In a recent episode of the Dealmakers’ Podcast, we spoke with Pavle Jeremic, the visionary founder of Aether. Pavle shared his inspiring journey from a unique upbringing to the forefront of bioengineering, driven by a mission to revolutionize industrial productivity.
His startup, Aether, has attracted funding from top-tier investors like BoxGroup, Gaingels, Jay Zaveri, and Dolby Family Ventures.
In this episode, you will learn:
- An upbringing amidst technology and war-torn Southeastern Europe instilled a lifelong commitment to leveraging innovation for global betterment.
- Transitioning from biological nanotechnology to true nanotechnological revolution for unprecedented industrial productivity.
- The journey from fee-for-service to end-to-end product development highlighted the power of data-rich platforms in accelerating innovation.
- Emphasis on the importance of discerning valuable advice from a network of advisors with domain expertise in navigating the complexities of entrepreneurship.
- A decentralized future of modular factories, powered by second-generation nanotechnology, revolutionizing industry and global impact.
- Highlighting the pivotal role of machine learning in driving the transition from biological nanotechnology to true nanotechnology, showcasing the transformative potential of this technological leap.
- Aether’s vision extends beyond conventional industry, aiming to render biological systems obsolete and usher in a new era of second-generation nanotechnology, promising unparalleled levels of industrial productivity.
For a winning deck, see the commentary on a pitch deck from an Uber competitor that has raised over $400M (see it here).
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About Pavle Jeremic:
Pavle Jeremic, who has a bachelor’s in biomolecular engineering from UC Santa Cruz, founded Aether Biomachines in July 2017 at the age of 21.
He built a platform that runs trillions of completely automated experiments. Jeremic says its speed, accuracy, and scalability mean Aether’s platform can reimagine biological manufacturing by repurposing enzymes to create entirely new compounds and dramatically lower the cost of existing compounds.
With $11.5 million in seed funding, Aether expects revenue to reach at least $2 million next year.
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Connect with Pavle Jeremic:
Read the Full Transcription of the Interview:
Alejandro Cremades: Alright, hello everyone and welcome to the dealmakerr show. So do today we have a really exciting founder. You know we’re gonna be talking about scaling you know then and all that good stuff that we like to hear with the financing. You know, involve ramping up. Also you know about culture ah hiring. Also about how to how to put together a really compelling mission and vision and also about the experience in raising money during difficult times because I mean obviously you see the macro environment right now is is pretty Bumpy. So I guess without further do let’s welcome our guest today Paff late jeremich welcome to the show.
Pavle Jeremic: Thanks for having me all andra.
Alejandro Cremades: So originally you were ah basically the the son of immigrants immigrant parents and it was quite a really interesting upward upbringing in different parts of the world so give us a walk through memory lane. How was life growing up.
Pavle Jeremic: Yeah, yeah, I mean ah so my parents. Ah you know I was born while my parents are graduate students in the United States they had just immigrated several years prior from Yugoslavia they left because the civil war. Started and it was a bad time to be in that part of the world and I’m very glad that they did it really worked out us moving to the United States and you know, growing up. We didn’t have a lot of money but I was I had a very unusual upbringing where one I was constantly surrounded by technology both my parents are graduate students and engineering and I you know graduate. Graduate students. Don’t make a lot of money so I was usually in their labs often as sort of the daycare equivalent and um for other parts. The era being raised my grandparents either in the United States or back in Southeastern Europe and so I really grew up in these 2 different worlds 1 surrounded by technology in the United States in major universities in the Us and then in the other world. You know, ah living in the old world in a world where an active civil war was going on and every time I came back. There were new bombed out buildings. Um I think it left an impression with me from a very young age as long as I can remember that. You know, not all the world is rosy and picture perfect and that there’s a lot of work. We have to do to create that kind of world for the rest of the human race.
Alejandro Cremades: Um, so out of all things Why why? bioengineering.
Pavle Jeremic: Why bioengineering? so.
Alejandro Cremades: Yeah I mean how how do you? Obviously you know like you got into technology and you were part of the labs you know because of your parents. But I guess like was it like a natural you know, smooth kind of like transition into into getting. Into bioengineering or or how do you develop the love to say you know what I want to study that.
Pavle Jeremic: Oh no, yeah yeah, yeah, it’s a good question. So um, you know I’m the first person in my family to ever do anything related to biology. So um, you know that it certainly wasn’t like working in my parents labs that led to that. Well I would say that where. Interest in biological engineering came from was a question I was asking myself from a pretty young age which was how do we create a technological basis that would enable 10000000000 and hopefully tens of billions of human beings to live and consume at a rate that you know we. Accustomed to in the developed world ideally without destroying the planet in the process right? which we are doing so right now and we’re not even providing that for every human being so I was thinking about that a lot as a kid and I was reading a lot about nanotechnology and you know ritle of science fiction which always helps. And I really I came to the conclusion at a pretty young age that the only way for this to even work this kind of massive increase in industrial productivity I mean we’re talking about somewhere between 7 to 15 times greater industrial productivity for the entire human race. Um. The only way that I could really see that even being remotely possible would have to be some kind of nanotechnology some kind of molecular base machinery that could extract and assemble products close to the limits of thermodynamic efficiency and do so pretty much anywhere on the planet. Of course we don’t really have.
Pavle Jeremic: Kind of natechnology doesn’t exist. That’s just in the the writings of Arthur C Clark and Isac Gasimov and other science fiction writers. So as I was growing up I was trying to understand. Okay, well how would you build this kind of nanotechnology. How could you even make that possible. Um and I could not figure out how you could do it until I was very fortunate really starting in early high school. Um, a professor at ucdavis here in California where I I was growing up at the time that professor took me in and let me do my own synthetic biology research and you know through that process I had 2 realizations that were really significant I think set the trajectory of my life till now the first was a incredible realization that. Nature had evolved something that kind of looked like nanotechnology now to be clear what nature evolved is not the long-term solution for the human race nature evolved to solve a very different set of problems than what our species needs to solve. But I’ll be damned if it wasn’t the closest thing I’d ever seen to functional nanotechnology way closer than anything else. The the human race that ourselves had developed so that was very exciting. This is I I had found for the first time something that looked like the starting point to build real nanotechnology. However, um I can tell you that I walked in I even remember walking into the lab on my first day I walked in grossly overconfident. And how easy it was to engineer biology I really thought you know oh this is going to be like any other engineering discipline I’m going to have a prototype ready in six months I’ll be done with my project in a year and I’ll move on to the next thing and I can tell you through painful experience that biological engineering is nowhere near as straightforward.
Pavle Jeremic: Any other engineering discipline. In fact I have a degree in it I would argue that the word engineering is perhaps a bit generous. Um, it’s much more of a science than an engineering discipline and that really comes from the simple fundamental truth that what nature has evolved.
Pavle Jeremic: Is not only not only do these machines operate on principles that are fundamentally different than any human deriv technology. But these machines are unbelievably complicated and non-modular compared to human-based technology and so you know leaving this this experience in high school doing this research this really fundamental. Ah, genetic engineering research I really left it with 2 realizations. The first was I had found what I needed to start with to build this future of abundance for the human race I found the starting point finally after years of thinking and looking but it was also very clear to me that you know.
Pavle Jeremic: We were not as a species close to being able to understand how to engineer these machines and that if I was going to take if I was going to start with the biological nanotechnology the nature evolved and use that to build true nanotechnology that could create this future abundance of the human for the human race I would need to build a technology. That could enable that transition that that wasn’t ah an already solved problem and so you know going through my um, my undergraduate experience and starting ether. That’s really what ather was about you know, hopefully that answer your question but that’s that’s really the ark. Um, and how I ended up in biological engineering in the first place.
Alejandro Cremades: So then how how did all transition. You know to you in 2017 obviously like finishing up your your studies and then deciding that perhaps it’s time to venture into the world of entrepreneurship.
Pavle Jeremic: Oh Yeah I mean I had been thinking about this for years I’d even tried to do a startup in high school and so this had been this had been the plan for a long time and and the reason why I wanted to start a company and you know at least begin to have. The impact on the human race that I want to have in the startup world. It was simply because I felt that it was the fastest and most effective path to changing the course of human history history right? It’s I could have become an academic but then I would have just wrote written papers. Um I could have. To work at a bigger company. But then I wouldn’t have the impact that I’d wanted I could have gone into politics but the technology doesn’t exist. The political solution is impossible until the technological solution exists for the future of our species so it was you know I had already decided I mean I remember when but it was very early on I decided that the only. Path I could see to having the maximum impact on the human race in the shortest possible time was through building a company to do this and you know I tried to do it in in high school. The the idea didn’t really make sense in high school went to undergraduate and. When I decided to found ather. It was really based off this idea of I was ready to go It was time to do it. It was time to find people to bring on Board. Um and pull together a team and start executing. Um, So yeah, it It had been planned for for quite a while and actually I Even um I was.
Pavle Jeremic: Double majoring in bioengineering and astrophysics and I actually dropped astrophysics in part because I wanted to just get out as quickly as possible and get to work. Yeah yeah I mean you know I would say that it is.
Alejandro Cremades: So then tell us how we’re getting to work. What did that look like.
Pavle Jeremic: The easy part is legally starting a company right? That’s that’s easy and there’s god knows how many startups and services now that can get you incorporated somewhere I will say that if you find a great name and you want to file for it. Um, file for it as quickly as possible where ather biomachines because ather got taken in the four day window that I didn’t file quickly enough. So um, that would be 1 piece of advice I have and I think you know.
Pavle Jeremic: Getting started with ather was an interesting trajectory. So what we originally started doing. You know it had been clear to me from the beginning that the only way to take these nanoscale machines that nature evolved and and create that transition to real function on that technology. Been clear for me for years even before undergrad that that would have to be driven by machine learning that it wasn’t human beings or it’s not like that human beings are not well equipped to understand proteins and biological nano-machinery but just the way machines work at the nanoscale is wildly different. Than anything at the macro scale. So it’s we’re not well set up to have an intuition for nascale machinery so it was clear to me for year many many years that even before it found today with or that um it would have to be machine learning driven process and I also suspected you. Good.
Alejandro Cremades: So so.
Alejandro Cremades: Keep going keep going.
Pavle Jeremic: Oh yeah, um I also was pretty confident that the data to train these machine learning models didn’t exist and publicly available data sets of different enzyme activities or protein activities or just.
Alejandro Cremades: Um, down.
Pavle Jeremic: Sparsely populated. They have annotation issues and you know a lot of papers are not necessarily as replicatable as you’d hope they would be so you know we spent the first bit of time trying to take public data sets and train machine learning models off of them and and it worked fine. You know we were able to make some progress but um. I think early on I was trying to find enough proof points to prove that the concept could in theory work so that I could start building the robotics because pretty much from the get-go I was convinced that existing datasets would never work. To train the machine learning models. They’re just not big enough. They’re not rich enough. They’re not reliable enough and sufficiently high quality and even more fundamentally. Um, what we’re doing at ether is just wildly complicated. We are engineering nanoscale machinery to catalyze new types of chemical reactions create new types of molecules. And then on top of that we have to bundle all of that into an end toend product and chemical process that actually can be sold and generate value. So you know I’m I’m not beating around the Bush here. This is a hard fucking company and every part of it’s very very difficult and I felt it was very important early on. To start building the full capability to engineer these machines ourselves because um, you know, even though it’s more expensive to build all this machinery and to build the robotics and to run them. You know I’m often I get sometimes be a little jealous of my friends that run software companies because you know my god do they spend less money every month than we do.
Pavle Jeremic: Um, but I felt we had to do everything ourselves because it’s just we can’t rely on a third party that isn’t as desperately motivated as we are to get everything right and get the results as quickly as possible. Um, and it’s taken us a long time to get to the point where the the process works it works quickly. It works robustly.
Alejandro Cremades: Um.
Pavle Jeremic: Um, longer than I wanted to um I will say that the most you know building a robotic factory and running it has probably been the most humbling experience of my life. It’s way harder than I thought it would be but we’re there. Um, and we really have incredible capabilities now that I don’t think exists anywhere on the planet.
Alejandro Cremades: So then let’s talk about that. Ah, for the people that are listening to get it. What ended up being the business model of ether. How how do you guys make money.
Pavle Jeremic: Yeah, yeah, and let’s actually talk about how we came across our existing business model because it was a bit of a journey and I think it’s ah you know an illustrative journey and and I what I will say before I talk about the journey of how we landed on our current business model I will say that you know.
Pavle Jeremic: Everyone’s advice and experiences are idiosyncratic to what they did So as much as this is our experience and what we learned and what worked for us entirely possible. Other companies might find something else that works you know, just always important to say that off upfront. But you know the the long-term plan for ather was always to. Figure out how to engineer these proteins these enzymes these peptides. Whatever you want to call them and honestly they barely even look like enzymes in nature anymore. So We have to come up with a better term for them. But um, it was always to the long-term plan was always to get to engineer these machines. To create new types of molecules new types of chemical reactions that aren’t really possible using any other approach and then building credible products based off of that new molecule or that new chemistry. Whether that’s a next generation Ballistic material. That’s as light as silk but stronger than keflar or if it’s a shipping container size Box. Can extract Lithium and produce battery good lithium at the backend. Um, so that was always a long-term plan but when I started trying to go to Market I had an assumption which was I thought that it would take a really long time to engineer. New types of chemistries and new types of molecules I thought that that would be a very difficult proposition and what I really thought was that when we were generating all this data. So So the core capability of ather from a technical perspective on our robotics in our platform.
Pavle Jeremic: Is the fact that we can not just test huge numbers of different enzymes and proteins in parallel but that we can test them against many different molecules many different metals in parallel as well. So We generate very rich datasets of all the unexpected functions that we discover either accidentally or intentionally. Removing for our process. This is really key. It creates ah datasets that only we have on the planet that are really incredible. Not just for machine learning but creating new types of products and I thought that when we were going to start that these datasets wouldn’t be be very rich. And the beginning I thought that it would take a very long time to engineer new chemistries or discover new chemistries and so I thought the best business model we should start with was a service model. So I thought Okay, you know we have this incredible protein engineering platform. We’re going to go find companies like pharmaceutical companies and we’re going to charge a fee. And we will engineer enzymes for them or proteins for them that solve a manufacturing problem for example and you know we actually even signed one deal and I can’t tell you what the name of the company is it’s actually confidential but what I can tell you is that from a technical level we succeeded and what I was actually shocked by Was. We know that this company It’s one of the largest ah pharmaceutical Manufacturers on the Planet. We know that they had they talked to other people other much larger enzyme companies and that they had been unable to find an enzyme that catalyzed this chemical reaction. They really wanted. It was very important for the manufacturing process of a drug that they were making.
Pavle Jeremic: We found it in I want to say four and a half months of operating the factory and not only that in in the process of finding this enzyme this enzyme designed we found a bunch of other new chemistries. We weren’t expecting a lot of them and the final thing we discovered was that. It is very difficult in our space to commercialize a fee for service model and the reason for that is it is hard to engineer proteins. It’s just a hard thing to do I mean we’re very good at it now. But it’s just a hard thing to do it takes longer than you’d expect a lot of the time and the other problem is is that. If you’re offering a fee for service to help them help ah a client improve a manufacturing process. Even if you reduce their manufacturing cost by 50% which is what our enzyme would have done. You have a really hard uphill battle to get them to deploy your product at scale for couple reasons 1 they’ve already invested all the capital. And the previous manufacturing process. So even if you’re saving 50% on operating expenses who cares they already sunk a $100000000 in this plant. That’s ready building. It’s going to take 7 years before that saving even becomes they’re going to rebuild the plan and the second thing that was even more fundamental is that and and this is really influence our current. Business strategy and go-to-marke strategy is that um, when you engineer an enzyme or a peptide or whatever you want to call it a protein that has some incredible new functionality that hasn’t existed in nature and doesn’t exist in in traditional chemistry either.
Pavle Jeremic: There’s a lot of work beyond that to actually turn that into a successful product. How do you use the enzyme in an industrial process. How do you purify the backend. What are the conditions that you run the enzyme and there’s a lot of work after you find the enzyme to actually get ah something that you can generate revenue off of and as much as. We hope and as much as many companies in our space hope that they can just partner with a bigger company to handle all those other problems I think you’re shooting yourself in the foot if you do that because no one is going to be as motivated as you are to try to generate revenue off of this nobody is going to move as fast. You will because you’re working with these giant companies and move very slowly and I think what we discovered through our process was we found something incredible that our competitors had been able unable to find and then we struggled to find a way to quickly commercialize that we struggled to get a timeline with our partner that would actually lead to revenue quickly enough to justify the investment that we made. But at the same time the whole idea of starting with fee for service was based off of my thought which was it would take us a really long time to find new chemistries and I was just totally wrong. We were discovering them like that they were coming up all the time as we generate data on our platform so that was a really key moment in the history of the company where we said wait a second. We don’t have to wait start working on incredible new products. There is a lot out there in the enzymes we’re engineering the functionalities we’re discovering and we were. We were actually wildly conservative in terms of how long it would take to get to this so I think that was one of the very big pivot points and then we started working on and what we work on today is.
Alejandro Cremades: No.
Pavle Jeremic: Actually developing end-twin products ourselves. So like I can give you 2 really good examples of some of our key products working on. Um you know one is in our ah mining space. So we’ve been engineering over the past year a class of very very small proteins are sometimes called peptides. It’s just a term that means a very small protein. Um.
Pavle Jeremic: And what these peptides do which is very interesting and exciting is we can engineer them to basically selectively trap different metals and we can do this with lithium we could theoretically do it with titanium we can do with Manganese we can do. There’s a bunch of metals we can I mean theoretically it should work with any metal just different metals will be differently difficult. So why do we care about this? Well if we can like lithium’ is a good example and that’s sort of our flagship product in that space right now but we have Titanium Ven Adium Manganese and a couple other metals going up right? behind it? Yeah yeah.
Alejandro Cremades: and and and I guess and I guess 1 thing here you know too is you know I’m sure that the that the listeners are going to really love listening to to this is obviously I mean you ah guys arrive to finally the business model that makes sense. How do you guys? go about finding the money to um. Finance the operation because I mean you guys have raised close to 50000000 I mean what? what was what was that journey like of of raising money for something so complex like this.
Pavle Jeremic: Um, I yeah.
Pavle Jeremic: Oh yeah, very difficult. Ah very very difficult. Um, so so what I would say is I think that this is probably the most adverse fundraising I mean I you know I haven’t been in the business for decades. So I was not. Around in in the business in 2008 or 2001. Obviously so um, take everything I say with grain and salt. But what I will say is this is probably the most adverse fundraising market I’ve ever seen in my limited experience and it’s adverse for a couple reasons one for all the obvious reasons of people freaking out about inflation and you know. I would say that there’s been sort of this strange phenomenon I’ve observed a venture capitalist telling themselves that recession is coming basically every quarter for the last two years and and you know whether or not the recession happens. They believe it so that influences how they invest in and it also hasn’t helped that most of the other major synthetic biology companies have struggled. Imploded in this time for reasons that you know unfortunately we had expected. It’s it’s stuff that we’ve tried to fix our company and not do but it’s just unfortunate that it’s happening especially now so I would say it’s very challenging and and I think what’s what’s important is it’s challenging for 2 different reasons. There are investors out there who especially if you say something like lithium you know which is the hot craze right now and that that’s everything that everyone’s looking at there are investors out there who will write you a check very quickly on it. But I have learned the hard way that it is.
Alejandro Cremades: And.
Pavle Jeremic: It’s pretty much a net negative for the company to bring in investors that don’t that one haven’t built companies of their own or have experience operating very difficult companies and they know how difficult it is to actually build these kind of companies and 2 you need to bring in investors that know your space and know how hard. Industry. You’re building is because getting money is actually not necessarily the hard part getting money that’s going to be a net positive for you beyond just the check but the actual connections and the advice and the influence in the company that’s difficult so I would say that um in our raising this sum of money. I would say the the first difficulty was really trying to understand who are the investors that are actually going to be that net positive based off my experiences of learning the hard way and then the other thing was once you found those investors that you think will be the net positive. You know it’s it’s a very difficult market. You really had to sit down and go through in detail work with the investor. Why does the technology make sense. Why are we uniquely differentiated why? Why is our go-to-marke makes sense and what I’ll tell you honestly is it’s probably better for the entire ecosystem that fundraising is like this. It was probably too easy. To raise money over the course last ten years and a lot of frankly, really bad ideas. Got a ton of money and nuked those industries for a long time and and the other I think I think the last thing that that I really noticed in this this fundraising cycle which I thought was interesting is that you know previously before.
Pavle Jeremic: The sort of implosion of the private venture market about a year and maybe a few months ago once you secured a lead investor for your for an equity round of course getting the follow on was a pretty fast process. It was you know you have lead investor. Great. Find follow on investors and they would you know you’d lose some but you’d get checks pretty quickly there afterter what I thought was interesting and again this is probably actually healthier for the entire ecosystem in a lot of cases for us. The follow ons were often as difficult as elite. It was a detailed diligence process with every investor it worked on now. Plus side of that for ather as we grow is every single investor that joined our round is deeply familiar with what we do and they know how difficult what we’re doing is so I think it’s actually going to be a net positive but it was just an interesting observation that I had which was you know, used to be follow on was a foregone conclusion. I didn’t experience that to be the case now. There’s probably also the flip side that it was an adverse market a lot of other symbio companies imploded. Um, so I’m I’m sure that that my experience won’t be the case for other people in other markets I’m sure there’s exceptions to that rule but interesting observation nonetheless and probably better. But the industry overall.
Alejandro Cremades: So now imagine you go to sleep tonight and you wake up in a world where the vision of ether is fully realized what does that world look like in 1 minute but would you say.
Pavle Jeremic: So in a world rather vision is realized almost every product that the human race consumes is basically manufactured in semi modular shipping container size factories that are distributed across the entire planet. You have. Hjv drugs being manufactured in decentralized way across sub-saharan and central africa you have next generation materials for our soldiers being manufactured on site to repair different components even at forward operating bases. You have ah lithium and other critical minerals like titanium being mined. With these shipping container size systems dotting across the country and the entire world to the point where I mean lithium titanium all these other metals are as cheap as steel or even steeper ah cheaper, um, the vision really is this this massive increase in industrialized productivity and industrial productivity. Based off the full decentralization of its manufacturing and being enabled by these nano-machines that we can create and you know what does the second generation nanotechnology look like after we make our biological systems obsolete because importantly, that is the goal today we work with biological systems. The goal is to turn. Make them obsolete I have some ideas of what they probably look like but I’ll I’ll let you know when I see them working.
Alejandro Cremades: I love that now. Let’s say I put you into a time machine and I bring you back in time to that moment. You know, maybe let’s say around 2017 when you were thinking about launching you know ether and let’s say you have the opportunity of um, just keeping that younger Pavle Jeremic: t. 1 piece of our device before launching you know the company. What would that be and why you know you know now now that you’re actually like almost seven years in
Pavle Jeremic: Um, me move.
Pavle Jeremic: Yeah, yeah, it’s good question I mean there’s a lot of advice idea myself, there’s been I Will certainly say that you know I wish I mostly learned from successes but actually you know it’s mostly been catastrophic failures and you know you try just try not to make the same mistake twice. But trial by trial by fire. Um, let me think I would.
Pavle Jeremic: I think the most important piece of advice I’d give myself which it took me a while to really understand this is that especially and and and this is especially true in Silicon Valley but it’s also true in everything else in life I just in Silicon Valley in particular it’s quite significant. Everyone is going to have an opinion on what you should do but not everyone is going to have a good opinion on what you should do and I think something that I’ve learned sometimes the hard way is to really think about building a network of advisors and friends that I trust and then really thinking about. Given their experience given what they’ve done historically well and maybe what they’ve done not well in their past because everyone has something they’re good at something. They’re bad at what are the kind of things that they’re going to give good advice on and what are the kind of things where it’s like yeah you know I know that’s your opinion but I don’t think so. That that to me I think has been really a ah significant learning. Um, because yeah I mean especially in Silicon Valley I mean you know you just get flooded with people that have strong opinions on what you should do and honestly most of those opinions are garbage. Um, and and again they might not be garbage for that person in their roles if they went and founded. You know an app company delivering food. Maybe that opinion made perfect sense for that application. But that I think is really the critical thing that I would tell myself and really try to help my younger self understand is your job is to understand in part.
Pavle Jeremic: What are people? Yeah, we’re just pattern recognizing machines. That’s what human beings are so when you ask someone about a pattern that you’re seeing what have they seen before and what do you think they’re going to be good at recognizing versus. Not.
Alejandro Cremades: Now.
Alejandro Cremades: I Love that I Love that now for the people that are listening pavly. What is the best way for them to reach out and say hi.
Pavle Jeremic: You could always reach out to me over Twitter now. Um I actually respond pretty quickly on there. You could try to email me but that’s harder um to reach out on me but my Twitter handle is send biomars and or if you just look a pavly yetim each on Twitter you’ll find me as well and there’s not that many people with my name at least in the United States um beer
Alejandro Cremades: Amazing, well easy. He know hey pavly. Thank you so much for being on the deal maker show today. It has been on on earth to have you with us.
Pavle Jeremic: Thank you, Thank you for having me. It was a great conversation.
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