Anish Acharya

So if you're an on-prem database and there's no engagement layer and there's not a lot of human workflows built around the so-called system of record,

I think that you actually are at some risk.

If you're the core system for a bank, you've got thousands of transactions per second.

You've got hundreds of humans that interact with you.

You have this incredible demand for accuracy.

I still think that you're sort of as good as gold in terms of defensibility.

Yeah, I'll give you the opposite.

I was always skeptical of the sort of data network effect.

You know, that was like this thing that got thrown out a lot when you couldn't think of what mode to say.

But today, if you look at companies that have proprietary data sets, and not just proprietary, OpenEvidence is a good example of this, but live, proprietary and live is a very, very powerful mode.

When you say live, what do you mean?

Like your health data, for example, right?

That's our sort of live and ever-changing source of data.

Now, there's a question of how proprietary can that be?

But once you actually have data like that, or perhaps live data about a product that's running, now you can put a relatively commodity model in front of it and get much better results than the most cutting edge model that does not have access to the proprietary or live data.

Handheld, yes.

Yeah, so here is actually where I think there's nuance in the margin conversation that's important.

OK, so if you look back at any time you've gotten, we should talk about, you know, the bubble that doesn't exist or perhaps there is some sort of subsidization and distortions happening in the market.

For the record, I don't believe we're in that period.

But I do think that any time you have this sort of superheated markets, you have some distortion.