Rob Heiser

We have 24 people.

I love small.

It's the family.

Are you kidding me?

This is the best time.

Uh, everybody's in the Ohio office.

We have one person that's a little bit remote.

Uh, sales and I'd call it client services.

So both inside and outside, inside and outside sales probably makes about, uh, eight of them.

Uh, rest, the rest is either, you know, we have a CFO, something like that, but most of the rest is, uh, both.

uh engineers uh i'll call data or etl data sciences and we we're very big in terms of library science

Well, the big thing today, we talk a lot about what's happening in data science is you're taking big data sets that really don't make a whole lot of sense, right?

And you're trying to make sense of what that data is by using AI.

What we're doing on the library side is we're categorizing all that data.

So we're seeing billions of transactions a year.

And so we see those transactions and we're categorizing them both by the technology that we built, but also

It always fails out to if we don't understand what that exact transaction means, because this is what the value we bring to our clients, our customers, is that we categorize that based on real people, real people looking at it.

And so we have what's called these variations of transactions.

So if you ever look at your bank statement and you're saying, oh, I know this is Target or I know this is Starbucks, but maybe I don't remember what this one was, right?

That description of that merchant, that interaction where you swiped your card or