Elastic NV at Goldman Sachs Communacopia & Technology Conference Transcript

The following is excerpted from the question-and-answer section of the transcript.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : For those that are not familiar with the Elastic, can you please tell us your story. I'm not going to ask you that question. What I'm going to ask you is the same question I've been asking in '22, '23, '24, what is the vision for the company? What does success look like in four to five years?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Got it. I was going to title the session, Kash asks Ash. So that should be at the front end of whoever is going so Kash asks Ash or Kash versus Ash or whatever you want to call it. Navam, we will find a word of way to weave in. It's coming, trust me. That's great. So as we dig into AI, there's bits and pieces of the stack that you talked about vector databases, vector search, vector embeddings, search, concept of core Elastic search. Can you -- I mean, I know you're an engineer. Can you put it all together, what is that ultimate AI application stack look like? And why do we need these different elements that do these things embedding search database? And where do you play in each of these layers of the stack, the way you are articulate?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Thought that it should lead to less hallucination, the more information it has, right?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : On that note, I know in your most recent quarter, we'll bring Navam into the discussion shortly. You talked about a few use cases. What is the best use case, the most impactful use case where this whole stack embedding, vector search, vector databases, and the context engineering is having the maximum effect?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Detecting illegal use of proprietary music.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Got it. I want to come back to you later on about the -- how you participate in the economics of the AI stack. But Navam, if I recall right, you're an engineer, right, a former engineer, I mean --

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : No, I understand. But so I'm an engineer. I used to be an engineer, but I'm finance guy, too. The reason I asked is, was that the reason you hired Navam. Your bar is so high, but we've got to be an engineer, first and foremost, and then the finance stuff, the MBA and all the --

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : That's great. So Navam, welcome to our first -- should we call this a podcast? I think better than a podcast. We're asking some real questions to real people. But how has it been so far for you at Elastic? How it's been your experience?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : And this quarter that you reported was your first full quarter?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Reacceleration, margin expansion, I mean the guy is crushing it. Yeah. So how were you able to do this? And what is your prognostication of -- if you uncovered so much in four months?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : He's being very humble. I mean, talk to us more about the price increase thing, people debate this, oh, yes, all the growth was price increase. Most of it was not much. What is the best -- personally, I like it when a software company increases prices and some look at it and say, well, that means the units are down, blah, blah, blah. Like, you want to invest in a company that has pricing power and is able to show that pricing power by raising prices common share with the value that the company delivers. Were -- are people wrong about it? If you got a sense, I know you've been at a couple of other conferences before, are people being a little wrongheaded about assessing the quality of your price increase and the durability of your growth?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Got it. So in the context of being able to successfully put through a price increase and the quality of the Q1 beat, people see the rest of fiscal 2016 guidance as being very conservative. How do you, as the CFO, balance the process of setting prudent expectations versus signaling confidence, which is always a tricky thing to do?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : We're better positioned today relative to a quarter ago, two quarters ago, three quarters ago after you went through your GTM changes?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : How are things looking up now?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : So you've tweaked and you've got the right model --

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : That's great. My go-to-market is actually the opposite of started with 12 companies and growing 37 companies. If the IPO markets continue to be healthy, that number will likely grow, but everything has a limit. I want to talk to you, and Navam, I will come back to you. How are you deploying AI internally within the company as a CFO with an engineering background? Aren't you like jumping all over this and seeing how you can -- it's operating efficiencies within finance or sales? How are you deploying this stuff and getting advantage out of it internally and then I'll come back to you.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : What do you call it.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : For sales, it's got Elastic GPT.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : How do you foresee using AI and something like accounting? And how does that --

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : How long have you been doing in customer support?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : It's going to go higher, I think say -- it's going to go higher. It has to go higher.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : So what's your view on coding versus cursor versus what you get with GitHub or the Codex-based technology?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Vibe coding or regular AI-produced code.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : It;s not as cool as Kash versus Ash.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Got it. anybody, you want to jump in with a question? Please raise your hand. I know it is the afternoon effect. It's like pushing 3:00, we all need a cup of coffee before we can rejuvenate ourselves. But I have another one for you, Ash. The what have we learned from the early deposits about a couple of thousand folks that use RAG in your installed base? And I keep hearing maybe it's buy stock in the media that the context window is bigger for these latest models whether its GPT 5.0, whatnot. And people are RAG is dead. I'm sure it's not. But how do you think about broader context windows versus the value-added RAG, which is essential for you to add value to your customers?

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Very clear. It reminds me that just the way you explained that 1 terabyte of information. Anybody here remember in-memory databases and how it was a thing. And there are some people here. You will just not admit that you're old, but in memory databases are going to wipe out because they had the context windows. It run transactions in memory, but then we had reawakening.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : You transfer airlines.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Actually, maybe the 19 seconds we have, we've talked a lot about search. Give us a state of the assessment in APM, observability, security, like.

Question: Kash Rangan - Goldman Sachs Group Inc - Analyst : Got it. On that note, I wish you a successful journey in the years ahead. And thank you once again for your support. So good to see you part of the team here. Let's give a round of applause for Ash and Navam.