Israel Krush

That's where I met my co-founder, Rom, who did his master's in computer science.

I like to say we actually met in a machine learning class, nothing to do with the MBA, just something that I was able to take because of my background.

And that's where HIRO was originally originated.

That's cool.

Yeah, so I think that when we started the company, and again, almost eight years ago, we had an hypothesis, which is AI agents are going to be all around us.

Today, it might be obvious, you know, but we're still not there.

But it's obvious that this is the direction that we're heading to.

But the less obvious thing was that it's going to be very hard for large enterprise organizations with lots of data from various data sources to deploy and maintain those AI agents.

And again, I connected to it mostly from the technical background.

thinking about the intent classifications and again, machine learning models and why the deployment is tough and why the integration to legacy systems or to the knowledge is going to be an obstacle.

So really thinking about it from a technical perspective.

And like a lot of early stage founders, we did like the lean startup methodology, which is basically build, measure, learn, right?

And as part of that, we would speak with anyone who would be willing to speak with us.

So we spoke with CIOs from academic medical centers and health systems, but we also spoke with CIOs from banks and travel agencies and government clients.

And we've realized also that in regulated industries, the complexity level is even higher because of regulation, right?

Which you can probably connect easily.

And I think it wasn't before,

So end of 2022, where ChetGPT, let's call it the ChetGPT boom, right?

All of a sudden, everyone knows what the large negligence model is.

Everyone are using like a ChetGPT application, right?