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Pavle Jeremić, Founder and CEO of Aether – Interview Series

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Pavle Jeremić, Founder and CEO of Aether, is a scientist-entrepreneur focused on turning advanced research into real-world industrial impact. With a background in biomolecular engineering and early hands-on research across synthetic biology and molecular prototyping, he founded Aether to bridge the gap between AI-driven discovery and physical, market-ready outcomes. His work centers on applying machine learning and automation to problems that traditional chemistry and manufacturing have struggled to solve at scale.

Aether is an AI-native biotechnology company that designs novel proteins using a combination of proprietary AI models and high-throughput robotics. These proteins act as molecular machines capable of enabling stronger and lighter materials, breaking down persistent environmental pollutants, extracting critical minerals, and supporting more sustainable manufacturing processes. Backed by leading investors and moving rapidly into commercialization, Aether aims to reindustrialize key sectors by replacing slow, capital-intensive chemical processes with precise, scalable, and environmentally efficient biological alternatives.

Your path from early research roles to launching Aether shows a consistent drive to turn science into real-world impact—how did those early experiences shape your decision to found the company and define its mission?

My drive took shape at a very young age. I grew up in two very different worlds, where I spent part of the year in the United States and part of the year in the former Yugoslavia. I realized that the nice university towns in the U.S. aren’t a reality for every part of the world, and that inspired me to try to find a way to create more abundance, economic freedom, and upward mobility. When I was around 10, I read books about nanotechnology, and it clicked that this type of technology could be a solution.

Then, in middle school and high school, a professor at UC Davis took me in and let me do my own synthetic biology research. Through that research, I realized that proteins are the closest thing we have to real, functional nanoscale machinery. This is where the idea for Aether was born. If we could get exceptionally good at building nanoscale machinery with protein-based building blocks, what kind of incredible products could we make? Could we create a future of abundance? That’s our mission at Aether today.

For readers unfamiliar with the space, how would you describe your Protein Function Model and why it represents a new paradigm in protein engineering?

At a high level, our Protein Function Model can map a protein’s function to its design. However,  because of the statistical nature of things at the nanoscale level, one protein can have many different functions.

What drives our Protein Function Model and makes it unique in the industry is our ability to generate data sets, or indexes, where we test huge panels of proteins against huge panels of different functions at the same time. By doing this, we can identify the specific functions of each protein, and then give it the function we’d like it to perform. For example, we want protein X to break down a toxin and protein Y to bind to gold. Whatever the function at the molecular level, our model can output a protein to execute.

At what point did you realize that AI-designed proteins could realistically move from lab concepts to commercial industrial solutions?

If you had talked to me at the beginning of Aether, I would have told you that the most important thing we needed to do as a company was to engineer this novel protein system. But, we made a very intentional decision a couple of years ago to not only engineer the protein but also to vertically integrate and create final products. So we put in the reps, learned lessons along the way, and today we are reaping the benefits of incredible product design, our scale of capabilities, and impactful products that are in the market.

What allows AI-designed proteins to outperform traditional chemical manufacturing approaches in speed, efficiency, or scalability?

Our process with our AI-designed proteins provides us with the precision and sophistication of massive chemical factories, but at a fraction of the size, enabling us to make new products faster, more affordably, and more sustainably.

Proteins offer specificity – they are nanomachines that build, or bind, or break with precision. This makes them efficient. With the use of AI, we can engineer them to be even better. We can make proteins that catalyze a specific reaction; for example, stitching together monomers to put them together at a faster rate.

How do you test and validate that a newly designed protein will work reliably in demanding, real-world settings like defense, aerospace, or mineral extraction?

We test and validate protein functionality in real-world conditions through extensive in-house prototyping in bench-scale catalytic reactors. We evaluate relevant performance parameters; for example, selectivity for dysprosium over terbium, down-selecting the best candidates that are then scaled up for validation in pilot tests and beyond.

Among your current applications, from advanced materials to environmental remediation, which do you expect to scale first, and why?

We recently raised $15 million to scale our first commercial products in super materials, RapidPrint and Ultra 3D, which print up to 10X faster and 2X stronger than industry benchmarks. They are used in powering drones for defense and complex parts for the aerospace industry–two areas where we are seeing the most demand right now.

How do you evaluate the environmental benefits of your work, whether in breaking down persistent chemicals, capturing carbon, or enabling more sustainable manufacturing?

We use different methods to assess environmental benefits. With enabling more sustainable manufacturing, for example, we evaluate the difference in toxic chemicals and energy used between our process and the traditional chemical route.

As you move deeper into commercialization, how do you see the company evolving in terms of products and industrial focus?

Our goal is to eventually vertically integrate from the molecular level all the way to kiloton-level manufacturing of incredible products everywhere on the planet.

Looking five years ahead, what progress do you hope Aether achieves, and what milestones would signal you’re on the right trajectory?

Looking ahead to the next five years, we’re hoping to build the foundation for re-industrializing the US through orders of magnitude cheaper and more effective manufacturing technologies based on the molecular assemblers we create.

Thank you for the great interview, readers who wish to learn more should visit Aether.

Antoine is a visionary leader and founding partner of Unite.AI, driven by an unwavering passion for shaping and promoting the future of AI and robotics. A serial entrepreneur, he believes that AI will be as disruptive to society as electricity, and is often caught raving about the potential of disruptive technologies and AGI.

As a futurist, he is dedicated to exploring how these innovations will shape our world. In addition, he is the founder of Securities.io, a platform focused on investing in cutting-edge technologies that are redefining the future and reshaping entire sectors.