And then once we have that, we're like, okay, here are the things that you can do to improve this and just be top of class wherever you need to be.

The way I think about it, especially if I'm a CEO exec kind of tuning in, You know, there's all of this, is AI hype? Is it a bubble? There was this, I think it was 24, 25 MIT case study that 95% of AI projects or initiatives don't have ROI.

And then there were like, you know, other reputable studies that said the exact opposite.

And so like, is it, you know, who's got it right? Who's not? I think the main thing thing that separates people who get value from AI, again, a very umbrella term versus not, is whether they are doing it for a particular reason.

And so we always start with a goal or a success criteria in mind, because if you don't, then it's just like, hey, I know I need to go do AI.

But if that's the frame, then what kind of AI, what for, how do you know if it's successful? So we actually use data at that level.

So if you go to, this is a free tool, anyone who's listening can go in, cscorecard.blastpoint.com. That's our totally free system that looks at every piece of NCUA data and creates an index and a scorecard for every single credit union and the leaderboard in their market and all of this stuff.

Tomar, I know you've got way more to say about this.