Transcript was automatically generated.

Frank Curzio 00:01

How’s it going out there? It’s Tuesday, April 21st. I’m Frank Curzio. You’re watching the Wall Street Unplugged podcast.

Frank Curzio 00:05

We’re breaking down headlines and tell you what’s really moving these markets. So I have an awesome interview set up for you today. It’s with Jason Hein, who’s a co-founder and chief technical officer of a company called Telescope Innovations. Telescope is a remarkable company.

Frank Curzio 00:26

It builds robotic systems called self-driving labs for the largest pharmaceutical companies in the world and uses AI to analyze these results. So in short, they’re able to use these robotic systems to cut down the time of drug discovery from 10 to 12 years to just 5 while cutting the cost of production for these costs through clinical phase one,

Frank Curzio 00:47

phase two, phase three, then FDA approval, which costs around $2 billion by 75%. Now, there’s a lot of companies that say they do this. We even have one in their portfolio right now that, that’s, that’s doing it. Uh, but this is a $22 million market cap company that just sold its second robotic system to Pfizer.

Frank Curzio 01:08

Second. A lot of these large pharmaceutical companies, if you know the industry, try lots of products out for the first time, and they say, “Okay, we’ll try it. We’ll see how it is.” I mean, you talk about multi-billion dollar giants. Some of them is, uh, when you look at Eli, it is almost a trillion dollar company these days, right? Th-these pharmaceuticals are getting bigger and bigger, the largest. And they tried these products.

Frank Curzio 01:26

For Pfizer to buy two of these and buy its second one means that they’re impressed that it’s working. And it’s working because it saves them a shitload of money. Uh, and it allows for more drugs to, uh, compounds to be discovered, right? It also provides a system where usually you have and, and Jason’s gonna talk about this in the interview.

Frank Curzio 01:45

You have a bunch of people that are working on this, and it replaces them. So you don’t have to deal with, you know, uh, certain hours of the day that companies are working where these, you know, the robotic systems and, and, and the self-driving labs are going 24/7. You don’t have to worry about healthcare costs. You don’t have to worry about, you know, craziness with their HR department. Uh, so these things are nonstop, and it saves a lot of money.

Frank Curzio 02:05

And also, you’re throwing AI into the fold, and it’s analyzing these results, showing, like, what’s the best way to bring these drugs to discovery and the compounds, which millions of compounds are sitting in labs and sitting on the shelves, uh, at so many of these large pharmaceutical companies because it costs so much. And if you’re wrong in phase two, right, and you spend it, it’s a billion dollars.

Frank Curzio 02:23

If you’re wrong in phase three and your data comes back terrible where they have to just shut, shut off production and shut off everything, uh, you see stocks go down 80, 90%. So, you know, you have this costly process where they’re looking for guarantees to fill in their patent, all the drugs that they’re expiring from their patents, uh, a-instead of, you know, having multiple shots on goal.

Frank Curzio 02:43

And this is a company that, that fills that gap. Now, when you look at Telescope, they have partnerships right now with Genentech, Amgen, AstraZeneca, Merck, uh, Merck, Bristol-Myers, and Roche, which is insane for a small company. Even crazier, Telescope has generated $4.3 million in revenue this year.

Frank Curzio 03:03

Okay, it’s a $22 million market cap company. Uh, nobody’s covering this name. And I personally met Jason at his lab and his classroom in University of British Columbia. This is in Vancouver. And after that, we decided to, to sign an agreement. And Telescope is now part of our marketing consulting division, which is growing tremendously.

Frank Curzio 03:24

And I have received lots of questions saying, “Frank, is this a conflict of interest when I do this?” And it’s not a conflict of interest. First of all, we’re only working with great companies, great companies that I put my own money behind. Uh, second of all, if you look at the marketing, this division, uh,

Frank Curzio 03:42

and if you look at this industry, is really a crappy industry. Uh, there’s companies that hire firms to, you know, build up, you know, brands and try to get their stock higher because they have warrants that are gonna expire. Uh, and they wanna get them exercised because they wanna raise money. And being an analyst first for 30 years and marketing, you know,

Frank Curzio 04:01

second, I see this a mile away, and I tell these companies to go, “You know what?” themselves because I know exactly why they want their stock higher. This isn’t the companies that we’re working with. And this division’s on fire because so many companies and small companies, even like ourselves, they wanna grow their brands. They have innovative products. They don’t understand the marketing, you know, especially when you talk to scientists and chemists and engineers and people.

Frank Curzio 04:22

They, they don’t understand the marketing of what shareholders really wanna see, how they build stories. And we’ve been doing this our whole entire career, watching others make so much money off of this and, and people saying, “CEO St. Frank, you do so much more for us than all these other companies that do a crappy job. You know, you guys should actually create this division,” which we created now for two years ago.

Frank Curzio 04:41

And it’s by far our fastest growing division because we only work with good companies. A lot of other marketing companies are just gonna accept the check. They don’t care. We care because our reputation’s behind this. So no, it’s not a conflict of interest, especially when we look at companies exactly like this where Jason is remarkable. You’re gonna see an unbelievable superstar management team coming together for such a small company. They have great partnerships.

Frank Curzio 05:01

Uh, check the box on innovation. Holy cow. I mean, in the right sector, AI as well a-as robotics. Uh, and you’re gonna see the incredible growth opportunity right after you listen to this interview. And let’s get to it now with Jason Hein. Here is that interview right now. Jason Hein, thanks so much for joining us on Wall Street Unplugged.

Jason Hein 05:21

Good to see you. Thanks, thanks for having me today.

Frank Curzio 05:23

So CTO and founder of Telescope Innovations. Uh, it was really great to meet you in person. I have a friend that said, “Hey, you gotta meet this guy. You gotta meet this company. It’s incredible. It’s robotics. It’s AI. It’s chemicals. It’s, you know, technology.” And I said, “It’s right up my alley. Something that I love.” And you were nice enough to meet me in person in Vancouver.

Frank Curzio 05:44

It was at your lab, which is located at University of British Columbia, which you said is the greatest college ever in Canada. We’ll leave it there.

Jason Hein 05:51

That’s right.

Frank Curzio 05:52

Which is awesome. Uh, let’s get right in here because, uh, I, I know when you look at your company and even on your website, describe you as a chemical technology company, but man, it’s so much more when it comes into robotics and AI. Let’s start there and, and explain this company and your motivation to start it.

Jason Hein 06:10

Absolutely. Well, so, you know, where this motivation for me starts, I’ve always I’ve been a chemist and a geek at heart in that space. The if you look at any major problem we’re dealing with right now, uh, making something, making a molecule, it doesn’t matter if it’s a drug, it’s a battery material, solar technology, whatever, building something matters.

Jason Hein 06:28

And that’s what got me into being a process chemist. I was I was taken by that. That process, building something, is 50, 100 different, uh, disciplines all in the same space at the same time. Automation has been the key way that my lab works on this. So that’s where we bring in robotics. The problem is robotics need to be smart. And what we’ve seen with the pivot of,

Jason Hein 06:48

uh, uh, new robotics coming online, uh, the, the current injection in AI, it just means that all those can finally bring together at the same time to really make major impact in the world. And that’s things like drug discovery, energy technology, all the above, right?

Jason Hein 07:02

And, and the real exciting piece, uh, was finding an ability to take what I was doing in my research lab at University of British Columbia and translate it to real-world application. That’s where the startup had to exist because, uh, all the deployments we’re doing need a full-time dedicated team that’s actually turning this into real-life, uh, application.

Frank Curzio 07:24

Now, when I went to go visit you, I, I think I might have annoyed you because I love what you do. And I asked you, like, a million questions. And you’re probably like, and he was like, you’re probably because for me, I was just so fascinated because thi what you’re doing with this company, I’m so used to.

Jason Hein 07:36

It’s, it’s great having like, sorry, sorry. There’s just, like, having, having somebody that’s as enthusiastic as I am about this is, is fantastic, honestly. So it’s really I, I, I enjoy it. Apologies, love. But yeah, absolutely.

Frank Curzio 07:50

No, it’s really it’s really cool because enthusiasm came from when you hear companies say, “This is what we’re going to do,” compared to saying, “Hey, this is what we’re doing now.” I wanna start off with self-driving labs because self-driving is a word that people think, “Okay, EV cars and stuff like that.” Your self-driving labs has to do with robotics. And you had this working when I was there, which was incredible.

Frank Curzio 08:09

And I, I didn’t know you were this far along. And then we really got into it. And I said, “Holy cow.” I mean, I, I, I just I, I couldn’t believe, like, your, your partners, which we’ll get to in a second, but let’s talk about the technology, self-driving labs, a-a-and, you know, what exactly does this do? How does it benefit, you know, big pharma companies by, by using your technology?

Jason Hein 08:27

No, completely. And again, I think that’s one of the fun parts about this space. Like, I’m, I’m one of the guys that helped to help to, to define that part. So a team of us, we’re actually called together to build the concept was, “We’ve gotta make major changes in the world, uh, climate change, you know, response to the pandemic. We don’t have enough time to actually do that.

Jason Hein 08:46

Is there a technology out there that could potentially help us go faster?” This was back in 2027, 2016, sorry, 2016, 2017. And that’s where this, this overall concept of maybe there’s a fusion where a robot could start making decisions in real time about what experiment had to get done. So instead of just don’t it’s monkeys and typewriters is kind of normal automation.

Jason Hein 09:07

You’re just doing more. That’s higher, higher density of information. But what we’re adding, and this is where the self-driving lab comes in, imagine you had a Tesla, and you can program your Tesla to drive with the wheels straight and turn at this corner. Like, it’s pretty easy to do a, a, a, a script that the Tesla follows. What you want is a Tesla that’s gonna break when grandma’s crossing the street and, oh, there’s construction.

Jason Hein 09:28

It has to adapt in real time to the problems that you’re seeing. And that’s really the same concept we’ve done with this research and development. So take a company like Pfizer. They have a mandate. They’ve got they have to respond to a global health crisis, whatever. That has to happen where it’s human investment. And you need to make the right decision at the right time, um, to, to hit your goal.

Jason Hein 09:49

We’re everybody in this space, pharma, whatever. We’re dealing with, uh, tighter timelines, tighter budget. We have to deliver with more, more higher delivery, less material, less money to actually do it. So if you had, uh, a robotic assistant that knew based on that last experiment, this is absolutely the next experiment I need to do, you’re not waiting for,

Jason Hein 10:09

“Hey, I’m waiting for this experiment to do. Then we gotta go think about it. I have to go to this meeting. I need to train these other people.” The robot is in the lab constantly clicking along and doing the right experiment that was based on whatever, uh, you’ve designed it for, right? You’ve sent it on a mission. You’re designing it towards a target. This is where it needs to go. And it’s making those decisions to figure out how to get there.

Jason Hein 10:30

That just means time compression. You know, you’re embedding all that institutional knowledge that would normally be across 50, 60 different people. You’ve got the best assistant in the world as physical AI, right?

Frank Curzio 10:42

So, uh, this is gonna be so much fun for you right now. Explain this. Okay? So this is when you look at, like, robotics, right? They think of Optimus maybe in a robot, like, shaking your hand as a person. These are robotic arms. Talk about what this system, what’s it replacing? Why is it such a big deal? Because people look at this picture and be like, “What’s going on?” I saw it in person, which I was blown away by. But, but explain what’s going on here.

Jason Hein 11:05

So what this is, is those two blue and gray ones up front, yeah, those are robotic arms. They’re the manipulators, right? They’re moving around things like files, powders, liquids. And they’re doing the actual sort of point by point. But they’re also interacting with the same equipment that, um, a chemist would work with too. So, uh, a balancing can add a certain powder, liquid handling, all those different steps.

Jason Hein 11:26

So this right here is kind of the factory version. And, and the analogy I like to do is, organic chemistry is a lot like cooking. So this is the robotic kitchen, effectively. Up front, the one that’s kind of closer to you, the little one that’s in the bottom, that one’s the, the, the sous chef. Its job is to go through and say, “Look, hey, big chef, you wanna set up this meal?

Jason Hein 11:46

Well, I’m gonna cut up your, your dice your vegetables, get things ready.” It’s doing all the sort of stuff that you’d need to do for the real experiments happening in the back. So they work as a tandem pair. Front one’s job is to get experiments ready to go, pass those off. The one in the back then picks it up, actually adds it to a reactor, does the chemistry, monitors the chemistry, hands it over, analyzes it.

Jason Hein 12:08

So this thing basically represents what a team of four to five process chemists would be able to do. But it doesn’t sleep. As long as the consumables are up, it keeps grinding through that part. You know, a simple part. If you’re having to study a reaction, imagine again you’re cooking. You sit everything together, and you’re making a soufflé. And that takes 12, 13 hours of time.

Jason Hein 12:28

During that time where that’s happening, if that finishes at midnight, well, then you’re coming back to take it out of the oven. And this is where a system like this will kick off that next step no matter what time of day that happens to be. So in addition to the whole self-driving part of it, a big chunk of what we capture here is evenings, weekends, 24/7 operation, cloud operation.

Jason Hein 12:49

That picture is actually our installation in Seoul. Routinely, we dial into that from here in Vancouver to do updates and maintenance, which means I don’t even need to be in Seoul in order to do chemistry in Seoul.

Frank Curzio 13:02

You know, bringing this into real world so people could understand it, right? Because you’re looking at this whole robotics picture, and it’s amazing. But, you know, and people heard me talk about this. And this is why, you know, I’ve been talking about this for a while when it comes to AI. Uh, I want you to talk about this which is in your presentation, which I know already because when it comes to these companies, they have, you know,

Frank Curzio 13:20

massive, you know, amount of shots on goal, which there’s a costly process, right? You have the patents, which are 20 years. A lot of these drugs, you say drug development right here, timeline in years is like 10 years. Uh, it’s on average, it’s usually 12. Uh, you’re looking at $2 billion in cost. And you wonder why these drugs come out, and they’re so expensive at the beginning because 12 years,

Frank Curzio 13:41

you know, you only have 8 years to really sell them. Sometimes they come out 13, 14 years.

Jason Hein 13:45

Yeah. Absolutely.

Frank Curzio 13:45

This process is absolutely amazing because you’re saying accelerate the time from lab to market by 10 to 100X and reducing cost tremendously and bringing drugs to the market more. Explain exactly what this means because this is more than just you and your stock and your technology. This is real-world stuff that could save people’s lives.

Frank Curzio 14:06

This is stuff that’s gonna be a game changer in healthcare, right? And explain that part, which, which, you know, I’m fascinated. I get the chills talking about.

Jason Hein 14:13

Well, it’s three things. Like, number one, like you said, look, the process that we do right now means that the timeline from I discovered the molecule to it’s actually out in patients is, is huge. And if you look now, most of the failures that, uh, drugs go up on, it’s at that phase two, phase three, just before it actually reaches, you know, clinical deployment.

Jason Hein 14:34

Something goes wrong. It’s not the right molecule. You’ve invested all that time and money into it, and the molecule’s dead, which means every molecule that makes it into the clinic has a host of failures behind it that the company needs to, uh, to, to carry that burden. That’s why these timelines look like they are for safety, for access, everything else. There’s just there’s a burden of,

Jason Hein 14:53

of, of, of experiment that has to get done so that we know it’s the right molecule helping the right population. Having a tool like this just compresses that timeline. So all of that, that, uh, development cycle, getting to the market means people get helped. Sure, that’s a that has an undercut from just a, a bottom line in cost recovery.

Jason Hein 15:10

But to your point, you’re not waiting 10 years for a drug that might help somebody to reach clinic. You can accelerate that, that process, which means the right medicine is making it to the right people quicker. There’s even a secondary part to this is just, just the general structure. If I’m gonna go through a filing, and I need this drug to make it to people to help out,

Jason Hein 15:30

well, I need to figure out one drug that’s gonna help as many people as possible just for cost recovery. If I made that my, uh, my design of the molecule and the, the, uh, the cost of, uh, developing it was so much reduced, I can help a smaller population, which means personalized medicine. I don’t have to come up with a business case that says,

Jason Hein 15:49

“I need to help half a billion people.” I can help 2,000, 5,000, and it’s still economically viable, which means you’re now doing specialized medicine for people faster, which helps everybody, right? This is not something that’s just mass market and blockbuster. It’s it makes sense for everybody that needs, uh, needs access.

Frank Curzio 16:07

Now, a lot of companies that, that, you know, people and, and, and, you know, having a, a very small market cap company and people saying, “Hey, this is what we’re going to do. This looks really cool,” uh, what I found fascinating is this just isn’t a prototype. It’s not a concept. Uh, when I look at your news right here, I mean, this is telescope innovation. It stole second self-driving lab at Pfizer.

Frank Curzio 16:28

Okay? I could see Pfizer saying, “Okay, you know what? This looks pretty cool. Let me try it.” If they’re getting a second one, it means it works. You look at Korea, right? Uh, massive, right? Self-driving lab for pharma R&D, the very, very huge when, when you look into these contracts. You know, talk about the level of how it went from,

Frank Curzio 16:46

“Hey, this concept,” all of a sudden, Pfizer’s knocking on your door saying, “Oh, we don’t need one. We need two,” which probably means they’re gonna order even more. I mean, this is a real business now. This isn’t something as a as a, you know, low-level biotech, a healthcare company. You guys are selling this stuff now.

Jason Hein 17:00

No, absolutely. So to, to be clear on that second one, that is our second deployment. Pfizer has now got this, this one at that point. We have a, uh, a smaller package. And this was their big extension where they’re now getting the one with a lot more features and, and engagement. And it actually it, it supports, uh, a group that they’re actually building out.

Jason Hein 17:17

So internally, they’re, they’re saying that this is how we are going to be doing, uh, science going forward. So that’s an investment in technology, in, in people, in practice. So they’re, they’re really looking at this as a systematic way of saying, “How do we change what we’re doing?” Um, but the comment about,

Jason Hein 17:36

you know, yes, we’re a small market cap, uh, I think the, the joke I gave you before is what it’s, uh, 25 years to be an overnight success. Um, the, the reason we look the way we do, right, is because, uh, or the reason Pfizer’s sort of interested to work with us is because I have a legacy, uh, with my, my academic lab.

Jason Hein 17:55

So we have, you know, a reputational side of this that really means that people know who we are and what we’re doing. Yes, the business may be young, but this has been my life, right, in that in that in that part. Um, second thing, too, is that we’re the ones that have been training all the people to use this technology. So, yeah, the technology is one part, but you have to arm the scientists of the future that knows how to use it.

Jason Hein 18:15

And that’s really what my lab has been doing up until now. So the investment you’re seeing, uh, this outmoded side of, you know, high people deciding that this is a, a small market cap to throw in is on the back that we’ve been the world leader in this space, uh, for process chemistry for the last, you know, 25 years. Um, I’ve been involved, uh,

Jason Hein 18:34

with, um, what’s called the Canada First Research Excellence Fund, which is Canada’s multimillion, it’s actually $200 million investment into this space to say, “How does self-driving labs revolutionize the Canadian chemical ecosystem?” And, and I’ve been very fortunate to be one of the people that’s helping to drive that thing with my colleagues at the University of Toronto,

Jason Hein 18:52

the, the other number one school in Canada as, as we have talked about.

Frank Curzio 18:55

I put you on a spot there now.

Jason Hein 18:57

No, no. It’s all good. It’s all good. But you, you, you see what I mean, right? That yes, the business aspect of doing this might be the smaller kind of component, but it’s coming on, on the legacy of, of just time in this space that, that means that we are the ones that understand this. And again, that’s the difference, too. While the robotics and things that we’re building out now, we’ve invented a good chunk of the hardware that has to go into the chemical space,

Jason Hein 19:17

there’s very few groups that have the domain expertise of knowing what the problem is in chemical manufacturing, in phi, in, in pharma to really make the impact that we can. So this is where we’re punching way above our weight class, which is also a very Canadian thing that we get to do, right? I think this is this is a very common part of what builds out is we have this history that’s,

Jason Hein 19:38

uh, that’s what that’s, that’s why we’re sort of accelerating through this. And, and again, we’ve been sort of in stealth mode. The way the business was built out is and this is just how my research trajectory works. I’m gonna show you, and I’m gonna prove it, which means instead of the hype cycle, instead of dealing with other components, instead of saying what’s possible, let me go build it and show it. So we’ve been a focused, revenue-driven company,

Jason Hein 19:58

uh, since we started out because project-driven design like this means we’re building real-world application. That’s, that’s really the, the, the most important focus.

Frank Curzio 20:08

Now, talk about the product line because you have something called Direct Inject. If people hear a presentation, uh, talk about what this is and how it incorporates into the, the self-driving labs.

Jason Hein 20:19

So the, the way we started out, the very first thing my lab was working on was just the simple concept of knowing what’s happening inside the reaction is critical to make decisions. And that’s where automation helps a person doing the decisions, let’s say. Um, the analogy back to cars, too, this is your GPS. So before, if you were driving around, you might print out your maps.

Jason Hein 20:40

You’re trying to look for, uh, different, uh, waypoints. Conventional synthesis without a tool like this means you’re following a recipe, and you hope you get where you’re going. A tool like this lets you see moment by moment what’s happening inside the reactor, which means you can make real-time decisions. You can adapt on the fly to any different part, which is huge, right?

Jason Hein 20:59

This is a, a, a, a big part of what’s necessary. So that was our first, uh, product that we launched back in 2020, 2021. We’ve already started to make a, a large footprint around this. This is a core part of my research that came out of UBC. And that, like, that’s manufactured here. It’s built in Canada. Uh, we distribute globally with Metler Toledo.

Jason Hein 21:20

So one of the largest instrument companies in the world is, is kind of our, our distribution hub. And again, that, that shows you that partnership, too, that a small microcap in Canada is doing the manufacturing, but we’re distributing globally through a partner like Metler Toledo. Um, but that tool, that’s just the GPS, right?

Jason Hein 21:36

That’s the intelligence by how a robot might understand the system where a person is the one that’s actually, um, using that information. What that tool does, though, is that incorporates back to the robot. That’s its eyes. The robot now has the actions. It can set up the chemistry. It can run the chemistry. But a tool like the Direct Inject is how the robot understands what it needs to do next.

Jason Hein 21:58

It’s how it listens or sees the world, basically. So that’s where these two sort of fuse. Yes, it’s a dedicated product line on its own, but the technology know-how that we did that is being incorporated back into the larger SDL to, to give it the ability to make decisions.

Frank Curzio 22:14

So speaking of decisions, you, you how does AI incorporate this? A lot of people say they have AI. It’s all about the data. But as you’re doing this with so many I mean, I think people need to understand that there’s millions of compounds that these guys have that, that they don’t wanna push to market because of how expensive it is. It’s huge. And they can’t afford to be wrong. So they want, you know, as much as a guarantee.

Frank Curzio 22:33

When you’re lowering the cost and shortening the timeframe, it allows more shots on goal, allows more stuff that you might not try, and maybe, you know, it increases the chance of finding something that’s revolutionary. How does AI filter into this when I even look at this picture, uh, because this is all it’s not just robotics. It’s AI. It’s chemistry and everything linked together that obviously it is getting the attention of some of the biggest pharmaceutical companies in the world.

Jason Hein 22:54

There’s, there’s kind of three levels. So the current AI component we use right now is actually some very rudimentary stuff. This is Bayesian optimization. It’s kind of normal, um, uh, statist like advanced statistical analysis is, is kind of the thing that’s kind of running it right now. Think of it this way, though. Just like that, you know, your Tesla, when the robot has to go and pick up a vial,

Jason Hein 23:14

move it to a different place, if the powder that it’s handling doesn’t move the way that you originally expected, you need to adapt. So instead of looking at the system and imagining it’s just orchestration, don’t, don’t think of it where it’s just choreography with the robots moving around and moving vials picked in place. Every one of the actions we set up has, uh, a goal and a target.

Jason Hein 23:34

So pick up that vial. Did you pick up the vial? Do you sure you have the vial? So all those components where what it’s doing is grabbing the, the like, every action it does, it’s checking itself to make sure that, yes, I did it. And if it didn’t work the way I wanted, I need to adapt or change how I’m going to I have a response that I can potentially do. You told me to dose 20 megs. I didn’t get 20 megs.

Jason Hein 23:53

What do I need to do to make sure I do get 20 megs? So this is where that dynamic kind of component of, again, self-driving. It’s gotta be able to figure out based on this, the, the chemistry you’ve given it to faithfully execute the goal you told it to. That’s number one. That’s just reliability in how the robot works itself because it’s adapting on the fly.

Jason Hein 24:12

Think of it like the, um, Boston Dynamics, if you’ve ever seen the videos where they’re poking it with a hockey stick.

Frank Curzio 24:18

Yep.

Jason Hein 24:18

The goal there is it’s gotta rebalance. It has to be able to run a program live to figure out that, hey, if I’m off balance, I need to do something to recover. So that’s one piece. The second, though, is, okay, when I run something on that deck, I can design all the experiments. I can figure out what has to happen. It can faithfully execute it.

Jason Hein 24:37

That’s great. But I still have a lot of heavy lifting to do. And maybe the kind of experiment I’m thinking of is wrong. What I really want, I’m like, I don’t go to the lab and say, “Go make me Taxol,” right? Don’t go, “Go make me Lipitor. Go make me, uh, uh, uh, the next Ozempic or something.” That’s the goal you’re trying to do.

Jason Hein 24:53

But really, make Ozempic is behind a whole bunch of experiments that a molecule does what you want it to do. And what you can do is you can give the platform, “I need to run the chemistry. That chemistry needs to have these kinds of features. Those are the analytics are telling it.” But the AI can look at it and said, “Wait, wait, wait. You missed something.

Jason Hein 25:13

This is the next experiment you need to do.” That course correction on what molecule, what experiment you get to do is a piece that we’re starting to bet in. The nice thing about that is we are fundamentally a hard tech company, uh, which means, yes, the, the, the AI development is not our core strength, but talking to people like AWS, Google DeepMind,

Jason Hein 25:33

everybody else, Leela Scientific, right? These are people that are developing that brain engine that ours is the physical body that can, can link those two parts, right? So the hardware design is our key focus. That’s our metric because that’s what Pfizer wants to deploy right now. But as the AI gets better, our tech gets even stronger. And this is something that that those,

Jason Hein 25:52

those secondary partnerships with those model development stuff will start to really start to acceleration, uh, accelerate in this space.

Frank Curzio 25:59

So talk about let, let’s turn page here and talk about your management team, which is incredible. So, you know, you have, you know, obviously, yourself, uh, Dr. Barry Sharpless. Uh, he’s a senior advisor, two-time winner of Nobel Prize in chemistry. I believe he’s the only a lot that he’s the only person that’s alive as a two-time winner. I believe that’s what I heard, uh, which is incredible, right?

Frank Curzio 26:20

So, so you’re looking at a company, and you have, you know, a, a I think US around $20, $22, $23 million market cap. Again, very small, which is which is speculative here. But, you know, you, you have amazing technology and not just a company that’s saying you’re in AI and robotics. And then look at this management team, Henry Dubina. You 35 years of experience. You have,

Frank Curzio 26:38

uh, you know, who I’ve spoken to numerous times, Veso as well. You know, just all these people have numerous experience in this field. Robotics, AI have been around. You don’t see, uh, an executive team like this on a market cap that’s so small unless they really, truly believe you have something special here, and they’re gonna participate in the growth, right? Because I’ve covered small companies all my life.

Frank Curzio 26:57

How did you get a team like this together, which is absolutely incredible?

Jason Hein 27:01

Well, so part of that, too, is I’ve been working with that team for years. So Barry was my, my research advisor, uh, for my postdoc, right? So he was the one that helped train, uh, me in this space. And he’s been engaged as we go through this part, um, you know, since we’ve been inception. He’s the one that kind of lit the fire of, like, this is how we have to go and change the world. Henry and other team,

Jason Hein 27:20

too, these are people I’ve been working with for, for years in Henry came from the space of, uh, Metler Toledo. So he was, uh, the president CEO of, uh, Metler Toledo AutoChem that grew up that entire space around enabling technology. He already has pivoted the field away from old tech working with stone hammers, basically, into what now looks like modern pharmaceutical design.

Jason Hein 27:40

So he’s already seen this kind of technology translation. He sees what we’re building out here, and he understands both from, you know, the relationship we had in advance. That’s what gives him the confidence of, “We’ve delivered. My team has delivered before.” So that’s why he wants to participate.

Jason Hein 27:53

But secondary, he’s, he’s the one that helped to bring forward these, uh, these massive changes in what hardware and what enabling technology can do for chemical manufacturing. It’s he’s the natural person to look and, and lead the ship to say, “Well, this is the next generation in evolution.” So really, what you’re seeing as far as this, uh, this management team, it’s, it’s friends and family.

Jason Hein 28:14

These are people that we’ve had longstanding business relationships in. This is not a team that got came together based on hype. This is the reason they’re here is because we’re mission-focused, right?

Frank Curzio 28:24

Uh, not just mission-focused. It, it, it’s just amazing to have this quality of a team, uh, you know, all joined together and just you could see the potential, right? These are people that could work anywhere they want within the industry, obviously, and they chose to work with you. Another part, which isn’t management, is talk about your students here, right? Because you’re a teacher and, and you’re a professor. Uh, and a lot of these kids get probably excited talking to you,

Frank Curzio 28:45

and you have them helping you out with a lot of this stuff, which has gotta be great for them and great for you because you have passion when you have passionate people that really love what you’re doing that’ll work with you, it’s, it’s the greatest it’s the greatest thing in the world.

Jason Hein 28:56

Oh, it’s and, you know, this is what makes it so much fun, right? So I have the, the I have the joy of, like, I can help grow these kids from undergraduate and graduate school. This is what they get into. That’s what happens through the UBC space. Most of the people that work here at Telescope, they’ve transitioned over. So these are trainees that I, that I helped to bring up. So we know what their capacity is, what their passion is, what their, their desire is.

Jason Hein 29:16

And the reason why, you know, they’ve joined is because this is what they see that they’re helping to change the field in this part. Um, secondary, too, is a lot of my students end up being that vanguard that’s out in chemical industry as well. So like I said, we’re one of the few groups that’s training people at this discipline. Most students that get through this training usually have to go through finishing school or whatever.

Jason Hein 29:37

And most of my students actually end up directly going from training to first-time job in industry, which means the, you know, we’re, we’re the students both working internally in the company but also the ones that are, are helping to be those, um, the, the translation side, uh, we, we all understand each other, right? This is a space,

Jason Hein 29:56

you know, built, built on, on, on people with a common understanding and a common, uh, training set. But, but you’re right. The, the passion that goes into it means that we’re building we’re building something with students that are not looking at the world the way that it is right now, but they see it with capacity and, and what’s possible. And, and having the ability to put together a lab where you’re challenging daily what,

Jason Hein 30:17

what yesterday we’re doing something or today we’re doing something yesterday was impossible becomes a, a very common occurrence that we get to go into. So it’s just, you know, move fast and break things gets to be a fun way to kind of work.

Frank Curzio 30:28

So I want to get into your recent financials just briefly. I know you’re the chief technical officer. So, uh, I won’t get too detailed here. But it’s important to realize, like we said, we have a $22 million market cap, very small company. Uh, I rarely recommend companies, uh, to, to my shareholders, to, to, to, uh, you know, my list of subscribers, uh, this small.

Frank Curzio 30:46

But you’re not just something you’re not just a company that says you’re gonna do something, right? I mean, you’re actually selling the I mean, you look at your revenue right here. Year-to-date gross revenue is $4.3 million, uh, compared with $2.2 million, same six-month period last year. You look at your news flow right here. It, it’s installed a second drive-in lab at, uh, Pfizer, another one in Korea.

Frank Curzio 31:06

I mean, you guys are generating revenue at a $20 million market cap, which is which is insane, right? Just to see how much revenue you guys are generating with, you know, where your market cap is. And I guess a lot of that is due to maybe, you know, people don’t really know the story yet, which is why I love working with, with companies like this. Um, how do you change that, uh, you know, it’s just for me, if you put up the numbers, eventually,

Frank Curzio 31:24

people are gonna figure things out and say, “What is this company doing?” You, you know, I, I wanna bring up this slide, which I find incredible for your size company. And I’ve never seen this covering stocks in, in 30 years. I mean, these are your partners right now, right? So these are global customers in your partner network. These are names on the list that you usually see from much, much, much bigger companies. Well, you have Pfizer, Amgen, uh, Roche, AstraZeneca.

Frank Curzio 31:44

You know, you have Pfizer over here with, with academic and funding partners. Uh, you know, these, these Bristol-Myers, Merck. I, I mean, these companies know that you have something very, very big here. I guess what’s the next step for you to try to get out there is, is, is, hey, you know what? We’ll kind of constantly improve this system. Now that we have good cases in Korea and, and Pfizer, now we can really bring the support to everybody else.

Frank Curzio 32:04

A-and maybe talk a little bit about the scaling process. Is it difficult to scale this process to the point where, say, if you it seems like you’re gonna get lots of orders because when you have the basically one of the biggest pharmaceutical companies in the world ordering two of these, not one, the second one means that this obviously works.

Jason Hein 32:20

Oh, so the, the I think the biggest one goes to, like you said, it’s the scaling question. The, the our decision initially was, let’s focus on prove it, don’t say it, right? So that’s exactly why you’re seeing the, the revenue that we have right now, which we’ve been driving based on this saying, “Look, we it has to actually work.” And that’s the best test is, is actually case-driven points based on, on, on delivery.

Jason Hein 32:41

Um, and, and again, that’s, that’s coming from the space that, unfortunately, this is one of those, uh, spaces that has a ton of hype. It’s really important to make sure we go out there and actually, uh, build something that’s being tangibly tested. So that’s, that’s why it kind of looks as it is. Now, scaling, that’s kind of the, the, the reason that we’re trying to, uh, to go, uh,

Jason Hein 33:00

with the right sort of, um, uh, vector, let’s say. We wanna make sure that we’re scaling in a way that means that we’re here 5 years, 10 years, 20 years, right? That means grow carefully, grow well, deliver on what you say. You’re not going it has to be something where it’s overpromise, underdeliver, or, uh, not that way. It has to be something that is, uh, underpromise, overdeliver.

Jason Hein 33:22

It has to be what we sort of focus on, right? So the as far as next steps, um, now that we’ve got this baseline platform, we’re going to the market and saying, “Does this meet your problem?” But the one of the issues I think we’ve got is it can be anything to anybody. And that means that, well, which problems, which projects do you take on? You can rapidly overstrip your stuff just because you spread yourself too thin.

Jason Hein 33:42

So it’s being very strategic about where the next major deployment comes in in order to scale across that. But the, the, the poll that we have is, is kind of insane. Like, the, the next couple employee or the next couple deployments we have have to be done, uh, in, in a really, uh, important way that we can actually continue to scale the, the company here, right?

Jason Hein 34:03

This is not something that overnight we wanna go completely hockey stick. We need to make sure that we’re delivering on the partners that have that have gotten this far, and we’re supporting them, uh, well in that part.

Frank Curzio 34:13

And you have basically a revenue it’s a razor, razor blade model, right, where it’s not just, “Hey, we sell the systems. Good luck.” I mean, it’s maintenance systems. There’s I mean, talk about that, too, because you, you, you structured this where it’s like, “Hey, we got the system. We just sold it.” There’s always recurring revenue, it seems, every part of this business line, which, which, you know, and, and I credit, you know,

Frank Curzio 34:32

Henry, CEO, who has a history of this, uh, you know, just, you know, working with companies like this is incredible. But you guys have a good runway here.

Jason Hein 34:40

Absolutely. Well, then that’s exactly the point about scaling to, to cover, cover back to it, right? We not this doesn’t go out the door, and we’re done, and we move to the next one. An engagement we have with a company like Pfizer means that there’s a longstanding relationship there, too, because their success is our success, which means we have to have people and resources ready to keep them supported. Um, so that’s where as we,

Jason Hein 34:59

as we scale this part out, it’s not just to deliver the platform. It’s a longstanding, uh, relationship where constant upgrades, constant training, um, adaptation as, as their needs change, then, you know, scaling with them is an important part for us to focus on, too. So this is why, um, it’s not just a, a simple one-and-done product, right? This is a,

Jason Hein 35:19

a, a, an ecosystem that, that continues to grow across that part. And it also goes the other side, too. So Pfizer may be the end user, but on the on the back end, the hardware, the robotics that we have right now, um, vertical integration around that starts to become a major, um, win just because people can see what’s possible. We have vendors now saying,

Jason Hein 35:39

“Hey, we can see what your platform is. We would love if our technology made its way onto your deck so that now it’s part of this, this, this growing ecosystem.” So support from both sides of people that wanna engage with us so that we have, you know, hardware that’s working on it as well as people that need to use it means we’ve got, uh, a really, really good growth strategy.

Frank Curzio 35:57

What are some of the catalysts and we’ll end it on this. What are some of the catalysts, if investors are gonna buy your stock here, that, that they look forward to, say, even short-term, long-term? And I’d say this with a lot of companies, where, you know, you could have a brilliant, you know, brilliant catalyst. If they’re long-term, people sometimes are like, “Ah, I’ll just wait a little while.” But, you know, even the short-term, long-term, you know, what’s going on where investors could get really excited about?

Jason Hein 36:17

So I think the next year or so, what we’re really starting to talk through is, um, like you said, Pfizer’s been a great, uh, collaboration. I think what we’re gonna be able to close up is something that looks like duplication of that Pfizer model across multiple other sites, right? So this is either, uh, a consortium-type model where many people are in the same sort of house saying,

Jason Hein 36:36

“Look, we wanna learn along with Pfizer as a as a noncompetitive, uh, conversation,” or, “We see what you did over there, but we need your attention focused on this other space here. So this is a duplication or sort of like a forking of what we’ve been doing.” So I think we’re gonna start to see, um, in the next year, one of those two models is gonna win out,

Jason Hein 36:55

and that’s where we’re gonna really start to really, you know, rubber meets road heavier. The second one, too, is, uh, as I mentioned with the AI models, we are the physical embodiment of the AI. We are the part of how the AI touches the world. As we start to see, um, the specialty AI for healthcare, the data they need and the ability for,

Jason Hein 37:15

uh, a platform to provide and to feed that beast in terms of the data, um, getting an agreement together where one of those companies says, “You guys are our partners of choice. We’d like to work with you as the hardware,” is gonna be a major liftoff, right, because it means suddenly everything we’ve done, uh, is, is automatically better because the brain changed, effectively.

Frank Curzio 37:35

Yeah. This is incredible, incredible stuff. A-and so Telescope Innovations, uh, you trade on Kenyan stock exchange of a TLI over-the-counter, right, which is normal for container-listed stocks. They wanna have an over-the-counter listing for US to buy TELIF. And I just bring that up right here. But again, you’re looking at a company that has, you know, considering your market cap,

Frank Curzio 37:55

$22, $23 million US, and, and generating, you know, already halfway through the year, you know, over is it close to $4.5 million of revenue, having the partnerships. I mean, this is something that, that, you know, I think you’re gonna have a lot of people excited about. The technology’s there. You have great partners. I mean, it just it checks off all the boxes, which is why, you know, I love working with companies like this where it’s totally undiscovered,

Frank Curzio 38:15

and it’s such in my wheelhouse that I love this. And then just seeing you, uh, reminds me sometimes where it’s like, you know, that this kid in this playhouse, it’s just like, “Hey, look at this. And look at that.” I’m asking millions of questions. It’s really, really exciting. And, and I look forward to your future. And, um, I really wanna say thank you so much for joining us. And I think, uh, you know, people are gonna find out about this stock. It’ll be very, very exciting. You have so many good things going on.

Jason Hein 38:35

Oh, appreciate it, Frank. And you nailed it. Like, this is this is my passion. This is what I work to work on. I love coming in every day and, you know, working with the students I’ve helped to build out and their legacy relationships, um, and just looking forward to keeping it up. So thanks again for the opportunity.

Frank Curzio 38:47

Awesome stuff. Thank you for coming on. And, and we’ll definitely touch base soon.

Jason Hein 38:52

Thanks, man.

Frank Curzio 38:54

Hope you enjoyed the interview. I, I really like Jason. He is passionate. He’s brilliant. He loves what he does. I mentioned earlier, I saw his classroom and, and his lab, and he was taking me through it. I was probably there for an hour.

Frank Curzio 39:09

And, uh, I was just, you know, a kid in a candy store asking him millions and millions of questions because I was fascinated because I saw these robots firsthand and, and what they’re capable of doing. Uh, and I couldn’t believe he told me that we just sold our second system to Pfizer. I mean, one is kind of like, “Okay. Let’s see how it is.” The second means that it works. A-and it puts them in line for to be acquired,

Frank Curzio 39:30

uh, at a much, much higher price than it is right now. It puts it you know, they have so many different partnerships where, you know, they could license a lot of this stuff, which is what they’re doing now. They understand, uh, it’s a supply chain management, which they’re going over now. This way, they could scale this stuff. But demand is really off the charts for this. And I love working with small companies that nobody really heard of. There’s no coverage on it.

Frank Curzio 39:49

So every I really have to do details. I have to go over the numbers and really break this down, which I’ve done in my newsletter and recommended to our paid subscribers. Uh, this is a company I have high hopes for. Uh, management, of course, has to execute. So there’s always risks with that. But meeting with the management team and seeing the experience and, guys, we talked about the management team during the interview, and I showed you.

Frank Curzio 40:08

When it comes to small-cap companies, again, doing this for, for most of my life, in order to get a team like that for such a small company, there has to be almost that promise of this company is going to be very, very successful years on. And when everyone comes together, right, you don’t have a ton of cash to pay these people.

Frank Curzio 40:28

What it is, you’re paying them in options, or you’re paying them in shares and, and saying, “Hey, you know what? Be part of this innovative process.” And these are brilliant people who are on the board, brilliant people on the management team that could work anywhere they want. And to be working at this small company is a testament. It says, “Hey, we really believe they’re gonna participate.

Frank Curzio 40:46

They’re gonna benefit if this company grows tremendously.” And that’s why they’ve all come together to work specifically for this company. A-and when you see that, it’s the ultimate buy signal. When you see people that could work anywhere and get paid millions of dollars to work to be advisors here or there, and they all come together for this small company, uh, it, it really is remarkable. And that’s what caught my attention.

Frank Curzio 41:05

So, uh, I’m very happy for these guys. Telescope Innovations did this so early in their growth trend. I feel like nobody heard of them. Uh, this is a company you’re gonna see a lot of more analysts cover later on, especially as revenue builds. Now that, you know, you’re gonna see news if you go into their news flow, which I which I showed you, it’s, you know, Korean company, South Korea company, uh, that they’re selling these self-driving labs to.

Frank Curzio 41:25

Uh, you know, they are generating revenue. They have partnerships, I think, with most 15 to 20 top of the largest pharmaceutical firms. Again, you don’t see things like this with such a small company. That’s what has me excited.

So listen, if you have questions or comments, feel free to email me, frank@curzioresearch.com. Other than that, I’ll see you guys tomorrow on Wednesday’s scheduled Wall Street Unplugged. Take care.

Announcer 41:40

Wall Street Unplugged is produced by Curzio Research, one of the most respected financial media companies in the industry. The information presented on Wall Street Unplugged is the opinion of its host and guests. You should not base your investment decisions solely on this broadcast. Remember, it’s your money, and your responsibility.