Navrina Singh

a good set of high risk applications, but you also have applications which are like really just low risk and you just want to enable AI adoption.

But at the end of the day, you have to just build trust with this technology.

And that's where we bring in our scientific measures to be able to do that.

Yeah, you know, it's really interesting because as you look at these open source innovations, especially coming out of China, one, you know, we have to be a little cautious because the security, you know, requirements of some of these open source models actually are not, they're not even meeting the requirements by most of our businesses.

So our businesses are interested and looking at them.

But they're not actively using any of these in enterprise applications because of the massive amount of security risk.

However, if you think about the other side, which is innovation and especially the latest models, I think they're the ones by Z.AI.

Yeah, the GLM, I think 4.5, yeah.

I think what is really interesting about those GLM 4.5 is the first agentic first open source model.

It has like long context window.

It has a lot of ability to plan, reason, act on your behalf.

And it's really low cost.

So imagine you're in this open source ecosystem and someone sort of handed you the keys to building really highly performant agents that can pretty much accomplish any task.

I think that innovation in itself is really exciting.

But I think the data access concerns, the national security implications,

The scrutiny required around are these compliant to our standards, our enterprise guardrails?

It is massive.

And so right now we do plan to take it through our model trust score and make a determination like what is where do they stack up?

But they are really cost effective for agent building, for developers and enterprises and innovators.

So there's a lot of excitement.