Well, the way we use AI and have for a long time, it's really been part of what we do for many years. It absolutely does. The concept of LLMs, however, which is the current range with AI is a bit misleading. In other words, you have to detect what's wrong and how it got wrong to be able to fix it. I didn't -- there's 3 steps. I'm sorry, and let me back up and see if I can make this clearer than I have. Most people who will try and do Traceability will not even see that they have errors. It's not detectable by looking at it. You actually have to have a deep database to check every field in every record and determine whether or not in the context of that record is it a correct reference. So it's a little bit, as I mentioned earlier, it's a little bit like the post office. You could have a note, let's say, you sent a note to me, and that note said Randy, I now believe that the earth is flat, okay. Now you take that little note, you put it in an envelope, you look it, put a stamp on it and take it to the post office. That's like EDI. Here's what the post office does, though. The post office looks at the size of the envelope and says, okay, that's a legal-sized envelope. It has enough postage, it weighs it and checks the postage and then it says it's got a ZIP code, good to go. That's what EDI does. It's just the transport mechanism. Meanwhile, inside your envelope is an untrue statement. The earth is not flat. And therefore, it's not detectable in the context of EDI. We detect it. We've tested hundreds and hundreds, actually since we have 2 million records now. We've tested about every combination and permutation of type of error that you can imagine. So step one is can you see the errors and AI can help us with that. But here's where we've gone because we realized what a problem, the errors themselves are. If every day you are a supplier and you send out 1,000 files and as we found half of those are erroneous, half of them are erroneous. And we sent you a message and said, here's the 500 files that are wrong, fix them, you would have to hire an army. Everybody would hire everyone they could find to check for errors and fix it. So we've developed a way, again with AI, to not just detect the errors, but in essence, autocorrect them. So we're a little bit like spellcheck and auto correction. And that's an enormous difference. And our system is AI-based, but doesn't, in any way, rely on what today's people people would call a large language model. It's a different -- it's AI for sure, but it's not large language Model. Sorry, long-winded answer, but hopefully it was complete.