Seth Hastings - Aeon

No, that's really cool.

Let me step back a little bit because that was a fantastic synopsis, I think, about how most businesses start, right? You have an idea, you identify a problem, and then you discover, hey, is this worth pursuing? And I think a lot of people wouldn't have pulled back like you guys did.

I think, you know, it's hard to know when you're maybe wrong or not like in the right spot.

Um, but it sounds like you guys did and pivoted into something where you saw there was some room for growth.

Right.

Um, which I think is really cool.

And if the fact that it's in your backyard, it's even better.

So just for, you know, to zoom out a little bit.

So Eon, is it an ERP like in the, the oil and gas industry or is it manufacturing in general or how would you describe it? Yeah.

So basically our approach

is to automate and make more efficient a lot of these outdated processes in the energy sector broadly, but starting with oil and gas.

So oil and gas is surprisingly immature in its processes on the technical side.

And this actually has a really clear reason, which is the cyclical brain drain that happens when the oil price drops and people get laid off.

So we have this kind of whole industry environment where many of the tribal knowledge and organizational how-to is concentrated into just a couple of people, and those people are retiring out.

And as this continues to happen over a few decades, because the industry stays operating in this mode of cyclical layoffs, the processes never mature.

And so you can have an oil exploration company like one we're working with that gets dozens of documents a day from their drilling partners that they're not able to take the time to read and analyze and understand in action.

Wow.

Instead of having two or three engineers spend eight hours finding documents, putting them together, making a basic summary, trying to strategize from there, what if we already had all of this in our system and it could quickly output an analysis to say, hey, here's how we make the improvement, here's where the delta is, and then you can post-test as you go without any extra hours.

That's kind of the core value proposition of this first product.

And it works because these are tasks that lend themselves both to traditional tooling for things like statistical analysis, but also really heavily to AI to be able to intake disparate sources and turn that into database solid actionable evidence.

So we built up kind of this orchestration workflow layer that we can then apply to a bunch of different types of solutions.

So we're also looking in the manufacturing space.

We have an early design partnership over there.

But the general idea is that we will take this common engine and then use it to build out more solutions across the space.

There's a few more things in there, but I'll hold off some for later.