Why Our First Fund Isn’t Really Our First Rodeo

By Phillip Alvelda, Managing Partner, Brainworks Ventures

Watch the video: First-Time Fund, 80-Year Team (90 seconds)

The Long Road to Fund One

The story of Brainworks starts in 2000, long before AI was fashionable. Volker Hirsch and I met while working on industry committees to create the wireless data industry. This was the era when getting a web page to load on a mobile phone was a genuine technical achievement, when the idea that AI would transform every industry seemed like science fiction.

We stayed in touch. We introduced each other to deals. We brainstormed about where technology was heading. Over the years, that informal collaboration deepened. Volker went on to spend thirteen years as a Partner at Amadeus Capital Partners, one of Europe’s most successful venture firms, backing companies like Graphcore and VocalIQ—the technology that became Siri 2.0 after Apple acquired it. I founded six companies, won an Emmy for mobile TV innovation, and eventually ended up at DARPA directing the Neural Engineering Systems Design program.

Louis Rajczi entered the picture through a similar organic path. He and Volker had co-invested and advised each other’s portfolios for years. Louis and I connected through our shared interest in deep tech, exchanging deal flow and strategic insights since his days at Siemens Venture Capital. Eventually, Louis and I built a startup together—the kind of experience that either destroys a relationship or cements it permanently.

Ours was cemented.

By the time we decided to formalize Brainworks, we’d already been functioning as an informal investment collective for two decades. We knew each other’s strengths and blind spots. We’d seen each other make mistakes and recover from them. We’d built the kind of trust that only comes from shared history.

What 80 Years Looks Like

Combined, our team brings more than eighty years of experience in AI, venture capital, and building companies. But raw years aren’t the point. What matters is what we did with them.

My path started at MIT’s AI Lab in the late 1980s, studying under pioneers like Marvin Minsky. I had the extraordinary fortune to learn from some of the greatest scientific minds of the twentieth century—Feynman at Caltech, Sagan at Cornell, Koch at MIT. That foundation in fundamental AI research shaped everything that followed: six companies founded, an Emmy Award for pioneering mobile video distribution, and eventually DARPA, where I directed a program that turned twenty-five million dollars in investments into over two point three billion dollars in portfolio value.

That 92x multiple isn’t an abstraction. It represents companies like Paradromics, now valued at $580 million and leading the brain-computer interface industry. Prophesee, whose neuromorphic vision sensors are valued at $620 million. GrAI Matter Labs, acquired for over $300 million. These are real companies solving real problems, and I was there at the beginning of each one.

Volker’s path is equally deep. Thirteen years at Amadeus Capital Partners gave him a front-row seat to Europe’s AI renaissance. He backed Graphcore before most investors understood why custom AI chips mattered—and watched SoftBank acquire it. He invested in VocalIQ when voice recognition was still unreliable—and watched Apple buy it to build the next generation of Siri. His pattern recognition for AI winners is battle-tested across dozens of investments and multiple market cycles.

Louis brings a different lens: twenty-three years spanning corporate venture capital at Siemens and institutional venture at Forté Ventures, plus seventeen years of operational experience in Fortune 500 companies. He understands how large enterprises evaluate and acquire AI startups because he’s been on the buying side. That perspective is invaluable when we’re helping portfolio companies navigate strategic partnerships and exits.

Three partners, three different vantage points, one shared conviction: AI has fundamentally changed the economics of company building, and the venture capital model needs to change with it.

The Chemistry You Can’t Fake

Here’s what twenty years of collaboration teaches you that no amount of due diligence can replicate.

You learn who brings what. Volker sees European opportunities I’d miss—not just geographically, but culturally. He understands how to work with founders in Berlin or London or Stockholm in ways that a Silicon Valley investor never would. I see deep-tech angles he wouldn’t catch, the kind of technical nuance that comes from decades in AI research labs. Louis connects dots to corporate strategic buyers that neither of us would find on our own.

You learn how to disagree. This might be the most important part. Some of our best investment decisions came from arguments—not fights, but productive disagreement that sharpened our thinking. When Volker pushes back on a deal I’m excited about, I know it’s because he’s seen something I haven’t. When I challenge Louis’s enthusiasm for a corporate partnership, he knows I’m trying to stress-test the logic. We’ve built enough trust that disagreement feels collaborative rather than competitive.

You learn to trust the process. When Volker says a European team is exceptional, I don’t need to fly to London to verify it. I’ve seen his judgment validated too many times. When Louis says a corporate acquirer is serious, I believe him because he’s been right before. That trust accelerates everything—due diligence, decision-making, founder support.

You can’t fake that kind of chemistry. You can’t build it in a few months of fundraising preparation. You have to live it, year after year, deal after deal, until collaboration becomes instinctive.

Why Now?

If we’ve been working together for twenty years, why formalize a fund now?

The answer is that the moment finally matches the opportunity.

For most of the past two decades, AI was promising but premature. The technology worked in research labs but not in production. The companies we believed in needed patient capital and long timelines. The venture model of the era—raise huge funds, deploy massive capital, wait fifteen years for exits—didn’t fit what we wanted to build.

That’s changed. Generative AI and frontier models have crossed the threshold from research to production. The cost of training and inference has collapsed. Five-person teams can now build what used to require a hundred engineers. The companies we’re seeing need six million dollars and four years, not a hundred fifty million and fourteen years.

This is the moment we’ve been preparing for. The economics finally favor the kind of investing we’ve always believed in: deep technical expertise, hands-on founder support, reasonable fund sizes, and exits that don’t require unicorn outcomes to generate exceptional returns.

More practically, our individual careers have converged to make this possible. I finished my work at DARPA and was ready to apply what I’d learned to venture full-time. Volker had seen enough at Amadeus to know that a new model was needed. Louis had the operational depth and corporate relationships to round out the team. The three of us had been circling this idea for years. The market finally gave us permission to execute it.

The Emerging Manager Advantage

Here’s the part that surprises most LPs: being a first-time fund is actually an advantage.

We qualify for every emerging manager program. We fit the mandates that fund-of-funds have specifically designed to capture the outperformance that first-time and second-time funds consistently deliver. The research from Cambridge Associates, Preqin, and the Kauffman Foundation all points in the same direction: emerging managers generate better returns than established funds, not worse.

Why? Because emerging managers are hungrier. They can’t coast on reputation. Every deal matters. Every LP relationship is earned, not inherited. Every portfolio company gets partner-level attention because there’s no army of associates to delegate to.

At the same time, we don’t carry the risks that typically concern LPs about first-time funds. We’re not learning to work together—we’ve been doing it for twenty years. We’re not building track records—we have them, individually verified and documented. We’re not figuring out our thesis—we’ve been refining it across three AI winters and two bull markets.

Emerging manager fund, non-emerging team. That’s the combination.

What This Means for LPs

When you back Brainworks, you’re not betting on potential. You’re betting on demonstrated capability in a new structure.

You get a team with eighty-plus years of combined experience in AI, venture capital, and company building. You get individual track records that include a 92x multiple at DARPA, successful exits at Amadeus, and deep corporate relationships from Siemens and Forté. You get twenty years of collaboration history that proves we can work together through good times and bad.

You also get the structural benefits of an emerging manager: a fund size that allows us to access early-stage deals with meaningful ownership, a team hungry enough to work harder than established competitors, and the statistical advantage that first-time funds have consistently demonstrated over their more established peers.

We’re not asking you to take a chance on an unproven team. We’re asking you to recognize that the best emerging manager opportunities combine new fund structures with proven operators. That’s Brainworks.

Yes, technically we’re a first-time fund. We check every box for emerging manager programs. But the team behind it? We’ve been doing this together for longer than most funds have existed.

We’ve just never formalized it until now.

Want to learn more about the team behind Brainworks? Reach out at alvelda@brainworks.ai or visit brainworks.