Hello everyone and welcome to At Bairns. I'm Andy Surwer and welcome to our guest, Tom Siebel,

CEO of C3 AI and a veteran leader in Silicon Valley. Tom, great to see you.

Thank you, Andy. Nice to be here. So tell us about C3 AI. What specifically does it do? C3A.I is an enterprise application software

company, and we began 15 years ago, before AWS, before the Google Cloud, for Azure, and before

the GPU building a software stack that would enable companies, we believed that the future

would be about elastic cloud computing, big data, internet of things, and predictive analytics.

So in January of 2009, we began work building a software stack that is thousands of person years of software engineering and a couple of billion dollars worth of work that provides all the services necessary and sufficient to design, develop, provision, operate, massive scale enterprise AI applications.

And then we use that stack to build 90 now enterprise AI applications

that address the value chains of utilities, energy, oil and gas,

defense, intelligence, consumer package goods, financial services,

what have you.

So we have 90 enterprise AI applications in the market today.

Right. So now it is, you know, fast forward a little bit, you know, a decade and a half.

And, you know, after, say, November of 2022, all of a sudden the world woke up and decided

that the enterprise AI was something important. And that is now going through a little bit of a hype cycle world woke up and decided the enterprise AI was something important,

and that is now going through a little bit of a hype cycle.

That big said, I don't think this is ephemeral.

I think it's legit.

And we are now finding ourselves with 90 turnkey enterprise AI applications, which I think is something like 89 more than anybody else in the world.

And the company you found in 2009 didn't start off per se about AI, although you did end up

getting the ticker AI, which is a great move. It evolved a little bit over time, didn't it not?

It did. The stack that we built, it was the same. And we were applying these basically predictive

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