Positron is a company reinventing how researchers leverage AI/ML in science, accelerating the pace of discovery 10 times and fueling innovation. Pulse 2.0 interviewed Positron Networks co-founder and CEO Sid Rao to learn more about the company.
Sid Rao’s Background
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Can you tell me more about your background? Rao said:
“Well, let’s start with the basics. I’ve spent over 25 years in the trenches of software development, product management, and leadership—everything from writing code to steering the ship. I cut my teeth at Nortel Networks, then went to Microsoft, where I transitioned from developer to management. Eventually, I took the helm at an Indianapolis-based software startup, CTI Group. Ten years later, after turning things around, we had ourselves a successful exit. And then came Amazon Web Services, where I spent nearly another decade leading initiatives in real-time communications, productivity apps, and machine learning.”
“Seven of those years were spent working alongside my co-founder—an exceptionally talented leader in real-time communications who also ran an ML DevOps group. Together, we built a deep understanding of what scientists need to turn theory into reality.”
Formation Of The Company
How did the idea for the company come together? Rao shared:
“It started the way a lot of good ideas do—by listening. My co-founder and I saw something troubling back in our AWS days. Our machine learning scientists were racking up enormous infrastructure bills — upwards of a million dollars per researcher per year—because they didn’t have the experience to
leverage cloud computing efficiently. These were brilliant minds with industry-leading talent, yet cloud infrastructure’s nuts and bolts slowed them down. Then we started talking to university researchers, and guess what? The problem wasn’t just in our backyard—it was everywhere.”
“So, we did what you do in situations like this: we launched a campaign. We spoke with over a hundred research institutions across the country, and a pattern started to emerge. Researchers across every scientific discipline—biology, physics, climate science—you name it—felt the same frustration. They were eager to push boundaries with AI but were stuck trying to figure out cloud computing, containerization, and all the rest. And that’s when it hit us: democratizing scientific computing wasn’t just a good idea. It was a mission. We needed to give these researchers a direct line to the infrastructure they needed—without the headaches.”
Favorite Memory
What has been your favorite memory working for the company so far? Rao reflected:
“There was a research group in Oregon, backed by a major pharmaceutical company, working on cancer detection—an area close to home for me and my team. They had the funding, the vision, and the drive to build AI models that could spot cancer in lab tests and CT scans. But here’s the kicker—they were advised to spend $1.5 million on a big GPU infrastructure purchase, and guess what? It was all sitting in boxes. Why? Because they didn’t have the bandwidth to figure out Kubernetes, containers, and the alphabet soup that comes with modern cloud computing.
“That hit hard. This wasn’t just a missed opportunity; it was a tragedy. The money that should have been fueling research was sitting idle, and worse, the researchers were stuck trying to become cloud engineers instead of curing cancer. We asked ourselves two questions: What if that money had gone straight into advancing their research? Second, why do scientists need to master DevOps to make progress in their field?”
“That’s when we built Project Robbie—our answer to this crisis. We’re leveling the playing field, making sure that every researcher, regardless of their budget, has the power to focus on discovery, not infrastructure. And honestly? That’s the kind of work that gets me up in the morning.”
Core Products
What are the company’s core products and features? Rao explained:
“Well, let’s delve into the heart of what we offer. At its core, Project Robbie is a high-performance computing service designed to eliminate the usual headaches associated with cloud-based research.”
“It’s tailored for researchers, scientists, and students who need to run Python and other programs in the cloud without getting bogged down by IT complexities. Whether you’re conducting AI or machine learning experiments that demand the latest GPUs—like NVIDIA’s A100 or H100—Robbie has you covered.Now, let’s talk about integration. Robbie is built to work seamlessly with the tools you’re already comfortable with. If you’re a fan of Jupyter Notebooks, you’ll be pleased to know that Robbie integrates smoothly with platforms like JupyterLab, Visual Studio Code, and Google Colab. Do you prefer the command line? Robbie offers a modern CLI that is compatible with Mac, Windows, and Linux systems.
“This means you can dive into your work without the usual setup hassles, focusing on what truly matters: your research.”
“Robbie democratizes access to high-performance computing, ensuring that cutting-edge resources are within reach for all researchers, regardless of their technical background. It’s about breaking down barriers and accelerating innovation across scientific disciplines.”
Challenges Faced
What challenges have Rao and the team face in building the company? Rao acknowledged:
“Well, let me tell you, the world of AI is moving at a breakneck pace, and with that comes some severe growing pains—chief among them, GPU availability. You’ve got researchers lining up around the block, eager to train their models and insufficient hardware. Most folks might throw up their hands and say, ‘That’s the market for you.’ But we don’t do that. We took a different approach.”
“We partnered with Boston University, a powerhouse in research and innovation. They had existing infrastructure and planned investments and needed a way to put all of it to work efficiently, effectively, and without the typical bureaucratic red tape. That’s where Project Robbie came in. It bridged the gap and accelerated access so researchers could return to doing what they do best: pushing the boundaries of what’s possible.”
“And here’s the kicker: While the hyperscalers were busy chasing the shiny object that is inference, we realized something fundamental: training is where the real magic happens. By offering a broader set of infrastructure choices tailored to researchers’ needs, we cut through the noise and got the computing power where it was needed most—fast.”
Evolution Of The Company’s Technology
How has the company’s technology evolved since launching? Rao noted:
“Well, when we first got this thing off the ground, we built on AWS as any sensible, cloud-savvy folks would do. We’d spent years there and knew the terrain; it was the logical first step. But here’s the thing about research computing—it doesn’t play by the same rules. It’s not a monolithic, one-size-fits-all operation.”
“Instead, it’s an archipelago—scattered islands of capacity, each built with different funding sources, infrastructures, and different priorities.”
“The funding landscape alone is a puzzle worthy of its own PhD dissertation—federal grants, local government programs, private sector dollars, and numerous capital investments that institutions are understandably protective of. And with that reality staring us in the face, we realized something critical: the future of research computing wasn’t in relying on hyperscalers. It was in networking and aggregating those islands, stitching them together into something cohesive and powerful.”
“So, we pivoted. We evolved. We built a front-end experience—consistent, intuitive, and researcher-friendly — because, let’s face it, scientists have better things to do than figure out infrastructure. But behind the scenes? We created a system that allows capacity to plug in seamlessly, whether it’s a university lab, a private research facility, or a government-funded supercomputer. Along the way, we tackled significant data and locality challenges because, in research, proximity to data isn’t just a convenience—it’s a necessity.”
“Bottom line? We didn’t just build a platform; we built a bridge. And that’s how you democratize scientific computing.”
Significant Milestones
What have been some of the company’s most significant milestones? Rao cited:
“Well, here’s the thing—in just one year, with a tight budget and a whole lot of determination, we built Project Robbie. Not just built it—deployed it. We partnered with Boston University, and researchers across multiple institutions are already running production workloads.”
“And let’s talk about the team. We’ve brought in heavy hitters—Dr. Smagardis, Larry Augustin, Jon Stumpf, Russ Siegelman. These folks know their stuff, and they believe in what we’re doing.”
“We’ve done all this while being smart, scrappy, and relentless.”
Customer Success Stories
When asking Rao about customer success stories, he highlighted:
“In November 2024, we gave researchers early access to Project Robbie. Within hours, they were running their workloads. A researcher at the University of Illinois called Robbie “magical.” In a matter of days, over the Thanksgiving holiday, researchers at seven institutions were finding Robbie highly applicable to their 2025 research plans.”
Funding
When asking Rao about the company’s funding details, he revealed:
“We are funded by a few angel investors committed to our mission but are not disclosing revenue metrics now. We plan on exiting 2025 with tens of thousands of daily active researchers.”
Total Addressable Market
What total addressable market (TAM) size is the company pursuing? Rao assessed:
“We believe we are addressing a market valued in tens of billions of dollars, with over 4.1 million users.”
Differentiation From The Competition
What differentiates the company from its competition? Rao affirmed:
“We are driving a durable advantage by being the easiest and most convenient scientific computing platform available for researchers.”
Future Company Goals
What are some of the company’s future company goals? Rao concluded:
“We are focused on making Robbie delight researchers working in public research institutions. In 2025, we will lay the groundwork for serving private research labs. In the fullness of time, we anticipate serving analysts and researchers across various disciplines.”
