David Abakhnikov

So we did a bit at Google and Waze.

We did quite a bit in Scholarship Owl as well for a few years now.

I mean, we leverage a lot of AI to do efficient matching and kind of like extract intent from kind of our audiences in the most efficient way.

So we've been doing quite crazy AI algorithms in Scholarship Owl as well.

only working with schools anymore is that accurate so actually the majority of our customers are not schools at all uh so i'm gonna i'm gonna uh correct you on a few things first like we're talking about at this point the scholarship pile has over 150 000 students um or uh college-bound gen z's basically um every month they sign up every month yes

wow so it's not only like high school students actually a lot of people who are already in college are looking for ways to you know pay for the next year or even things that are outside of tuition itself things like how do you buy you know gas money to get to campus or like buying a laptop that you need for school and all those things that are kind of school adjacent let's call it that way um

And today, the majority of our customers on our B2B side, like we launched Scholarship Alpha business about a year and a half ago, which is basically a platform that helps businesses, like private consumer companies.

Name one or two.

So Samsung is a customer of ours.

We work with BetterHelp.

We work with quite a few big companies.

Yeah, McGill Hill is a customer of ours.

So Samsung are looking for brand ambassadors.

So they're kind of recruiting brand ambassadors to promote their cell phones on campus or like among Gen Zs in general.

So many companies are using kind of our platform like...

the product we call scholarship campaigns which is kind of like the best of a scholarship and an ad campaign in one to do some of them you do it for lead generation some of them do it as market research they generate ugc with it like we have identified kind of four different main business objectives that companies and brands are using scholarship campaigns to achieve um

So the charge is basically cost per application.

So it's result-based cost, depending on how precise it is, how targeted it is, and what are the actions that the consumers need to do in order to apply.

So it kind of ranges...

Roughly between like $1.20 to $30 per application, depends on various metrics and so on.