 That's a good question, because we're trying to get a lot done fast, but you can only go so fast, especially when you're looking at things that are persistent problems like data quality. I mean, because we get to the point where we're very good at putting together pilots and prototypes, but when it comes time to scale, the data becomes an issue. So it might not be the fanciest or the sexiest AI goal, but my goal is to get a whole bunch of more data engineers. We have a chief data officer over at USARAC who has been doing a phenomenal job