In this episode of the Futurum Tech Webcast Interview Series, I had the opportunity to speak with Ash Kulkarni, the CEO of Elastic, about the company's upcoming sales kickoff and the challenges faced by its customers. During our conversation, Ash highlighted the positive momentum they have experienced at Elastic over the past year. The company has successfully released new products and formed partnerships with hyper-scaler partners, resulting in significant progress.

Elastic’s customers have expressed their desire to achieve more with less, leveraging insights from both structured and unstructured data in real-time. As enterprises seek a platform that enables efficient data analysis and drives business growth, Elastic have listened closely to their needs. In our discussion Ash emphasized the importance of Elastic’s relevance engine in making sense of data while ensuring privacy and security.

We discussed the following topics:

• Elastic’s evolution from being primarily a search analytics platform to offering observability and security solutions.
• The impact of large language models and AI, highlighting the opportunities they present.
• The immense potential for Elastic to connect private enterprise data with large language models, enabling the development of generative AI applications.
• The alignment between Elastic existing user base, its popularity, and the company’s developer appeal positions Elastic favorably to seize this opportunity.
• Elastics' ongoing innovations, including platform capabilities, AIOps, and security analytics.
• The establishment of Elastic’s Security Threat Research Labs, that aims to research open attacks and enhance protection for customers.
• The company’s collaborations with hyper-scaler partners like AWS, GCP, and Azure, as they play a crucial role in building momentum for the company’s offerings.
• How Elastic is committed to addressing its customers' challenges, such as the skills gap and the increasing volume of data. Elastic helps enterprises overcome these obstacles by providing real-time insights from all types of data, including both human-generated and machine-generated data, such as logs.