Patent Attorney and Founder
On this episode of the Bold Inventor Show, J.D. Houvener sits down with Zak Green, founder of Veyra and a veteran of global asset management, to explore how decades in finance led to cutting-edge innovation in AI-driven trading. From early patent struggles to building autonomous investment systems, Zak shares a rare behind-the-scenes look at how invention happens inside financial markets, and what today’s founders can learn about timing, strategy, and protecting their edge.
J.D. Houvener:
Hey everybody, welcome to the Bold Inventor Show. I’m your host, J.D. Houvener. We’re live every Wednesday at 12 noon Pacific and 3:00 PM Eastern.
We’ve got a great guest today, Zak Green, who’s joining us to talk about market prediction technology and innovation in financial services. Before we begin, a quick reminder: this is a public forum. Please don’t share confidential information, and nothing discussed here is legal advice.
Zak, welcome to the show.
Zak:
Thanks for having me. It’s great to be here.
J.D. Houvener:
Let’s start with your background. You’ve spent a lot of time in finance, how did that lead to founding Veyra?
Zak:
I was born and raised in Manhattan and spent over two decades in asset management. Starting around 2002, I led global liquidity businesses, including at a firm called Reserve Management, the company that created the first money market fund back in 1971.
Interestingly, they always regretted never patenting that innovation. That stuck with me early on.
J.D. Houvener:
That’s a powerful lesson right there. So how did your own invention journey begin?
Zak:
It came from a real problem I saw in the marketplace. I was working with large institutional clients, companies like sovereign wealth funds and major corporations. They all had strict investment guidelines.
The challenge was that funds are made up of hundreds of securities, and those holdings change constantly. So even if a fund initially met a client’s criteria, it could fall out of compliance without them realizing it.
I built a system to solve that.
J.D. Houvener:
What did that system do?
Zak:
It allowed investors to pre-select specific criteria, like minimum fund size, credit ratings, or restrictions on geographic exposure, and then automatically monitor those conditions in near real-time.
If a fund fell out of compliance, three things would happen:
- The investor would be notified immediately
- The investment would automatically redeem
- The system would reallocate funds into the best-performing compliant alternative
It started as a risk management tool, but it also became a way to optimize returns.
J.D. Houvener:
That sounds a lot like what robo-advisors eventually became.
Zak:
Yes, and my patent actually predates the rise of robo-advisors by a few years. My first filing was in 2007.
J.D. Houvener:
Let’s talk about the patent journey. What was that like?
Zak:
It was a long process. It took about five years to get the first patent granted, with a lot of back and forth. I later secured a continuation patent, which moved faster.
But monetization was the real challenge.
J.D. Houvener:
Why was that?
Zak:
Two reasons. First, working at large financial firms meant I couldn’t actively commercialize the patent, it was considered an outside business activity.
Second, the legal landscape changed significantly with the Alice decision. That made it harder to enforce software and business method patents. Even when attorneys believed there was infringement, many were hesitant to take the case.
J.D. Houvener:
So what changed?
Zak:
Eventually, with fresh perspective and the founding of Veyra, we found a way to apply the technology differently and incorporate it into our business.
J.D. Houvener:
Let’s talk about Veyra. What are you building today?
Zak:
Veyra has two main components.
First, we have a proprietary trading platform using fully autonomous algorithms to trade futures, things like gold, S&P, and Dow futures.
Second, we’ve developed a proprietary version of a mathematical framework called the Fast Fourier Transform (FFT), originally conceived in the 1800s and modernized in the 1960s.
We’ve enhanced that architecture to process massive amounts of data quickly and generate more accurate predictive outputs.
J.D. Houvener:
What problem does that solve for users?
Zak:
It removes the need for manual decision-making in trading. For example, an investor can opt into a system where their capital automatically shifts between strategies based on which algorithm has the strongest predictive signal.
It’s designed to maximize performance while reducing human limitations like speed and bias.
J.D. Houvener:
That’s powerful. So what’s your current IP strategy?
Zak:
We’re taking a hybrid approach. We plan to file patents around certain process elements, but we’re keeping key components, our “black box”, as trade secrets.
We don’t want to disclose everything publicly, especially what we believe gives us a competitive edge.
J.D. Houvener:
That balance makes a lot of sense, especially in fast-moving tech spaces.
Zak, thanks again for joining us and sharing your journey, from institutional finance to AI innovation and patents. Really valuable insights for inventors and founders alike.
Zak:
Thanks, J.D. I appreciate the opportunity.
J.D. Houvener:
And for those watching, if you have follow-up questions, feel free to reach out to Zak directly at:
[email protected]
Thanks everyone for tuning in to the Bold Inventor Show. We’ll see you next week.