Matt Price

You know, this is not like, you know, it's making stuff up, but...

I would say usually it's an inaccuracy based upon the inaccurate knowledge that's been provided.

That makes sense, yeah.

So we do it firstly by testing and training.

We have a lot of tooling that brings in, curates knowledge, and that's where we can help companies because we have a lot of people who can help do that and help them clean up as well as tooling.

So we can move very, very quickly.

Typically, we're live within 30 days from scratch with a customer with an AI system.

Wow.

The other thing that we do then is constantly calibrate, as I mentioned.

Every interaction is looked at and tuned and corrected and scored.

So we have people and AI doing that at the same time.

So typically, the accuracy continues to improve and increase.

Can we get to 100%?

Possibly if the world doesn't change around us, right?

But typically products change and external factors change and new things are being introduced all the time into the system.

And, you know...

You know, don't account for external world events that might, don't account for things like tariffs or things like that.

So, you know, obviously that's where this fine tuning of a system and continuous management is really important because things just don't stay still.

Our teams, we take customers, many of the times we're actually managing just the labor side things for them, and then we upgrade them to our AI native contact center.

As part of that process, pretty much every role that's involved from the human side gets repurposed and retrained.