Elastic N.V. (ESTC) Q3 FY26 earnings call: guidance and Q&A

Will the increasing penetration of AI use cases in the $100K+ ACV cohort lead to sustained growth acceleration beyond the previously stated 5% expansion?

Management confirmed that generative AI cohorts continue to show stronger growth and expansion, and there is indeed a possibility for growth to accelerate beyond the 5% previously discussed, as customers mature in their AI journey and increase usage.

“Yes, absolutely, there is a possibility. The art of the possible is there for us to actually accelerate beyond that 5% that we laid out during Financial Analyst Day, and the trends remain positive.”

asked by Sanjit Singh · answered by Navam Welihinda

What are the core pieces that make Elastic a leading provider of context for AI applications, beyond just vector search?

Ash Kulkarni outlined the need for a platform that can ingest all data types (structured/unstructured), convert to vectors for hybrid search, rerank for accuracy (e.g., GENA AI models), assemble agents (Agent Builder), orchestrate actions (Workflows), and monitor (LLM observability).

“The most important thing to keep in mind is context is going to change from task to task. And so the data platform, the context engineering platform that you provide needs to be able to do a whole bunch of things all together in a very consistent way.”

asked by Sanjit Singh · answered by Ashutosh Kulkarni

Was the self-managed strength due to prior push-outs? Why is Q4 sales-led subscription revenue guidance sequentially down, which is unusual? How does monetization differ between self-managed and cloud customers?

Ash stated self-managed strength is not push-outs but due to customers preferring to keep sensitive AI data within their control (on-prem or cloud VPCs). Navam explained Q4 guidance incorporates prudence, a 3-day shorter quarter (>$14M revenue headwind), and historical patterns where Q4 guidance can be lower than Q3 actuals.

“These are modern workloads, that continue to grow as that usage of AI grows, and we are going to continue to benefit from it. Which is why we believe it is really important to not just look at cloud, but to look at the whole picture and take into account the strong growth that we are seeing even on self-managed.”

asked by Robbie Owens · answered by Ashutosh Kulkarni

Does Elastic view frontier AI models (like OpenAI's) as future competition or more as partnership opportunities?

Ash views frontier models as reasoning engines that depend on Elastic for data and context. He sees them as 'operating systems of tomorrow' that require data systems like Elastic to feed them, enabling agents to communicate and build applications.

“Really, we don't -- in our opinion, AI doesn't displace us, it really depends on us because if you think about these frontier models, there are amazing reasoning engines. Like the way I think about them is they are going to be the operating systems of tomorrow.”

asked by Matthew Hedberg · answered by Ashutosh Kulkarni

CRPO growth is stable at 15% constant currency; why isn't it accelerating faster given AI tailwinds, and how does Elastic bridge to its 'true north' of 20%+'?

Navam highlighted CRPO crossing $1 billion and 19% reported growth as strong progress, noting RPO at 22% growth (best in 2 years). Ash added that the full-year sales-led subscription revenue guide shows continued strength, and as more customers adopt AI functionality, the faster-growing cohorts will drive acceleration towards and potentially beyond the 20%+ midterm target.

“The other thing that I will say to this, Brent, is that if you look at the full year guide for sales net subscription revenue, you can see that the strength in our business continues. And look, for us, the midterm guide that we laid out is not the place where we end up the place that we believe we can go beyond that.”

asked by Brent Thill · answered by Ashutosh Kulkarni

Is MongoDB increasingly appearing in bake-offs for AI apps, or was the mentioned competitive win a one-off?

Ash clarified that the specific win was a customer scaling issue with MongoDB for a basic search application, where Elastic provided better performance for hybrid search. He noted Elastic typically plays in unstructured data, so head-to-head with MongoDB is not common but happens occasionally.

“No, this was a situation where the customer had started to use that technology for a basic search application. They had some issues scaling it and as they were trying to build a more scalable solution, especially for hybrid search, they realized that they needed something that could perform and that was the customer win that I talked about.”

asked by William Miller Jump · answered by Ashutosh Kulkarni