Daniel Chilcott

Where there is value, there's customization needed.

So the question becomes, how much can you pre-build as a platform versus what needs to be implemented specifically for a customer?

So long story short, I left that business to start the company that preceded Flowgear.

And we had a desktop app that was very lightweight by today's standard integration platform.

Sold that for a few years, worked on it over two, three years, posted a bunch of customers on it.

And then one of our customers approached me to do a deal in 2010.

And the idea then was to take

that concept and deliver that as a cloud service in its own right.

And today that sounds obvious, but back then it was actually quite unusual to have an integration platform as a cloud service.

And a lot of our early customers didn't understand why we would want to do that.

A lot of the end points that they were integrating into back then were actually on premise and needless to say, that's flipped.

So that's where we came from, this idea of creating a reusable way to integrate.

I'm very biased, but from my perspective, everything looks like an integration problem.

And to me, one of the most exciting things about AI is its potential to apply it to integration, right?

Because it's the custom glue that sits between the apps.

And you can use AI to interact with apps, but actually it's probably one of its more powerful expressions is figuring out how to glue the systems together that run your business.

So it's completely revolutionized it in short.

For us, there's really two ways that it is applied.

One is that customers are increasingly building integrations that talk to AI endpoints to make decisions around data or understand intent and conversations that are being processed through integration, for example.

But the other is using AI to actually build integrations from the ground up.