Founder's Story - Why Every Major Bank Still Uses 1965 Technology: The Trading 'Rails' Revolution That Changes Everything | Ep 291 with Peter Ashton CEO of Veyra Holdings

Episode Date: December 15, 2025

In this Founder's Story conversation, Peter Ashton breaks down the science, strategy, and soul behind Veyra—a trading platform designed to close the wealth gap by giving everyday people the same predictive tools that have been exclusive to Wall Street's elite for decades. Through personal stories of transition, loss, discovery, and a bold vision for 2026, Peter reveals why the future of trading isn't about chasing algorithms—it's about understanding the mathematical laws that govern markets. Key Discussion Points: Peter distinguishes mathematical intelligence from AI—while AI predicts based on patterns, mathematical intelligence uses unchanging laws to compress data and project market outcomes with remarkable accuracy. He discovered a NASA scientist who modified 1980s aerospace missile identification systems for trading, and after initially losing money, learned traders simply want automation or clear buy/sell signals. Veyra's unconventional structure includes 9-10 co-founders (including a CEO who raised $130 billion) united by making "the unwealthy wealthy," and six months in they've built a distribution network of 550,000 subscribers positioning them for billion-dollar valuation with just 15-20,000 customers at $499/month. Peter reveals all major financial firms still run on 1965 infrastructure, creating massive opportunity for Veyra's modern "rails" built for algorithmic trading. Takeaways: Mathematical intelligence operates on unchanging laws rather than probabilities, offering higher accuracy than pattern-based AI. The most powerful technology isn't always new—1980s NASA systems become more relevant with modern computing power. Strategic partnerships and distribution channels accelerate growth faster than traditional lead generation when targeting underserved markets. The simplest products win: complexity is the enemy of adoption when people just want clear signals or full automation. Closing Thoughts: Peter Ashton proves revolutionary disruption doesn't require brand new technology—it's about reimagining proven systems for different markets. With nine co-founders who spent careers making the rich richer now united to make the unwealthy wealthy, Veyra represents a fundamental shift toward democratized wealth-building tools. As AI competition intensifies, focusing on mathematical foundations rather than trendy algorithms may prove prescient. The question isn't whether the technology works—it's whether people will embrace institutional-level trading intelligence now available at their fingertips. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

So Peter, it's really great to have you. We were just talking about how AI is basically transforming every single aspect of our life. And I can't wait to dive into what Vera is doing and how it's transforming trading. And I mean, developed by a NASA scientist. So let's just dive into this because I have to understand what is the difference between artificial intelligence and mathematical intelligence? Yeah, mathematical intelligence is essentially the laws that govern the data. So it uses math to calculate and make sure that the laws are absolute and they don't change. Then you can load the data. So it's all about data compression. And then artificial intelligence, right, essentially says based off what I've seen is likely to happen. And mathematical intelligence is essentially, these are the systems that I obey. And because of that, this has to happen. So it's not very well known. Not many people talk about it because it's not as sexy as, you know, talking about AI. But math is essentially the framework, the ground framework that we load data into to get an outcome. And that outcome is a projection of what that data set is.

And if you can compress it and use math to identify what you're looking at, you can actually predict at an incredibly high accuracy rate, like in the markets or in anything weather patterns, or it doesn't matter what it is. You have to use math, right, to take all those data sets, compress it down, and then you can use AI as an overlay. So that's really the two difference. I'm fascinated by the ability that AI can do.

I guess in this instance, mathematical intelligence, what it could do at such a high level that it's definitely smarter than I am. We may not be in what they call AGI, right? But I feel like it's way smarter than me. So when you started going from, you know, you were a really into sports division one football player and then you started getting into this and learning about mathematical intelligence. How was that transition? You know, it was a hard transition.

going from playing sports my entire life, right? And then, you know, that being done, and then you don't really know what to do. So I actually had a venture capital firm in 2020 for about two years. And my business partner was the founder of Funimation, and they created Dragon Ball Z. And so because of that and that partnership, I was able to go find really cool founders and really cool people building disruptive technologies. And I found that everybody was trying to find a way to predict the markets, right, you know, a couple years ago.

So these are people, you know, having these cool technologies to predict, you know, what Tesla is going to do tomorrow or Nvidia is going to do tomorrow. But it wasn't, no one really had the right testing or the right technology to do it. And that's when I found a guy that I ran across and he had this technology that was built in the early, mid to late 80s and he was a NASA scientist and he used aerospace missile identification technology to modify it for the markets and all you do is he built an operating system where you basically load data of a given symbol right the history of a symbol right and you can use that to predict where that symbol is going to go in the future and that was like my first like this is cool

It's crazy because most people think like, hey, I was invented, you know, Chad CBT. Not that it's, you know, been around for 70 years and things from the 80s are even more relevant now than ever. When you, what, like type of results? Like, what were you seeing? Because this is something I've been very, very interested. And I've been waiting for this, waiting for something to come out like this. I'm really big in the markets. And of course, like you're saying, you know, I, I, I've,

I've been thinking like how can AI, you know, how can automation and these things have a great positive impact for people like myself? So what type of results? What were you seeing as you started to use this technology? Yeah. It's we didn't want to look at like have AI tell me what to invest in. Like that was, that's what a lot of people are trying to do. We wanted to find and use data. So, not so much, all the data that we're using, you can see in a five minute, what's called time series stacking. So you stack one time frame on top of one another for whatever symbol you want to trade in the market. And you get a higher accuracy when multiple timeframes line up, right? And so when you can predict in the next five minutes, 15, 30, hour, you know, 240 minutes,

and you can project out in advance. And you have this like alignment it's a very, it's really weird, but it's really cool when you see the alignment. And it will tell you when to make a trade and when to not make a trade. And so we took that and I started testing it myself. Granted, in the beginning, I lost a lot of money. So you have to like test it and see what works and what doesn't work. And we found that people just want a simplistic way of tell me what to buy and tell me when to sell. Right. And if you don't want to do that, just automate the whole thing for me. So we wanted to tailor this type of trading software, not to the accredited investors or qualify clients or family offices and so forth. We wanted to tailor it to the general population.

And so anybody will be able to use our software and trade $100 or $500 or $10,000. Right? You can just load it into our system, pick what you want to trade, and click start, and it will auto trade for you. You're talking about something that has not been available to the public. We're democratizing institutional level trading products to the general population and only doing it as a subscription-based system. So we don't take any performance. It's all subscription-based.

Yeah, I was going to say democratize actually came to my mind as you were explaining it. And it gives, like you're saying, it's kind of been this thing where the wealthiest of people have access to great smart resources and people, which enables them to be able to do these things in the past. But unless you're at a certain level, it would have been hard. Right. You would have had to do this yourself. So I could see where the democratization comes into play. So something, though, that I think is very different among how you are doing business. And that's the amount of co-founders that you have. I believe it's like around 9 to 10 co-founders. And I mean, I've had, you know, I've had great experiences with just one and horrible experiences with just one.

But I think it's your CEO has raised over $130 billion on Wall Street. One of your co-founders played major league baseball for over a decade. How did this all come about? I'm very good at doing just a few things, right? And I'm trying to triple down on those things, right? And the team that I brought, they all care about this idea of making the unwealthy wealthy, right? They've spent the last 10, 20, 30 years of their careers making a rich richer. And the gap is getting larger and larger. And so when I was able to cast this vision to them of building something, something that, you know, anybody's brother, sister, cousin, you know, friends of friends can click and download and trade and make high returns, right, with no catch, just you pay your subscription fee. That resonated with a lot of these people. And so I had to, in order to scale quickly, right, I needed to bring in a team and basically gave them equity of the company

in order to help me build it. And so they all have their boundaries, right? Nobody, has ideas, but the vision is still the vision, right? You can have ideas, but you can't change the future trajectory of the business, right? Because that's what we're all came, you know, together to do. So yes, we have like nine plus co-founders, essentially. But the vision that I kind of casted, like that's the direction. We're all, we're all moving together. I mean, that's, you know, I could see the more ambassadors you have of your company. the more people rooting for you, the more people that have skin in the game. It's going to enable you, like you're saying, to scale and grow. How big do you think that this company could go?

What is your long-term vision? So when we started, we started the company six months ago, right around six months ago. And I was going to fund the business. And then it got to a point where we needed to bring on more and more people. And so we decided to do a small capital race. We decided to raise a $2.5 million at a $50 million valuation. The reason why we did that was we established a very strong distribution channel where this company, they essentially, they market and they launch newsletters, they capture customers that we can market our product directly to them. And so we decided to partner together and do an equity swap, right, to establish our distribution

channel. And we're gaining 20,000 people a day in those newsletters. So we're at 550,000 currently in our network. So if we do just a simple conversion, right, you know, our flagship product to, you know, anybody can see the future direction of whatever symbol they want to trade, right? No automation, just simple. That's $4.99 a month. So it's very, you know, it doesn't cost that much.

And if we do a 3% conversion on $550,000, that's a lot of recurring revenue. And so, you know, all we need is about 15 to 20,000 people paying 500 bucks a month and we can sell the business for a billion dollars. So that was the metric around, you know, the valuation side, how big it can go. I think it can go to 100,000 people using our product because it's just so simple, right, is, you know, I want the peace of mind knowing what my portfolio is going to do in the future. So I'll pay $500 a month to essentially have confidence that it's going to trend in whatever direction that I'm going either long or short. Yeah, I like how it's kind of sounds like you, you kind of looked at the end result and then you kind of created the math to get there. And then you're like, okay, in order for me to get to like a billion sale, I need to do all these things in the middle to get there. And if I want to do that, that means I need to partner and those things.

How is that? Because I'm with you. I feel like lead generation, like traditional lead generation is becoming harder and harder. I feel like there's just so much noise on, you know, how many LinkedIn messages do you get a day? Or now there's, you know, AI is automating so much email. So I'm getting like a million emails every day if someone try to sell something. So I feel like from a, you know, app perspective, a company that collaborating with these

type of partnerships might be the best thing that most people can do. What is your thought around, just how noisy, just all lead generation seems to be getting and how partnerships, you know, can play into being, to helping anyone who makes an app be become successfully hopeful? Each lead generation caters to a select group of people, right? So if you want, if someone messaged me on LinkedIn, like, hey, I can generate 25 leads to you. well, that's great, but they don't know what my company does or my product is.

So they just message me and message you probably and say, hey, I can generate 25. Who are those leads? What do they do? So I think you have to understand your target market, right? And most of the time, SaaS companies, it takes between two and three pivots to establish your go-to-market strategy. Right. You pivot one time, and then a lot of times you have to raise additional dollars, right, to hit that. So it's hard to find that product market fit.

And what you do is you have to talk to your customers. You have to talk to the people that are using your product to refine it and tailor it. And so we decided to go down the route of forming strong partnerships with companies to scale faster, right? So forget all the equity, forget all the revenue streams, forget all that, right? If you're building a business for enterprise value, none of that matter. as long as you book all the revenue. So as long as you can just book the revenue and drive enterprise value, it doesn't matter about how much equity you have because a small piece of a large company is better than a large piece of a small company. So that's how that's the route we went.

And it's it's going to pay off quite a lot because we're looking at, you know, January, February, March really driving in and launching these products to people and have an awesome 2026 year for us. Do you think that AI is going to allow more people to get into business? Or do you, or I guess, and or do you think AI is just going to create a massive amount of competition? I think both. With all the competition comes a lot of new businesses. But everybody is in the AI space. right they're all running on old like old traditional rails so all the AI all the quants you know there's really only been three iterations since 1822 right and so we're that third of rails I call them rails because they're built on all this is built on math so 1822 Joseph Fourier built a

Fury 8 Transform, 1965, they built a faster version, and that's been it. So all the quants, all the major financial firms, everybody in the world are using these old rails, but the original rails that were built in 1965 were made to use for computers. Well, now you have algorithmic trading systems, right? You've got, it's in this age of automation. Well, those old rails are slow now. And so that's why there's so many AI companies popping up is because there's gaps in the market. There's gaps in this.

So people are, oh, I'll just create an AI company, right, because it's easy to do. So I think there's a lot of noise, right? And if you get down to it, if you can build new rails that everybody can now use, that's faster, you eliminate those gaps in the market, which means there's less companies out there. And the markets become less saturated. man yeah i didn't i didn't even what you just said i had no idea like that's how the intricacies worked or behind the scenes um so thank you for sharing that i guess we'll see in a year two three years uh all the you know explosion of companies that started 2024 or 2025 maybe even 2026

if they're still around um as the competition plus i mean the technology just it's like you know Gemini just announced version three, which is faster than, you know, chat, jvety, faster, da-da-da. It's like every two weeks there's some advancement in some LLM or something coming out, just overall. So it's, what an exciting space. I mean, I really love what you do. I've been waiting and waiting for something to come out that you're doing that I can implement. So let's say it's somebody like myself and I want to get started. I know, like you said, it's not something.

it's a few hundred dollars and I think this could be something really beneficial for me. How can I get started? Yeah. So if you go to our website, so it's Veyraholdings.aI, you can get started. And we're going to be launching a series of products over the next six months that are tailored to the everyday person who wants to make money in the markets, right, by trading $100,000, $500,000, $10,000, right? There's a limit.

But, you know, from that side is you go. go to our website, you sign up and you have access to all of our products. You can pick and choose what you want to trade, or you can trade yourself by using our charts. It's pretty simple. Well, Peter Ashton, CEO of Vera AI, super excited. I was saying earlier, I love the background. I really thought you had a fake background. I need to get that. I need to get the TV behind me. It looks amazing. Really excited about what you're doing. I learned a lot to I never heard of mathematics intelligence. I didn't know about the rails. I'm learning a ton by talking to very intelligent people like yourself. And I'm excited. After you sell for a billion dollars,

come back and I want to know what life is like post-retirement. But thank you so much, by the way, for joining us today. Thank you. I appreciate it.