AI in Root Cause Analysis to go Beyond Simple Answers

I think one thing that's also coming, and it's probably something I'm gonna be working on this year, is, actually, what do we do beyond just that simple answer of give me this piece of data? It's like, how do we find out, oh, this is the root cause of why that happened. You know, and maybe that's drilling about the different permutations of dimensions. Maybe that's doing anomaly detection. But whatever that is, I think that's coming this year where we'll go beyond that initial, like, BI type data pool, and we're going to give them, like, an answer on why something happened and maybe what should they do next. I think that's, that speaks to really why I think I spoke to a friend of mine who works in private equity who, has been really looking at the space, and his his very simple take is quite a he's quite a minimalist. So he'd always, like, boils things down to a simple answer, which is not always true. But he's like, outside of AGI, which is like everything changes, AI is ultimately just an a productivity tool. It's a tool to make difficult things easier. And what you described very well then, there's two examples, is to, like, just access to data becomes faster. Right? Nothing else that it's not like you couldn't in before get ahold of, that metric. You can always like, we already have semantic layers. We already have drag and drop tools, which actually aren't that complicated. It's just the speed at which you can get access to that particular number and not have to sift through, like, a few different definitions. What you're describing now is and that's true in problem solving as well. Like like, a human problem solving is getting numbers to then problem solve in their head. Similarly, like, it's just a speed of that process.