Jesse Zhang

And then the third tier is you're actually taking action.

So I lost my credit card.

I need a new one.

And it's actually walking through a pretty large flow.

And that's where AI agents have been really excellent because you actually wouldn't expect it to be able to do that.

And so it's able to go in.

It can be a pretty complicated process.

system where it's like okay well first i need to figure out what your address is and confirm if the address is correct and then i need to look and see hey do you want me to lock the old card like okay great i'll do that i might need to check for fraud to make sure this person is not just constantly asking for new cards and it's just like all these things stitched together that's really what makes it agentic and that's why there's been such a step function improvement with lms in the spirit of that question what could go right

Oh, yeah, that is a huge topic.

I think that's a huge part of our product.

We have a viewpoint that this data, of course, is super valuable, because it's literally what your customers are saying.

But it's very underutilized, because historically, it's a very unstructured data.

So what people typically would do is like, okay, well, every month, we have a million conversations, we'll have a full time team of 20 people.

And they're just like sampling these conversations and trying to like check on a rubric and try to compile topics and things like that.

And that won't get you so far.

But now what you can do is you can literally have a language model that reads every conversation and extract whatever info you want from it.

And so that allows you to do things like, okay, well, over time, there are these topics that people probably didn't even know about because these organizations are big.

So the people in leadership positions, they can only have such granular insight into what's happening.

But it'll literally just flag like, hey, there's this 2% of conversations where things are not really going that well.

And it's because we don't have context on this topic.