And if you can combine that with some of the agility that these, these smaller competitors have, like, you can get faster, faster than they can get decades of data," was my point to them.

Yeah, definitely.

I think a lot of organizations are really seeing the value within data products, especially when you can tie in that business context and really model out, um, through semantic modeling the business context.

And like Larisa was saying, as an outport, and now we're seeing it as data agents as the outport, whereas before it was just more concretely, um, reports and dashboards which were predefined questions that were being answered.

And now organizations are able to go and ask the data directly whatever question that might come to mind, and I think that's where it's becoming super important of the idea of garbage in, garbage out that you've probably heard a lot of.

If that data is for lack of a better word, garbage, then the AI is just going to amplify that, and, um, whoever's asking the data that question, you would before be able to mask it through, um, just specific reports and being able to show exactly what you wanted from that data.

But now with people being able to access it, it really opens up a whole new landscape, um, which is both exciting that you can really understand the data that you have and work from that data, but also, um, it brings up that idea of really having a grounded foundation within the data as well.

What are both of you excited about in, in the data space, the AI space? Like, you know, again, it's sort of building off my last question, but, you know, what, what's got you jazzed? Like what are you like, "Man, I can't wait till people see this"?