Karl Keirstead: Okay. Good to hear. Thanks.
Gina Mastantuono: Thank you.
Operator: We’ll take our next question from Gregg Moskowitz with Mizuho.
Gregg Moskowitz: Okay. Thank you very much. So it’s really interesting that you signed four large deals on September 30th, literally, right after the availability of Vancouver, and Now Assist and it sounds like your GenAI Tech was a clear catalyst, if not the catalyst for these transactions. So I guess for Bill or CJ, I assume these were all existing customers, but did they all purchase Pro Plus, did any of them purchase Enterprise Plus or any have been deploying your new text-to-code functionality? Just curious to hear any additional color that you might be able to share. Thank you.
CJ Desai: Hey, Gregg. Thanks for the question. I’ll take this question. I would say, just to summarize because we, in the Vancouver release, launched Now Assist for our four flagship product lines which is ITSM, HR, customer service, and Creator. So let’s start with that, and those are all resonating whether our customers want text-to-code or text-to-workflow capabilities, or they want their employees to be more productive, or they want their IT staff or customer service agents to be more productive. So, depending on the customer, and what they solving for, all of them are resonating really well. So this was driven mainly on Pro Plus, but these were Pro customers, who also bought Pro Plus. So one example, one of the customers who did buy this on September 29th, specifically, said to me, hey, CJ, you know, we had the most successful ITSM roll-out.
Now, we want to buy Pro Plus, and they’re on ITSM Pro already, and we just want our employee experience to be great, versus another customer that Bill mentioned, they said, not only we want to solve for our employees, but also our end customers. So these four specific transactions were across the board, resulting in very strategic and significant wins. As we move forward, I would tell you that what is still resonating with our customers is the speed to value. This is not something where now large language models need to be fine-tuned for one customer at a time, and the way our engineering team has implemented this solution, I can tell you, Generative AI is probably one of the best, if not the best complement I have seen to ServiceNow platform, where you can use generative AI to look up something to summarize something, and then you take action via ServiceNow platform.
Gregg Moskowitz: Fantastic. Thanks, CJ.
Operator: We’ll take our next question from Kirk Materne with Evercore ISI.
Kirk Materne: Hi. Yeah. Thanks very much and congrats on the quarter. Bill and CJ, I was wondering if you could just talk about the concept of starting to deliver AI solutions that are more vertically oriented. How far away are you from that? How much of the verticalization do you want to take on, and how much do you want to leave to your partners to sort of take some of these use cases with GenAI into verticals with specific vertical technology? Thanks.
CJ Desai: Thanks. So, first of all, Kirk, thank you for the question. When we start, and you know, yesterday we had our Board of Directors meeting and similar question was asked, we’re first prioritized on our core set of use case that cut across every single industry. We are very focused on that, we are ITSM customer service, HR, as well as our Creator offerings. As we look forward though, there are specific use cases within financial services or healthcare types of customers or even government. So, I’ll give you an example. Some of our public sector customers, they asked us, hey, CJ and the team, can you provide us a solution, that can potentially run on-prem, given the nature of that agency, and our engineering team delivered that for our public sector customer.
So, I would consider that as a vertical solution, that we had to create, for our public sector customers. But as we take it to the next level, post this core set of use cases across our four workflows, we will definitely be prioritizing financial services and TMT moving forward.
