So can we drill in, Vince, to those costs? Can you walk us through the life of a copy, a pipeline per target, journaling, logging, latency, MIPS, data drift? Where does the time and cost actually go?

Yeah, and it's all of the things that you have on the slide here.

I mean, generally, we've spoken to many customers and in large sites, it's not uncommon to have dedicated teams to doing this sort of thing.

And every time they get a request, I need this data in this application, they start with, pretty much a clean sheet, understand the data, build some type of ETL process around it.

How do they take the data, understand its structure, get it in the format that the target expects? There's a I mean, I'm not necessarily sure I'd call it programming, but it's definitely a lot of work.

And that alone, I mean, we've had customers tell us that it takes weeks to months to figure that part out.

And if you think about doing that for hundreds or even thousands of mainframe data sources, you kind of see the investment it takes to do that and keep up with change.

So let's talk about, you know, our patented innovations at Virtual Z and what you've really designed, Vince, to take that copy out of the equation.