The Exchanges

Q Brent, and then seeing if it actually gets delivered, and then applying, you know, you know, multipliers per developer because, you know, this one, it's actually one and a half times what they say, and this one, it's actually their way faster than what they say. How do you, I mean, I could never figure that out manually with a human. How do you figure it out with artificial intelligence?

A So it actually took us about two and a half years, um, to just figure out our data structure. So, um, so Sayed, because he's a roboticist, he built a team of, um, there were the, you know, mechanical engineers, machine learning engineers, and as a team, what we did was we figured out that we could actually scrape the open web, um, essentially open source platforms that already have existing code and existing software projects. So we used roughly about our early data set included about 5000 software projects, and we use that to train our system to understand that, okay, with an iOS app, if the iOS app requires a two sided marketplace, here are the typical milestones, tasks, and this is the typical timeline. So it took us a while to actually like get data that was clean and then, you know, to figure out how to scrub that data and build up the platform. But what we did during that time was as we were building out the, um, the overall neural network, We were doing a lot of things manually, um, at the beginning. So we actually brought, um, product managers on board on our team. We had about 10 to 15 contractors early on that were actually, you know, running the scoping process. And we were comparing results between, uh, what, what the AI could do versus what, um, what human product managers, um, were mapping out. And what we found was that there was about 70% of, um, of An actual pr…

AI assessment note: “we used roughly about our early data set included about 5000 software projects”

Q So I want to talk more about that in terms of churn. Cause typically projects like they're not, sometimes they're not always going on. Talk about that in a second, but first I'm curious about the breakdown. So if you look at your past 12 months, would you, what percent of your revenue would you say is from placing the talent Versus the annual fees that are pure SaaS?

A That's a great question. So about 60% of our revenue comes from placing the talent, and about 40% is coming from the software. We do think that, you know, those metrics may change over time, but I think what's more exciting is now, when we first started with Enterprise, we were kind of going on a one-off project basis, and Well, what's happening was, so for example, with like the likes of Cisco, um, we were doing multiple projects, um, within like one enterprise, but it was with different teams. So what we're excited to do now is, um, get into multiple teams from the get go. Um, and the way we're doing that is we're, we're essentially like doing these pilots where we're able to prove out the value, um, with like an initial five figure deal. And then from that move into a six figure deal when, you know, they have the confidence to really like Scale it up. And so that's what we're pursuing, like, specifically this quarter and next quarter.

AI assessment note: “about 60% of our revenue comes from placing the talent, and about 40% is coming”

Q I think of like the closest thing to you that I have personally used, I think of top towel, which is just hiring developers. I still have to manage scope and everything. I don't think they have AI on the backend. So how do you, How do you manage to convince top tier development talent to work through your platform versus top towel or versus going in-house at a company?

A Yeah. So, you know, what we found, so I actually personally was a freelancer on these platforms, me and say it both of us. So what we did was, um, we, we were, we were freelancers on those platforms for about two years or so. Um, what, 1.5 to two years, we found that the average developer was being paid about 200 dollars on the leading freelance marketplaces like Upwork. And they had to, uh, 200 dollars for a small widget project. Okay. And so they would need to take at least 10 to 18 of those projects in a month so that they could make like a sizable income. And we're like, okay, what if you could make that sizable income with just one project that was typically with like a larger enterprise and had higher payouts? So that was like our pitch to developers when we were building out the marketplace very early on. And then the other part of it was also equal pay. So one of the things we really believe in as a company is we wanted to build a meritocracy where Folks that didn't have, um, you know, computer science degree from an Ivy league university could join Tara, uh, but on the basis, purely on the basis of their code. So we would actually look at their existing GitHub and other platforms to give them a score.

AI assessment note: “that was like our pitch to developers when we were building out the marketplace”

Q Why do you, the ones that are not enterprise, why do you not call them enterprise? Is it just a price point thing or it's the nature of how they use you?

A The nature of how they use us. So, you know, they don't need like, you know, enterprise level security. Um, and they're typically, we classify them as mid market. Um, and, uh, and, you know, with mid market, we've seen that the need is, is primarily, and, and, you know, some of these are like sporting goods companies. Some of these are, they're not your typical technology companies or it companies, but they need to innovate and iterate on, uh, on their existing products. So for example, like a sporting goods company wants to make, um, Jersey designers, like online, uh, online designers, you know? So So we're seeing that the need is, um, uh, is, is pretty prevalent, not only in tech companies, but also in companies that are kind of like, you know, wanting to innovate.

AI assessment note: “The nature of how they use us. So, you know, they don't need”

Q What do you see yourself being though? Like, I mean, cause look, top towel is hitting you on just the marketplace side. That's all they do. And then there's other companies that just do come into AI machine learning, that kind of stuff. You're fighting two wars. I mean, is there one you're generally trying to go more towards?

A I think our goal is to essentially become an end to end platform because at the end of the day, what, what, how we look at our company is that we look at the product being at the center and the core of just about everything that the company that our customers have to do. So if you place the product at the core, then hiring analytics, um, uh, API integrations, and as well as the talent that's assigned, a lot of that is, is, uh, is a part of the whole product equation. So because we look at it, um, we look at it from that perspective, we believe that more and more enterprise companies are now going to start organizing their Teams based on, based on products. And as they become more agile, their need for software development becomes more extensive.

AI assessment note: “our goal is to essentially become an end to end platform”

Q I'm so curious about so many things ranging from the green card to the company to everything, but let's focus on the company. Tell us what you do and how do you make money?

A So, um, my co-founder Sayed and I, we started Tara Intelligence, um, to essentially help, uh, founders, product managers, improve the product development process. Um, and so Tara uses artificial intelligence to essentially map out a product milestones. Um, and it also assigns contractors that are freelance developers to actually execute on these milestones. Um, and, and, you know, one of the reasons why we started the company was because we personally had, you know, we saw a lot of issues with the product management process as it was. And, uh, and we personally felt that, uh, you could essentially apply AI to this field specifically by scraping projects off the open web. So my co-founder is a roboticist. Um, I'm a financial analyst and, and we kind of came together because we met freshman year of college, but yeah.

AI assessment note: “Tara uses artificial intelligence to essentially map out a product milestones.”