Evan, take us on that journey.

Yeah, so this has been part of the research and work that we've actually been able to develop out over the last few years where we found that being able to focus our efforts on smaller models, to train them and to really hone them in on a a selective subject with a domain expertise, we're actually able to produce better results in a lot of instances, number one, but we're able to produce results in a way that's token efficient as well.

And so it's not just about getting the best answer for the industry that you're answering questions over and or doing activities in the industry you're working over.

It's also about doing it effectively and efficiently.

And so we don't need these large language models that know every bit of general knowledge.

We just need to be able to solve for the specific domain that we're in and really hone on those.

I want you to talk about privacy and confidentiality because undoubtedly it seems to be the biggest issue for many practitioners about what's happening to the data.

Yeah.

Evan, take us on that journey.

Yeah, so this has been part of the research and work that we've actually been able to develop out over the last few years where we found that being able to focus our efforts on smaller models, to train them and to really hone them in on a a selective subject with a domain expertise, we're actually able to produce better results in a lot of instances, number one, but we're able to produce results in a way that's token efficient as well.

And so it's not just about getting the best answer for the industry that you're answering questions over and or doing activities in the industry you're working over.

It's also about doing it effectively and efficiently.

And so we don't need these large language models that know every bit of general knowledge.

We just need to be able to solve for the specific domain that we're in and really hone on those.

I want you to talk about privacy and confidentiality because undoubtedly it seems to be the biggest issue for many practitioners about what's happening to the data.

Yeah.

What was that like? What was that situation? What was going through your head as that was happening?

yeah so i knew i got selected in the all-star game about a week ago and i told our gm i was like hey like i kind of need to be on my phone all day so i probably can't play in the game which he was fine with so i wasn't i wasn't playing um but i was in the dugout with all my teammates because if i'm being honest i thought if there was going to be a call that day it was going to be a little bit later So I was sitting in the dugout with a couple of my teammates, and I think it was during the bottom of the first inning of the game.

My phone starts ringing, and it says Arlington, Texas.

I'm like, well, this is probably the Rangers.

So I pick it up.

Their GM said, hello, Evan, how are you doing? Would you like to be a Texas Ranger? And I was like, absolutely.

No doubt about it.

Talk about just that entire journey of your collegiate career.

Was there anything you learned from last year that you hope to maybe bring into the mix for this summer?

I think it's just the mental aspect.

It's a long season, a long summer, and The grind gets intense and we just need to stay on the grind and kind of just keep chipping away slowly.

We can't get too high or get too low.

And hopefully we can just kind of coast on our own wave and get to where we want to be.

How much of this summer is going to be trying not to put too much pressure on yourself to produce like you did?

Um, it's, I think that's going to be a main thing to stick to mentally.

Just kind of remember, like, just have fun.

Evan, can I ask you the same question? How do accountants and advisors, how do they need to harness this power? How are you seeing that?

Yeah, so we're seeing advisors and accountants start to use AI for both front of house and back of house.

And so most clients will have sort of seen an accountant or an advisor ask them to turn on a recorder when they meet with the advisor or the accountant.

And the idea there is that behind the scenes they're using generative AI or artificial intelligence to transcribe the recordings and to produce notes for themselves and to then start the workflow or to trigger various workflows off the back of actually meeting with the client.

And so what the goal here is, is that they want more efficiency in the sense of they don't have to stop and take notes or fill in information while they're talking to the client, but they also want to make sure they capture everything.

And so we've seen that as an efficiency play to start off with.

And then behind the scenes, we're seeing more and more advisors and accountants use technologies that are maturing that help them with their back office processes.

How far do you think we can take this capability?