Katie Bianchi

Yes. And I think for us, what's been really interesting is that AI and this sort of revolution has made tight collaboration between go-to-market, CX organizations, product and IT. It's an absolute non-negotiable. One example I would give you is really how we're working to unify data capture and automated workflows across both pre and post sales.

Yes. And I think for us, what's been really interesting is that AI and this sort of revolution has made tight collaboration between go-to-market, CX organizations, product and IT. It's an absolute non-negotiable. One example I would give you is really how we're working to unify data capture and automated workflows across both pre and post sales.

So if you think about a historic motion between pre and post sales, pre sales captured all the technical requirements and all the outcomes and all the use cases. They stored it in a system or they didn't. We didn't have access to it and deal closed. Post sales would pick it up and start all over again and frustrate the customer by asking the same questions.

So if you think about a historic motion between pre and post sales, pre sales captured all the technical requirements and all the outcomes and all the use cases. They stored it in a system or they didn't. We didn't have access to it and deal closed. Post sales would pick it up and start all over again and frustrate the customer by asking the same questions.

So if you think about a historic motion between pre and post sales, pre sales captured all the technical requirements and all the outcomes and all the use cases. They stored it in a system or they didn't. We didn't have access to it and deal closed. Post sales would pick it up and start all over again and frustrate the customer by asking the same questions.

And they'd have to start from scratch in terms of building a technical strategy, which takes a ton of time, redoing work, missing context, etc.

And they'd have to start from scratch in terms of building a technical strategy, which takes a ton of time, redoing work, missing context, etc.

And they'd have to start from scratch in terms of building a technical strategy, which takes a ton of time, redoing work, missing context, etc.

And now as we're building this interlock between pre and post sales with AI driven flows that are going to carry that data from pre sales to post sales and use it to recommend deployment strategies that are tailored to each customer, you're eliminating handoffs. You're reducing friction. You're accelerating time to value.

And now as we're building this interlock between pre and post sales with AI driven flows that are going to carry that data from pre sales to post sales and use it to recommend deployment strategies that are tailored to each customer, you're eliminating handoffs. You're reducing friction. You're accelerating time to value.

And now as we're building this interlock between pre and post sales with AI driven flows that are going to carry that data from pre sales to post sales and use it to recommend deployment strategies that are tailored to each customer, you're eliminating handoffs. You're reducing friction. You're accelerating time to value.

And for our customers, it's going to mean a more seamless, much more personalized experience from the first conversation that they have with us in the pre-sale to the time that we get them to value through a full deployment. And honestly, I do not think that that level of integration would have ever happened without AI forcing us to really think about

And for our customers, it's going to mean a more seamless, much more personalized experience from the first conversation that they have with us in the pre-sale to the time that we get them to value through a full deployment. And honestly, I do not think that that level of integration would have ever happened without AI forcing us to really think about

And for our customers, it's going to mean a more seamless, much more personalized experience from the first conversation that they have with us in the pre-sale to the time that we get them to value through a full deployment. And honestly, I do not think that that level of integration would have ever happened without AI forcing us to really think about

the end-to-end process and the data capture that's required and what we want to build towards in terms of the experience that we want to provide for our customers.

the end-to-end process and the data capture that's required and what we want to build towards in terms of the experience that we want to provide for our customers.

the end-to-end process and the data capture that's required and what we want to build towards in terms of the experience that we want to provide for our customers.

I'll give two examples. I think one, if I'm specifically looking at the support use case, the way that we've changed the process is that number one, based on all the inputs we're getting through the case lifecycle, we're driving certain data inputs at case closure. And we're summarizing all of that

I'll give two examples. I think one, if I'm specifically looking at the support use case, the way that we've changed the process is that number one, based on all the inputs we're getting through the case lifecycle, we're driving certain data inputs at case closure. And we're summarizing all of that

I'll give two examples. I think one, if I'm specifically looking at the support use case, the way that we've changed the process is that number one, based on all the inputs we're getting through the case lifecycle, we're driving certain data inputs at case closure. And we're summarizing all of that