messaging. And I called my co-founders. Guys, let's put some messaging in the fucking label. Let's put the duct tape saying, find the QR code, scan it, see it. So people like my father,
01:06:25
Speaker
he can really have the benefit of it. And he starts calling the factory saying, hey, I want this QR code more often. And then we can increase sales. So I still see my family like every week. I have dinner with them. And we talk about these things. And my father, it tells me a lot of little cases of, you know, that guy is cheating the gods system. That guy is cheating the recycled yarn thing because that yarn is not recycled, but he mixed up with the other yarn. So he knows all of the little nuances.
01:06:53
Speaker
of the textile industry and all of these rabbit holes that usually brands don't go into. So we make our products to try to be bulletproof because we know that people will cheat the system when they can. He sounds like he's an encyclopedia on textile factories and what goes on in there. So definitely picking his brains is a great place. Yeah, definitely.
01:07:15
Speaker
Well, Gilberto, what a fascinating conversation. Honestly, I love your passion, your energy, your commitment, and the fact that you've got a solution that you're able to take to market and solve a huge problem that the textile industry is facing. And the ripple effect of that, probably we don't get to see today, but we will in the next five to 10 years. And I'm really looking forward to just seeing how you grow.
01:07:39
Speaker
and keeping a very close eye on Smart X and all that you're going to evolve into as a company. Thank you so much, Millie. It was a pleasure. And please continue because we need more content like this. Thank you. My pleasure. Ciao. Ciao. How amazing and insightful was that conversation? I mean, I learned so much from Gilberto today and hope you did too. I think an observation from my side is how focused he is.
01:08:04
Speaker
He could be going in all kinds of directions and all kinds of people asking him for solutions to problems maybe in the weaving sector or any other part in the supply chain. But he is laser focused on being the best in the area that he has carved out and started in, which is the circular knitting machine factories. And I think this is really important for startups. Stay laser focused on very specific pain points that you're solving for a very specific target group.
01:08:32
Speaker
This right here is a secret to success. It's also great to meet founders who are open and share about their struggles as well in starting up their company. And it was clear from his journey that it wasn't an easy one, but he plowed through and worked hard to build a company to where it is right now in a very short time.
01:08:52
Speaker
As he said, you just don't know the unknown unknowns when you start a business. And when things don't go according to plan, it's your vision and the purpose that helps you stay on track. The Modern Textile Factory Report link is in the show notes, so please check that out. It is a really valuable resource. Challenges in the fashion and textile industries are very, very complex and cannot be solved by one startup. New technologies such as AI
01:09:21
Speaker
and machine learning are enabling solutions that are never possible before. And there are so many opportunities for innovation and I hope this inspires you to find solutions to some of the pressing needs that we have in our industry. My hope is that this podcast is interesting to those in the textile industry as well as those in the tech industry because I want to encourage and promote cross-disciplinary collaborations.
01:09:44
Speaker
We all hold different pieces of the puzzle and we need to come together to solve challenges and innovate urgently to transform the textile and fashion landscape. Please do follow and subscribe to this podcast and leave me a review. I love to hear from you. And if you could spare just two minutes, I would love it if you could fill out a little survey. This would really, really help me get an insight into who's listening in and what kind of content you would love to hear more of.
01:10:13
Speaker
The link to the survey is in the show notes below and thanks again for tuning in guys. I really appreciate it. Join us again as we weave together a tapestry of textile innovations one episode at a time. Bye for now. This is your host, Meli Tharkand.