Andy Halliday

People having to switch between SaaS tools, the things that they've been accustomed to working with, and separated AI tools.

So this is different.

Like I'm using ChatGPT over here, but I'm also using Intact for our financial ERP.

And you have to kind of bounce back and forth between those two.

Export a CSV file, put it over here.

All of that is creating friction in the workplace.

And there has to be tighter integration across SaaS tools and those AI tools.

Yeah.

Well, that reminds me of the former business intelligence architecture, like, for example, Looker, which is a Google business intelligence platform.

It's basically, it was, and I'm sure it's more advanced now, it has AI tools built into it and so on.

But

One of the first requirements of using Looker effectively is that you have to do ETL, Exchange Transform Load, all your data from every different source into a single Redshift or at least MySQL database.

So everything's in a single database.

I'm going to have many, many, many tables with multiple joins and so on.

But it has to go into one place first.

And then Looker sits on top of that as the intelligence layer, the business intelligence layer, that allows you to generate SQL queries in a simple kind of spreadsheet way.

Now I'm sure AI is that new intelligence layer.

But the first thing you have to do is you have to do the ETL process to get it all into one place.

All right, well, co-work is going to make it easier for all of us to experiment with those things.

On a personal, professional level, I would...