Speaker 3 (00:00.322)
Welcome to the first season of the Hard Tech podcast. The Hard Tech podcast is about bringing together innovators, builders, investors and thought leaders all in the world of hard tech. In my background and starting software companies that I've scaled and exited, there's so much content out there for folks building in the software space and not as much in the hardware space. And that's exactly why the Hard Tech podcast exists. In this episode, we sit down with Eric Martinez, founder and CEO of Modul. Imagine your first customer being Amazon.

having to figure out how to build, scale and deploy hundreds of thousands of units before you've ever got your first units off the manufacturing line. This story is deep, it's a real story and success story of what it means to truly grow and scale in the hard tech arena. It's a workplace safety platform. I really think you guys are going to enjoy this and for all the startup founders out there, this is really what it means to come up against barriers that seem insurmountable and make it past them. I think you enjoy.

Well, everybody, welcome back to the Hard Tech Podcast. I'm your host, Deandre Hericus, with the usual suspect, Grant Chapman. We've got a super exciting guest in Eric Martinez, CEO of Modual, a workplace safety application. We got connected on LinkedIn or email and... Based out of South Carolina, just so happy to be in Chicago for your son's...

How's it going, everybody?

Speaker 2 (01:12.686)
Can get a close

Speaker 1 (01:17.486)
PhD. PhD. In cucks. Awesome. So if we all can look at that up but it's something to do with stem cells and what cell body produces but he just got his PhD from University of

That's

Speaker 3 (01:29.742)
Yeah, congratulations. That's amazing. Just so I would be in Chicago. So he said, hey, I'll drive down so we get the he's in person, which is super exciting. He actually brought some really fun gadgets for us to look at it and play with and show off. Well, yeah, I'd love to get this quick little intro on the company in the background. And we were diving into so many different topics leading into this. But yeah, well, this would be a great episode.

Thanks, DeAndre. And so yeah, Modules started about nine years ago. We started to prevent repetitive motion injuries. And I was a former insurance executive and we saw that most of our bills were being paid out on, you know, strains, back injuries and stuff like that. And we were spending a lot of money basically in opiates and not trying to prevent the injury. Just, yeah, exactly. Just, you know,

smooth it over the problem.

hey, it's easier to kind of just give someone a pill than try to actually fix the real reason what was going on. So I left AIG and I started Module to kind of address that issue around repetitive motion injuries.

That's amazing. And so what was the very first repetitive motion you were trying to tackle and what tech were you using when you started to track that?

Speaker 1 (02:37.538)
Yeah. So we, we were going after the lumbar, you know, Liberty mutual does a really nice job of showing every type of injury that happens in the workplace. We're good at big data. They exactly know how many, what body part, what percent of the body part it's, you know, it's, it's $110 billion a year company spend on injuries. But then when you start breaking it down to the type of injuries like fall from heights, getting crushed by a machine, repetitive motion, chemicals, bee stings.

The actuaries

Speaker 1 (03:06.134)
breaking it all down to those subsectors, you kind of try to find your market. And we found our market on repetitive motion and lumbar strains. everybody always has aching back. And we said, that's our market to go after. And lo and behold, we land the largest customer in Amazon to kind of start our company.

is so great. Now, how did you make that first connection?

You know, I, I think it was, I would hate to say trade show because we never ever get a customer from a trade show. We always feel great after trade shows. Wow. All these companies stopped at our booth. Yeah. What, what happened?

Sure.

Speaker 3 (03:42.702)
created action emotion, right? exactly.

It was kind of popular. were, we got 47 leads from this trade show. week later, two weeks later, month later, nothing crickets. And so I want to say trade show, but I know that's not the case. Uh, so I think it was just pure old outreach and somebody knew somebody of new somebody. And of course, Amazon has been in the news a lot with their, at least in the past with their injuries and lo and behold, we got one pilot and a small warehouse in South Carolina.

None of us called back.

Speaker 1 (04:14.072)
moved over to a warehouse in Maryland. And next thing you know, we're kind of just growing.

It's got to be such a fun ride, but a terrifying one in hard tech because unlike software you're like, yeah, spool up the servers rent more AWS space. guys have to go scale production and support and your whole supply chain to meet that demand as you scale and that rate can be an exciting part of the journey.

The three things that you kind of think about with the hard tech, you got your hardware design. So does it fit for purpose? know, is it, is it the function, the form and the function? Then you got your software. Where is your data going to go? How are you going to organize it? know, multifamily, then you got to protect it, you know, from everybody hackers. And then you're going to be able to scale it. You got that. And then you have that on steroids when you're talking to a customer like Amazon, and then you have your firmware.

And then how do all those sensors talk to the processor that talks to the wifi?

customer's IT stack and get approval.

Speaker 1 (05:09.494)
Yeah, then you go through the information security view and they talk about pen testing and sock to audits and vulnerability tests. And you're like a startup going, what the hell did I just get into? I thought I was just building a piece of hardware.

It's incredible though, like you guys had to do that so fast to land a, I mean what probably the largest client, a dream client was your first one. I mean, what a story there, right?

It is the dream client and I think later on we'll go into kind of almost like the nightmare client as well.

of what scaling so fast means.

There's a double-edged sword. I'm really trying to choose who your first clients are. You never want to really cut your teeth on your dream client. You'd love to find the guy down the road. And we did. We were out of South Carolina, a lot of industry in South Carolina, kind of cut your teeth on, let people wear it. You know, one of the things that we do with a lot with bending and our wearable is on the waist. And so if you have a dad bod or a beer belly, the device automatically sits at an angle.

Speaker 1 (06:09.954)
So automatically it looks like the body is bending. And so how do you account for all these different bodies?

So like, no, this is where my device sits. We're going Delta from standing, but how do you detect standing versus sitting versus bending?

Yeah, standing, sitting, bending, walking, twisting. you know, we, we, you know, laying down, we hired a ton of Clemson students that modeled all this and taught, by hundreds, well, almost a thousand Clemson students that we modeled tons of different activities. And the problem you see with Clemson students or any kind of college students, they're pretty much in shape. You still don't, they don't quite have the dad bod yet.

They still get the high school, you know, coming out in the college, right?

And so all our models are like these guys and gals with 32 inch, 30 inch waist, 36 inch.

Speaker 2 (06:54.764)
Yeah, and then let's move a hummingbird.

And we get to the, you know, we get into the real world where you deal with 40 year olds, 45 year olds, 38 year olds. Yeah. They're not, if they're not as in shape and for, so you're kind of data set was off.

It's like a tree, right? The older gets the more rings it gets, expands outwards regularly.

And so luckily we were able to kind of just figure all that out with our models. We do use, and I hate to say the word AI, not to say that's a buzzword, but we had to use machine supervised machine learning, random forest to kind of predict what everybody does.

Well, and so we say you're using machine learning. You have a large data set and you need to find the patterns and you can give it true sources to learn patterns from. So yeah, machine learning. We know how it works. We know it can find the statistical likelihood of a thing happening because you gave it the right answer. You know, it's not the modern generative AI that is like black box. No one knows how the math works on the inside. It just does.

Speaker 1 (07:48.942)
Yeah, so it's exactly the way it works, Grant, dead on. And so we taught the model what a bend looks like, what a step looks like, what sitting down looks like. What does someone look like when you're driving on a piece of machinery? And that's basically the way the whole system works is there's a base set of movements that we've trained the model on. And then when an employee shows up to work, we know what's good and then what we know what's bad. then, you you have the ultimate problem of the dashboard.

Yeah, how do you use the data for good?

Yeah, how do you use the data for good? And of course, every single company wants to look at it a different way. And so then we learn, you know, APIs and, how do we just let them call up our metrics and design the dashboard the way we want. You know, we think about the black hole of startups sometimes. I think the black hole, one of the big things is IT costs. You can spend as much money as you want on IT costs. Really just on dashboard design.

Right.

Speaker 3 (08:47.15)
And why is that?

It's, it's every, every company is a glove. You got to think of them as a five finger glove and not a mitten. And they have their operations and they know how to run their operations and they run them really well. And you're now trying to come in there and show them new data that's never seen before.

into a workflow that they've got locked down in concrete for the last decade.

And they think they're good and they think all their employees work hard and they think they're all in compliance with all their movements and stuff like that. And we come in and show them that 80 % of the work gets done, you know, in 20 % of the time and, or, you know, items like this, that half of their operations does it wrong. And they're like, well, I'm not thinking this is that great.

saying.

Speaker 2 (09:32.895)
Right, and then how do we fix that?

And they almost don't even want to see that data potentially.

organization. Right? Like you, the executive level, like, no, no, no, it's all great. I don't, I don't hear anything bad. You know, that, you know, director level that actually cares about making efficiencies because they need to grow the business. their metric, you know, reporting up is need to affect change. And then you have the actual people on the floor that absolutely don't want big brother watching over their shoulder, changing what they do.

nailed it. Exactly. Yeah. The supervisors are saying, hey, I've run these people my whole life and I think I've done a great job. Yeah.

And I'm not gonna fight them. I'm not gonna go die on this hill.

Speaker 3 (10:09.568)
It kind of leads into something that we wanted to touch on in the podcast around like preventative help versus like after the problem has already happened. And dive into that a little bit for us.

Yeah, where in that stack do you get the buy-in for preventative and who fights back internally and then we can expand on who the actual payers are for these kind of equipment and how does this market work.

Yeah, so I mean, every time you build or buy something inside a company, everything's based upon an ROI. And so, you you think about the ROI, it's the expense over your capital that you spent on the product. And so for us,

cost of capital for how long it you to pay it back.

Yeah. And so they're actually even more sophisticated. They'll throw a cost of capital on you if they think a three, four five year return is needed to be able to pay for it versus monthly. You know, I I want my payback in three months. You know, and so you get in this kind of, Hey, you got to prove that the business case it. And it kind of like modern healthcare today, you know, everything's geared up to take care of the injury or take care of it after the fact.

Speaker 1 (11:13.506)
There's not a lot of leading indicators still in today's business to say, Hey, this employee is about to do something bad.

or has been.

things bad, out of compliance. We wonder why, you know, why these accidents are happening. And what we find out is companies are really struggling around preventative measures versus it's easy to pay for something once something happens.

That's because insurance exists. Hence your prior background.

Yeah. The next best offer and products like ours is insurance, which is I can pay $5 an hour on workers comp premium. It's, not my problem. It's AIG's problem. It's the Hartford's problems. It's a traveler's problem and they'll administer the claim. They'll pay for the pills, pay for the surgeries. And that's a whole different part of the company that I don't even have to worry about. And so that's kind of where the competition lies with us. But then we go back to the other problem that the supervisor is getting the new data.

Speaker 2 (11:46.818)
and it's suddenly not my problem.

Speaker 1 (12:08.302)
And say, Hey, how do I deal with this new data? How do I do that? And so there's lots of hurdles to overcome. when you, think about, you know, preventative today and our new product that we've just built out and is, you know, it's the, it's the collision avoidance system. And so this helps the, notifies the employee and the driver of a powered industrial truck, a crane, any type of equipment, not to get hit by it.

Yeah, or that they're coming around a corner. They're going to be close.

corners. That's beautiful. uses ultra wideband so it sees around corners a lot better than cameras because cameras only line the site. So if someone's coming from a blind, we can pick them up on the ultra wideband camera. Well, you we talked to customers and we did a slide that, you know, in the month of May, nine workers in America died from getting hit by forklifts. And you look at the stats and you say, okay, 95 people die a year. And then you just Google forklift deaths in May, new stories. Right. And they just pop out.

crazy

Speaker 1 (13:09.523)
every day everywhere you go and you're like huh now why wouldn't someone spend

This problem. Yeah

versus wait for the $3 to $5 million problem to happen to them. And not even the three to 5 million. It's the death. It's the PTSD of all the employees involved. What happens to the production, goes on visiting the families that I mean, it's

families.

Speaker 2 (13:31.246)
And the time it takes to implement your safety changes, because you have to act as an executive, as a CEO, you have a forklift death, you have to be seen as putting in changes in place after that happens. So even if they're effective, not effective, kind of doesn't matter. You're going to go through motions to change safety protocols and make a show of doing this, which takes time, takes effort, takes energy, not just on the floor, but all the way through your management stack.

And what's crazy is the questions we get, they're like, well, if we don't put it in, then what's going to happen? And you go, well, what could happen is that. And then what they're also concerned about, well, if my employees don't react, my supervision, my leadership don't react to the data. Am I more liable now? And you're like, really? You're like, wow. That is just a jaded view. Yeah.

Yeah

Speaker 1 (14:19.18)
That you're so worried about being smarter from the data versus knowing that the data exists and that these are issues. And we got to go correct them saying, I got the data, but I don't trust supervision leadership to actually act on it. And now I'm even more like, so you sit there in these hurdles and you're like going, wow, I never thought of that hurdle.

It's just the interesting parts of the sales process, right, that you never expect to come up against. It's like we're delivering you all the data and now I'm concerned that if I have the data, I'm more liable if I don't act on that data.

worst thing you want to see in your process is the lawyer in the room and you're going, I wonder what the lawyer is there for. You're going, that a... That's good. They're going to explain our contract or get our PO done really quick. And they're also like going, if we don't act on your data, you know, aren't we more liable?

Yeah, that's good.

Speaker 2 (15:12.238)
What's that decay? Are they afraid of like that this is the newest canary in the coal mine and you're gonna put the canary in the mine is gonna instantly pass out, right? That it's gonna show how bad they have been. Is that actually more of a shame and a fear that they're exhibiting the sales process that they're kind of afraid to look under the hood?

Yeah

Speaker 1 (15:30.53)
think sometimes it's better off just to be stupid.

I think that all the time about myself. I wouldn't it be nice to not have to worry about these things that I know are coming?

Exactly. It's like, why, why do I know what's going to happen when I see this? You know, you're like, damn it. just rather not be able to connect these dots together. so that's a, you know, the big challenge is just one of the challenges that I never thought we'd have to overcome is that in action of, you know, hard tech, of being able to produce so much data. You know, you think now what language learning models we talked about, what we use supervised, supervised. So we teach the models.

your training machine learning algorithm, because it really is when you produce it, it's an algorithm at the end of the day. It's linear algebra, taking inputs and outputs and waiting tables. And this table, when it does this, looks like sitting. This table, when you put the math in, comes out, looks like standing. It's all statistics just at a very large scale.

And now, now the system, so we thought about, know, the big IT suck and spend and you go, now we're getting rid of dashboards and the AI models just spit out. This is your answer. This is what you need to do. You don't have to interpret barcodes, plots anymore. This is your problem.

Speaker 2 (16:41.614)
see that hey your first shift employees are 45 % more likely to a strain injury we don't know why that's happening but it's happening on this shift.

to see is your first shift employees are 45 % more productive and your first shift supervisor has 6000 more steps than your second shift supervisor. Yeah. So he's walking by managing around, he's managing by walking around and he's getting stuff done and he's talking and that's why the productivity is. Yeah. It's kind of, we had a, we had a case with a forklift that said, well, the worst, the least amount of use forklift had the most incidents.

really off employee to human contact. And so we started asking them why and they said, that's the, that's the crap for cliff. No one likes driving it. And it, know, has bad tires, bad visibility, everything like that. And it's like, well, it has all of that for reason. And employees drive it like crap or they don't, they don't have the right visibility and everything else that's causing a heck of a lot of issues for you. So I don't know where we ended up on that question, but you know, I think companies with preventative and,

really kind of moving to preventing injuries, proactive data versus dealing with it after the fact kind of is the next.

step. Well, and diving into that, is like a mirror image to like the med tech industry, right? So for the medical devices we develop, the very first buyer is not insurance. The very first buyer is private, right? Someone who really wants this insert device here is going to pay for it out of pocket because it's not, you know, not reimbursable yet. And they're wealthy enough to just cash it out. You get those clients to give you enough clinical data and use data that you can then prove, hey, this device that costs money or treatment that costs money, preventing them from using opiates.

Speaker 2 (18:27.374)
because we fixed the problems that have band-aided it. you show all these cost savings over time because it's the spike in cost and then versus the integrated over time, low and steady. And you need enough data and stats to prove to the actuaries, digging back to the insurance guys, you need to feed the nerds actionable data. And all of sudden you see this magical moment happen in these medical devices when they truly get picked up by payers. And all of a sudden the end user isn't buying it anymore. It's like iPhones. iPhones took off.

because Apple didn't sell you and I an iPhone. AT &T paid Apple and you paid monthly to AT &T and all of a sudden we're all used to buying three and four hundred dollar smartphones in cash. Apple could sell a six or eight hundred dollar smartphone because you're willing to finance it. Without that we would have never jumped to that expensive of a device being as ubiquitous as it became. Medical devices the same way. The payer is your insurance agent and they know that hey I want to pay this one big cost.

and collect a little bit over time because it saves. I can make more margin in that. This is the I feel like the fight that you're in right. And what is the buyer for you guys? Can you get a G or a G or a G insurance company name here? Can you convince them to pay for this or subsidize it? Just like progressive with a safe car, you know, OBD two ports that measure your break and acceleration. Is this a market you can chase? Is this a buyer for you guys?

They definitely are. have a great partnership with the Hartford. But all insurance companies you said are waiting on actuarial proof. And you you think, well, that's eight quarters, two years, three, you know, 12, know, 12 quarters, three years, you know, most of those actuarial tables stretch out three to five to seven years to get their trends. I'm willing to pay into it. And so what we have to kind of really think about and the reason why we shifted to.

repetitive motion to collision avoidance with our system. In repetitive motion, we are chasing the little risk. The small repetitive motion injury with our wearable.

Speaker 2 (20:23.401)
a long time.

Speaker 2 (20:28.142)
and you have to be consistent for years to show that you avoided the injury.

Yeah. And we avoided the injuries and we changed behaviors. And so this has a haptic on it. It vibrates when the employee bends in a non-compliant manner. you know, we had to be careful how many times we actually vibrated them because yeah, or they're like Nora or it's just becoming background noise. so this chased, you know, eight to thousand, eight to $15,000 type of injuries. And, there's enough frequency there that somebody's willing to kind of look for an ROI.

for it.

Speaker 2 (20:58.296)
took years to see if it was going to prevent that exact injury like years for that injury to build up right as we talked earlier about you know the your college students training the model for all 30 inch weights and their health in their backs aren't bad yet but they would have to wear that into their 30s to not have a bad back in their late 30s to prove that your device worked versus the standard you know back injury that might occur in that same field well

There's a thing about there. There's a lot of industries that work that, you know, You know, have some pretty horrific data that shows how hard people work.

Are you guys in agriculture with that device? do. mean like fruit picking and produce would be brutal.

Yeah. So we actually started off in the fields of, you know, California. Yeah, exactly. They kind of get some real world. Yeah. Who are the hardest jobs? You don't want to work. mean, you got it. Any type of picking, but what we found out is in the pickers got smart. The pickers ended up walking down the, the Rose. They don't walk down. go on their knees. Who knew? Right. So they took the bend out of it. And so now they're, they're closer to the product that they're picking because they go down the aisle.

That's I was thinking.

Speaker 2 (21:41.954)
War's case scenario.

Speaker 1 (22:03.636)
and not, know, everybody has their way to kind of prevent the injury. so, you know, that was their accommodation was to go down the knees, but we chased the little R for so long. And that was the $15,000 injury. And then when we moved into collision avoidance, we chased the big R, big R meaning, you know, $5 million claim, shutting down production, a death, an amputation, crushing, something like that, where people go, yeah.

And now they have new injuries. Yeah.

Speaker 1 (22:33.406)
I don't need to wait two years, three years to say that this will happen. We know one in every 11 forklifts have some type of injury, really injury incident a year. Yeah. So 35,000 injuries a year from forklifts. and so the stats are saying one in 11 that a forklift will hit somebody. Some kind of damage, you know, and so there's a hundred deaths. So there's 35,000 injuries, a hundred deaths. those injuries can be anything from.

Yeah, do some kind of damage.

Speaker 1 (23:01.452)
you know, an amputation, crush or to basically the most of them are running over toes. Yep. kind of the, the pallet and you'll as the feet get too close, those type of things. And so we went after that, that big R risk. And so we got out of the ROI game.

Yeah, and it's the emotional risk. You're actually taking money on the table, but also putting into the bet your emotional risk. No one, everyone's yeah, everyone's back. It's hurt eventually if you're in manual labor. It's like cost of doing business.

aching back there's a reason why that phrase exists into existence not just because hey you know there's everybody everybody has an ache in

Yeah, but as an executive, a business owner, a manager, you're like, no, I never actually want to see an employee die. I would have to carry that emotional burden. This is much more than a financial matter at the moment. You can really sell emotionally, which is a great way to get someone to empathize with the, you know, the, R, you know, bad back. It's really hard to get someone to truly care. That's right. That's just suffering. I'm paying them to suffer like this is the job, but you're never paying someone to die. Yeah.

No one will ever forget that either. I was a chief operating officer, CEO of a natural gas utility. And I can remember the first time we had someone die on the job site and we're like, wow. And it wasn't from natural causes. Yeah, a bummer. know, but you're like, holy, how can we prevent that from ever happening again?

Speaker 2 (24:14.978)
You're like still a bummer. It was still.

Speaker 2 (24:21.728)
I couldn't live that this was my fault. This was hard enough that it happened organically.

If I had a PO on my desk that I could have prevented this, I would have paid it if I only knew.

It goes beyond. It goes beyond the business. It gets very personal immediately. Yeah. Right. And the other question I was going to ask was on the business case side. So you said you chased the like the smaller claims for a while and then you said OK we're going start going towards forklifts and it sounds like from one of our previous conversations that it's really whenever you guys started to see some some good adoption from those companies. What was sort of that like decision making matrix where you made that pivot. I think that in software pivoting is

is difficult, but I think that in hardware it's like you have to go on this brand new journey potentially. So I'm just curious like what that what that really looks

Yeah, and how did that fit in the timeline of the story of the company?

Speaker 1 (25:08.908)
to fit all this into the time.

Back at Amazon and you're scaling, what led to the pivot?

And so, you know, you read the book habits and you go, know, for breeze got out there and they said, you know, who am I going to sell to? And everybody says, oh, you'll sell to the smokers and the people own cats, you know, the litter box, the litter box. And what they found out was that people that were buying for breeze was buying it for the new house. They get the people that really kind of clean freaks and.

If you're a smoker or a cat litter box, you've been living with smells forever.

You heard it. Nose blind. They're in their own commercial. So we made the mistake of chasing bad companies or companies that didn't really have great safety records. And what we had to learn was we needed to chase companies that were really good at safety. That cared. That had the culture around safety. That had the culture around business process improvement, innovation, utilizing tech, had ways to roll out tech, raise the rod hardware.

Speaker 2 (26:12.918)
And you had an evangelist that cared in this culture. Yes. You had evangelists to help bring you into the fold.

Yeah. And so we went down, we made the first mistake of chasing bad companies.

you they had the most risk and you could help them the most.

Yep. Lots of injuries, prevent a lot of injuries. Boom. And so, you know, you know, that kind of leads you to Amazon. They're in the paper all the time with their injuries and you go, great. We got the, we got the, you know, the poster child, but there was so much to the sale and so much to everything. It's just not, do you have a lot of injuries that we can provide? Or do you have whatever your problem is? There's the culture around acceptance. There's

You know, technology adoption is the scalability of not only you, but can they scale with you?

Speaker 2 (26:57.486)
And how big are they? Because if they're so big, the scale might be so hard to join. Yeah, it's the right size client for where you guys are in process.

We were definitely not the right size. Um, you know, we, we basically, you know, became, uh, one horse pony. Yeah. One trick pony. Yeah. You got the Walmart climate. I mean, if you're a fan.

Do you get the Walmart client?

Speaker 2 (27:21.555)
is that we should rename the rule.

Yeah, it's you know, you if I had to give any advice to a startup founder is, you know, choose carefully your first client sets. You know, you cannot you can definitely we hit it when you're you know, your your wife is smoking hot and you're the ugly guy. You can definitely out hit it or whatever. I'll kick your coverage. You you can out kick your coverage. You're hitting above your weight.

Thank you.

Speaker 2 (27:47.808)
Yeah, I I internalize this because when my wife and I go grocery shopping, they put the divider between us. I know I know I've.

You know exactly, no, sorry.

I'm not you. So yes, it's that the other adage is like, you you never want all your eggs in one basket, right? It's fit of a client. And also, even if they're a great fit, are they healthy for you?

probably the largest industrial wearable company at that point in time overnight. went from nine employees to 50 employees in like three months. now the next, you know, four months, the next bit of advice is hire HR person first. Right. Because you're willing to hire anybody.

Over. Yep.

Speaker 2 (28:29.966)
cannot hire this guy. Now, if you're HR person, you need that great filter.

Exactly, because all you're seeing is how late all your employees are working and how much you're burning them out. Yeah, they're like, no, this is going to cause you so much problems.

So you hit Amazon and it's going great. How does it pivot? you know, what is the yeah.

Our what happens, and I think you see this all in the wearable world is that employee adoption. It's not that the devices don't work is how can you get them to wear it so they can work? Right. And, know, you know, some people go it's form and function. Some people will say, Hey, you know, it's no matter what you're monitoring me, you're tracking me, there's big brothers. And we had to go to the decision to says, how do we create mandatory wear of our.

Because without mandatory wear, we're always going to struggle without a firm mandate from the leadership that says you shall wear them. And buy in from the supervisors. We're giving them new data that doesn't say that they're doing a good job. Yeah. How do you protect them so that you're still there? You're there evangelizing for you saying this is something that we got to do.

Speaker 2 (29:28.189)
and buy-in from the supervisor.

Speaker 2 (29:35.342)
How do you protect them?

Speaker 3 (29:41.536)
And why do those employees, like, why was there resistance there?

Well, I don't everybody, if it's kind of like driving, um, I'll put on my insurance hat here. If you ask everybody, everybody thinks they're a good driver. Now you're a good driver. Everybody's going to say I'm a good driver. I'm a good driver. And yet, you know, no, there's a scale one to 10, you know, where everybody fits in the, in the driving. And I can tell you, my kids are terrible drivers. If you ask them, yeah. they're 27, 25 and 21. We have about six or seven accidents.

do it every day, of course I

Speaker 3 (30:10.542)
cars now right?

Speaker 1 (30:16.684)
And yet they're not good drivers. But everybody thinks they're a hardworking employee. Everybody thinks that they're putting in the effort and that they're safe.

And that they're They're safe as they can be. They're more productive if they're not safe maybe. And they pride themselves on that. Yeah.

And we can create metrics that show you, are you a hard worker, but you cut corners? Are you a hard worker and a safe worker? Are you just not a hard worker? And the worst box, you're not a hard worker and you cut corners. And employees, you I wouldn't necessarily care for that. And so you kind of understand the resistance. And so one of the big things we kind of try to tell companies is you can't use this data for harm. You're using it to train, to bring people up, to improve, to get better.

not for their employee evaluations, but people just can't help it. They see that negative data and they just can't help themselves and say,

your data doesn't allow that, the camera systems is used for productivity and that's where they get the productivity data.

Speaker 1 (31:17.91)
yeah, that's the problem. That camera right there. And so we have to over, that's probably one of the biggest hurdles to overcome with employees is that this, companies here are going to use it so you can hold your kids when you're 50 years old without back problems. And this is going to help you for the longterm. And once we were seeing kind of this

trend of, know, Hey, I can't get my employees to wear it all the time. can only get X percent. go, got to figure out a way to get it to mandatory wear. And then one of an automotive supplier came to us and said, they just killed someone with a forklift.

was a like pivotal moment to say, we have to do this now. We lost Bob in memory of Bob. have to do this.

to find a solution. And then we're in a pivotal moment of the company is we lost our Amazon contract on this kind of wear issue and saying, we're coming off the deep dive of lessons learned. What can we do differently? What can we, how can we address this? And so we got to get mandatory wear. Low and behold, this automotive supplier comes to us. lost Bob and we say, wow, if we could design a wearable, there's mandatory wear. And we have all this great

data around repetitive motion. We don't need to lose that. We can still hold on to our past and cause the companies want that they know it works. But you know, how can I create that mandatory wear that, that requires the wear so I can get the improvements and repetitive motion and I can stop people from getting hit by forklifts. And that's what we set off to design when the supplier came to us and said, we had a forklift accident and can you help us?

Speaker 2 (32:38.413)
forward.

Speaker 2 (32:58.712)
God, that's awesome. So you had a client come to you with a problem that also helped you get over the friction of sales. They were so emotionally ready to move because of this event that had happened and how sad and terrible it is. You guys now have they're a ready buyer. Right. This is down. This is your camp. Like there's a difference between trying to convince someone to buy a thing they don't need and finding a ready buyer. Right. That they want this thing right now. And like we like alike and like doing business development for Glassport is like being a good real estate agent. You know, this is your term. So it's, know,

Not everyone's looking to buy a house right now, but you want to be the realtor they call when they're ready to buy.

You want to be right there. And we worked with this company before on the repetitive motion side for their new employees. And they were like, yeah, we love your product. we only do it for new employees cause we can't get our legacy employees. And, but, you know, is there a way you could do this? And so we went ahead and tested RFID, Bluetooth, using wifi signal.

Sure.

Speaker 2 (33:55.918)
That had to be the wifi one had to be a total boondoggle. That would be so crazy.

You know, trying to predict how far somebody is away by the signal. It's just crazy. And so we did all that and we, settled on a ultra wide band.

UWE is incredible at what it does.

Yeah. And there's a reason the Apple picked it for the air tag and that. And so we, we went ahead and did the research on UWB. We settled on that and said what it would take to put an ultra wideband sensor chip in our hardware. lo and behold, we did all the research and the work and we had a client that was willing to work with us. They had autonomous vehicles. We were able to put it on their autonomous vehicle. Yeah, that's, yeah, we had to do that kind of stuff. Make sure there's no co-interference. And then with their forklifts and lo and behold, you know,

integrate with their control system.

Speaker 1 (34:44.247)
Companies are like, you can protect my autonomous vehicles? Like, yeah, but we can also protect...

It is just an incredible story of like pivoting and finding that product market fit I mean from starting off on at Amazon and having to explore this company and no HR person we need to hire like crazy and trying to deliver to the Walmart or Amazon client and figuring out okay We can't get any adoption on the side of the workers and then having the opportunity to say hey How can we get make it required you find a unique angle with the forklifts the actual machinery where?

They have to wear the device because they have to make sure that they don't hit the machinery or the machinery hits them and boom.

Yeah, that's exactly the story.

And how long did that actually take? It sounds really good. that was great. It was a 45 minute podcast. It didn't take 45 minutes, I'm sure.

Speaker 1 (35:31.894)
No, no, you go, you know, you think about, I said nine years, sorry, anniversary. first three years is to figure out the wearable. The next three years were dark cause of COVID. then the next three years was this post Amazon retooling. What are we going to do next? In the meantime, you're doing capital raises, convincing people.

just how did you survive through the three different, you know, life stages so far in the business? Yeah, it's your venture back to the beginning. Is that correct? Okay. So you guys personal capital personal back like privately funded. Okay. And then you get to this, you know, the Amazon scale. So you start, do you raise to do that or is that

back by himself.

Speaker 1 (36:01.208)
first couple years.

Speaker 1 (36:07.168)
no, now you're like, I don't want anybody's money.

We got the biggest client ever over here

We want dilution now. Come on. This is winning. Of course you want to invest now. We're going to hold on to our cap table percentages. so, we took some money, obviously Amazon and the Industrial Innovation Fund investors and that's a public knowledge out there. And so we took their money and then had a little bit of a round just to make sure we can scale. Okay. And then, we lost, so to speak, the Amazon deal.

Yeah, the big client. The big So you can track.

So we have to contract and now we got to tell a story all over again and then you got to tell the story and you have to say the H word out loud which is hardware and say yep we're a hardware company but Grant you're telling me hardware is the new thing

Speaker 2 (36:58.252)
It is. It's the it's this thing that SAS got really big early on, right? When Apple and Android came out and you had hardware in people's pockets that no company had to develop because these behemoths did. You had the SAS explosion of everything you can do in SAS and then you had the boom at home of an at home IoT. Your Nest thermostats, your smart door locks, your inserts smart things here and that got huge. And now we're seeing this explosion of that hardware bridge.

Cause really you're a software company. You sell data and you manipulate data to make software choices to enable real world outcomes outside of your hardware. Your hardware is your necessary evil to be the bridge of that. And that's, you know, we see it starting to really infuse into med device, into industrial and safety. Um, because you know, you guys have needs that the iPhone can't fix, right? The iPhone is a general purpose tool.

Exactly right.

Speaker 1 (37:49.494)
times I've heard, well can't the iPhone do that? I'm like,

Right.

you've gotten a great proof of concept prototype built on iPhone probably over a weekend.

And you can make it look, this is what it's going to work like, but I need a device that is rugged, robust, industrial, easy to use, and not a personal device. And that's how it works. And this is that whole story of the necessary evil of hard tech to make a SaaS company work these days. Because SaaS by itself isn't cool anymore, because if you're just software, AI is going take your lunch anyways. So this is kind of why we see this resurgence of hard tech in the venture community here in the Midwest.

That's awesome. So I'm in out in Seattle. So they haven't got that memo yet. Yeah. So, you know, they're still saying SAS, SAS, SAS, but, know, we just finished our last round. So we were able to raise and so we just finished our last round. But, you know, it's a it's a lot of work for.

Speaker 1 (38:44.962)
hard tech guys with software. we were kind of 50 50. We are revenue is 50 percent hardware, 50 percent software. And of course, over time, you don't buy hardware anymore. So the five years that you're advertising your hardware out, you're just getting software revenue. But as startups, you're always selling. There's always more clients. And so the hardware mix is always looking like you're a big hardware mix versus the software mix. And then as you're saying, the hardware guys, they actually produce the data.

That's right.

Speaker 2 (39:12.994)
Yes, it's the goose that lays the egg.

And they're like, wait a minute, is the data, value of the company, software subscription, the value of the company, or the fact that we have, you know, three or four products out there that are hardware based that we can sell into.

and that are sticky and then once the clients adopted it, it's not cause fallacy. We already own this hardware, we have to use this system.

And then you see that most VCs were like, well, they're not, I don't want to say sophisticated, but they're very single-minded in their risk appetite.

just ask them, you can probably pivot your pitch to who you're talking to. To certain VCs you put on, am a SaaS hat, have this necessary evil hardware to worry about that, we craft code, SaaS is what we really do. And then you talk to the guys that are in hard tech that want that sticky factor that to prove you're a sales process can get them to buy into hardware, which means you installed it and they're never leaving.

Speaker 1 (39:59.886)
Yeah, great. I need your Rolodex, man. Yeah, my Rolodex is all the the sats guys are like, Oh, do you really have to have that hardware? Yeah. You know, isn't there some company out there? You can just have them build your hardware for you. I'm like, right. Yeah, that model doesn't feel that good to me.

It's not a shocker to me at all that you're able to raise. I mean, I think just hearing your story on the evolution, obviously your pedigree and your background as well, to where you've gotten the company today. I even at the later stages, as much as it does become a spreadsheet game once you get to the A and beyond, it's still about betting on that founder and their ability to iterate and pivot over time. I feel like throughout this entire conversation, that's all I've heard. And it's just been like, just well done. mean, it's just.

One day someone's going to say, Eric, you're to have to stop pivoting and find your niche. we actually, we added 21 new customers in the first quarter. It was our best quarter. And so with this major pivot, we also pivoted our, you know, our distribution sales strategy as well, away from kind of the insurance companies and using a different channel. So, but yeah, it's been a nice pivot for us. Hardware is,

Hahaha

Speaker 1 (41:10.358)
I love it. You know, I'm a mechanical engineer. I love the tour I got today. And I'm like, you've got this. Where's your, you know, you have a sewing machine. You have your laser engravers, you have your, you know, all your, 3d printers. And so, you know, I can really appreciate what you guys have here. Cause we have a small, small version of this in our own place, just to be able to prototype fast. And, but when you go to, you know, sand point road,

people don't want to talk about my 3d printers, my engravers. want to, you know, let's, you know, what's my offshore to onshore software engineering, expense and those types of things. So that's the big, you know, the big challenge. And so we, we keep firmware in house. do our firmware are, we actually moved our software engineering in house, but we were pretty much dominated offshore software engineering for the first six years of our.

embedded software or just the upper the upscale software like the higher end stack.

Yeah, everything for us.

was off and then you onshore your firmware for you and the internal or just onshore.

Speaker 1 (42:18.166)
No, it's internal. Yeah. So we've built it all on bare metal. you know, so we actually don't build on anybody's platform. It's our own code. or quick tell. Yep. blah, blah,

What are you building on?

Speaker 2 (42:30.542)
didn't know what microcontroller you guys using.

Speaker 3 (42:35.502)
you

Speaker 3 (42:41.088)
Everybody listening can also sign the NDA, right?

Speaker 2 (42:49.912)
because it's one of these stories in hard tech that, you know, if you talk to a SaaS founder, they know software is never done. They're never going to able to turn down their software development team because you're always providing updates. It's always doing that. And in hard tech, used to be you could just go launch a product and that was it. Right. So some sustaining in manufacturing, but you didn't have to develop new things. Once you started connecting to the internet, security, safety, things like that. Now you need that embedded software or firmware team to always provide safety and software updates.

That's I think the thing that people are starting to learn in hard tech.

You can, mean, the way we get pushed all the time to go, just use third party hardware. You just use third party hardware. Why do you build your own hardware? And I could see a world where we use third party hardware to do what we do, but we have to be able to control the firmware. The firmware.

is really where the customer meets the company. How do we communicate their needs and demands, their business features, whatever they want done is not out of the cloud. It's really what's happening on the shop floor or right there at the point of the device. And being able to control the firmware is really important. And these third party hardware guys don't let you have access to the firm.

be too many cats in the kitchen.

Speaker 1 (44:02.67)
Yeah, everybody's going to be, know, and so, you know, what are you going to do with it? Well, you know, and so we have to control the firmware to really kind of deliver anything from a warehouse operation to a farm, to a manufacturing. They all have different types of demands that we have to get going on. And so that's why we keep firmware as ourself because it does provide the fingers to that glove that we need.

It's part of your sales process, right? You can say, actually can change that for you. It's me. It's not any of my vendors. It is me. I can change that.

can change that parameter you need. So for our world, hey, I got a 15 mile per hour forklift. I got three mile per hour forklift. Totally different response times out there, totally different halo sizes, everything else. I got to be able to customize all that for them and do that. So that's kind of probably one of our value adds. Now, how scalable is that? We haven't hit that question yet. You have 5,000 customers, 10,000 customers.

You'll figure it out along the way. The next peak, whenever you get to scale it and you realize, okay, well, we could probably go here and do this and then we can probably figure it out that way.

And then your operator can look at your, you know, look at all of your expenses versus your revenue. Like we got to drop the clients that make us do this that are below this number because they'll

Speaker 1 (45:15.694)
I realize it's your biggest clients.

If the number is red it's bad, numbers green it's good. So here are the green numbers, we keep those. And the red ones, we go find a way to pivot and fix.

So you figured it out along the way is one of my favorite things to say. And one thing leads to the other. Yep. Always. You never know the next innovation. You just got to stay in the game.

Build the plane while you're flying it.

In all ways.

Speaker 2 (45:38.274)
And you couldn't sat down in a boardroom and predicted the path that you're on.

No way. You're exactly right. In no way would I've ever said we went from here to this pivot to this pivot to over here because we were solving a whole bunch of different problems along the way. So that one thing leads to the other. You got to have the one thing. If you don't have the one thing, you can't go to the other.

I need you to help me. we're talking to new clients, like, why can't you tell me how long, how much to like the dollar? Like you've been doing this for a decade. You shouldn't be able to tell me how much. I was like, I can't guess this within any amount of certainty. No one knows what's going to happen tomorrow and nude product or hard deck or what your customers are going to ask the moment we go trial it, you know, an alpha prototype at your first potential customer shop. They're going to ask me to change probably your entire product.

it happens all the time. And then of course the sales team so excited.

and they are beating down the doors of the

Speaker 1 (46:26.83)
got one for you, I got one for you. But that's not what we do at all.

Exactly.

My favorite phrase, if you could just, if you guys could just...

Yeah, that's what you love the sales guys. I hope we could just do this in your

big client or this, new deal insight on if you could show.

Speaker 1 (46:43.022)
Yeah, yeah, so that's kind of one of our big challenges out there, but I love that, you know, one thing leads to the other and you we got to have you got to have something to build from and for us, you know, our story about starting on the employee side and building out this repetitive motion models and everything else really differentiated us in the market now for inclusion avoidance because our company, our products are from the employee point of view. Now, how do I keep the employees safe?

And our competitors products are about the forklift point of view or the powered industrial truck point of view. How do I stop it from hitting someone? Two different tiling ways to kind of solve the problem. We're trying to protect the employee from all types of injuries. They're only trying to protect it from one. And that's when we go into our sales mode and we, as I'm doing right here on the call, that's really what it's our strategic differentiation out there in the marketplace is that we just put a halo.

around that employee around from forklift collisions to their industrial, repetitive motion problems. And if they pass out on the job or have a heart attack on the job, they fall on the floor. You can learn on that as well. they're having a light, your life exactly. They can press the button. I hope I'm falling or I'm having a problem.

you can alert on that.

Your life alert.

Speaker 2 (48:01.816)
piece of machinery, I've hit the E stop but I can't get out.

Yeah, they can do all that with ours. it really takes, puts that employee.

and you actually have decent location on them. that's what I'm You really can direct emergency people to the right place.

can get down to,

Speaker 1 (48:15.182)
I can triangulate it right there and help them out tremendously.

One thing leads to another. And that's where we'll end the podcast. It's absolutely fantastic. Eric, thank you so much for coming in. I was super glad it worked out. Everybody, this is the Hard Tech Podcast with Eric Martinez, CEO of Module, Deandre, and Grant. See you guys next week.

Thanks everybody. Take care.

Thanks guys.