Rob Enslin: Yes, Brad. Great question. We definitely see the full platform around process mining, document understanding and communication driving a lot of that as an integrated platform as customers want to expand automation from pure RPA into broader categories where we’re able to use NorthStar. You see that in financial services, banking, in particular, both in Europe and in North America, insurance for sure, across payers and providers. in that space. Remember, we’ve also implemented go-to-market, which has got industry skills, part of it and our industry solutions team is pretty strong. So we’re seeing it in those industries. I would also — and we forgot to mention public sector, some really strength in public sector that’s driving that as well in the federal government. So we’re seeing in multiple areas. And I mentioned oil and gas as well, including other areas of energy opportunities as well.
Brad Sills: Wonderful. Thanks. And one more, if I may, just on [plan versus expand] (ph). I guess where are you in that balance? Could we start to see more Atlanta? You mentioned some top of funnel softness here but just maybe in the big enterprise or even medium enterprise, could we see some progress with more land accounts going forward?
Rob Enslin: Yeah, we’re working — I mean, we see — obviously, we see — we like we are on the $1 million ARR and above in the $100,000 ARR and above, and we continue to work on the distribution model in this space, and we’ll continue to treat some of those models that we’ve had previously in that space. Ashim?
Ashim Gupta: Yeah. I feel like the quality of what we have is much better. When we’re looking at the customers and the logos that we’re acquiring, so our enterprise presence or enterprise connections, I think we’ve seen meaningful progress there. We talk about kind of smaller mid-market, emerging enterprise, we say that in various episodes. I think that that particular segment is going to be more impacted by the variability of the macroeconomic conditions. So I think, Brad, the area for us is not a quantity play necessarily that’s going to churn up and down. It’s quality and then where we want to get even better and better is then advancing those quality customers up through better and better sales specialists to increase our expansion. That’s kind of how we are measuring it and how we look to it.
Brad Sills: Great to hear. Thank you so much.
Operator: Our next question comes from Terry Tillman with Truist Securities. Please state your question.
Joe Meares: Hi, everyone. This is Joe Meares on for Terry. Thanks for taking the questions. You mentioned the SAP relationship briefly in your prepared remarks. I’m just curious how they’re helping you on the go-to-market side? And is there any way that you can quantify early benefits from the partnership?
Rob Enslin: Yeah. multiple aspects. One is working with ASIs. They — we also have joint teams working on joint accounts. We’ve created a common architecture to present to our customers. We’re busy going through the enablement of both organizations. And that will continue to expand through the year. So we’ve had multiple significant discussions between both companies, and we feel really positive around the enablement. And right now, it’s all about enablement and positioning with customers and working with the ASIs to incorporate the automation in how they go to market as well. And we will see the benefits of that SAP partnership in ’25 for sure — in FY ’25.
Joe Meares: Great. And then just as a follow-up, is there any way that you can quantify the impact of the 10 solution accelerators you have out there that they’re having on the implementation cycles or ROI for customers? Thanks again.
Ashim Gupta: We don’t disclose metrics around individual solutions or product lines at this time. What I can tell you is we continue to monitor the applicability in the sales cycle and customer uptake, and we’re really pleased with the feedback, but we don’t provide quantitative metrics or disclose them.
Joe Meares: Thank you.
Operator: Our next question comes from Fred Havemeyer with Macquarie. Please state your question.
Fred Havemeyer: Hey, thank you. I have a single set of questions, but two parts here. One for Ashim, one for Daniel. I’m thinking, Dan, since we last spoke, I’ve had a lot of fun working with training up various different AI models of a convolutional one working on a workstation right now. And I think what struck me through some of this experience is how many of these models are getting more and more efficient, especially being deployed in the Generative AI space sufficiently being deployed on smaller and smaller sets of hardware. So I’m curious kind of two parts here. Firstly, perhaps for Daniel, is there an opportunity in the future perhaps for more of the Generative AI workloads? We shifted towards the Edge rather than using, say, like centralized APIs from some of the hyperscalers out there?
And then secondly, for Ashim, while we’re in this phase right now of having Generative AI primarily hosted and available through hyperscalers, is there any impact on the gross margin line at all to some of the products that are being offered as they’re run through these APIs? Thank you.
Daniel Dines: I think that’s a very interesting question and perspective about what the future of GenAI. We are experiencing quite a bit with Llama II at this point. And eventually, I think for some of the use cases, like the one in [Migma] (ph), we would love to be capable of deploying this on the edge because we’ll significantly reduce the cost, the bandwidth required, time to value, and it’s kind of premature at this point to really understand if we can run a significantly large model like, I don’t know, 13 billion parameters on the Edge. But certainly, it’s an interesting way to look forward.
Ashim Gupta: And then Fred, like, when I look at it, our gross margin is 88%. We talked about 85% and long-term model of greater than 80%. These are numbers that we’ve done there. I think right now with what we see in front of us, we factored the uptick of both the cloud and AI capabilities in there, and we’re in the early days of pricing on these areas, and those are going to be factors for us to consider in terms of workloads and where they are. So we look at this as developing tremendous value. And so it’s not really a threat to our margins from that perspective right now, and we feel very good about the way we’ve modeled that going forward.
Fred Havemeyer: Thank you. And then if I could ask one more, I guess, a third question here because Rob, I don’t want to fret about you at all. I don’t want to leave you unquestioned. I’d love to ask as you’re having conversations with executives that are considering adoption of broader suites of AI solutions, just how are you with UiPath considering and addressing privacy concerns, data governance concerns the like, especially with respect to Generative AI?
Rob Enslin: Probably a question for Daniel. But I would tell you that generally, our security folks will take, our CISA will take — and CISA security team will take them through how we deal with data security, data privacy, had lands in multi-tenants where the testing takes place and explain to them how we go through it in in a way that we would normally go through any kind of sales. But so far, we’re handling it, I would say, not with the ease, but in very detailed discussions, and we have detailed road maps around that as well.