Martin Casado

there is a new reason to have all your data in one place, which is AI agents need context.

If you don't do that, then it's sort of like using ChatGBT from before ChatGBT was connected to the internet.

Postgres, contrary to popular belief, is very old technology.

It is not a good database simply because it was written a long time ago.

It has a lot of technical debt.

The bigger threat is that AI-native companies will just zoom and catch up to the established incumbents and maybe be better.

So Fivetran, we've been around for a while.

We've been around since 2013, had customers since 2015.

2013?

Yeah, exactly.

I've been doing this long enough that a slide about the past state in my own slides is the same slide as the future state from when I started.

But

What Fivetrain does is we help our customers get all of their data from all their systems like Salesforce, NetSuite, all their SaaS tools, their own databases into one place.

Getting all your data in one place, it's not a new thing.

Businesses have had the need to do this since filing cabinets.

The primary reason...

historically, that people used Fivetran to get all their data in one place was to do business intelligence, was to build reports about things like what's your revenue, what's going on with your sales team, what are we forecasting for this quarter, all those great things.

And now there is a new reason to have all your data in one place, which is if you want to use AI agents in business,

AI agents need context.

And it turns out that the same data foundations that work well for business intelligence and reporting with some additions and some modifications actually can work really well for AI agents as well.