... better insights, more information, you know, to, to the pharmacist and you guys as, as advisors in that area.

Sure.

Yeah, so we end up working with large data sets, whether we're doing an analysis or, um, somebody's asking us to do a consult, um, maybe we're doing a profitability review, something like that.

With some of the shifts that we've seen, whether it be the MFP program or just people adjusting to point-of-sale DIR, there's a lot of questions in and around cash flow.

For us in general, there's questions around pricing of inventory when we do account for, say, a transition of ownership or if we're doing a, uh, an adjustment back to a particular period in time, end of the month or something like that for somebody's accountant.

Um, and when you get 100,000 lines of data, you know, there can be outliers, there can be issues, there can be missing rows, and it's just not something that a, it's not something that a person or an individual can sit there and pore over for hours and hours and hours.

And being able to use just currently the first thing that we did with it was, "Hey, help us look for outliers.

So Jared, when it comes to implementing perpetual inventory, are you noticing, um, how AI can kinda help with that, uh, process in a pharmacy a little bit more? I don't know if you've used, if you've been using AI to help with, like, perpetual inventory implementation or whatnot.