Advances in artificial intelligence are reshaping how enterprises leverage their data, with AI-powered data search positioning Elasticsearch B.V. as a front-runner in this movement.

By enabling organizations to unlock insights from unstructured data through its innovative AI-powered search and security solutions, Elasticsearch is raising the bar for efficiency and scalability in enterprise applications, according to Ash Kulkarni (pictured), chief executive officer of Elasticsearch.

Elasticsearch’s Ash Kulkarni talks with theCUBE about the company’s AI innovations, semantic search and business process automation through advanced data and security solutions.

“Large language models are enabling that value extraction,” he said. “We are seeing customers go from traditional search — which was textual, lexical search — to semantic search. That’s the first step, right? Then, people are going from there to now saying, ‘Now that I can ask these questions, can I turn this into a conversational application so I can automate some of the queries and so on?’ This is the business version of ChatGPT.”

Kulkarni spoke with theCUBE Research’s John Furrier for theCUBE’s “Cloud AWS re:Invent coverage,” during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Elasticsearch leverages AI-powered data search to transform enterprise data management, from semantic search to advanced automation in business processes and cybersecurity.

AI-powered data search simplifies data management and automation

Elastic’s serverless vector database is a game changer for enterprises managing unstructured data, offering unprecedented scalability and efficiency, according to Kulkarni. The database integrates with Amazon Web Services Inc., making AI-powered data search and semantic capabilities accessible to a broader range of users. This shift empowers businesses to derive actionable insights without needing extensive technical expertise.

“[For] the semantic search, the great part about it is in the past, when you searched for information, you had to be precise in your questions; otherwise, you wouldn’t get matches,” Kulkarni said. “Now you can search for the concept, you can search contextually, and you can get amazing answers. And that’s how human beings respond. That’s effectively semantic search. Now the machine can do that, which is so powerful.”

Elastic’s advancements extend beyond semantic search to retrieval-augmented generation and agentic workflows. These tools enable automation of complex business processes, reducing the need for manual effort and increasing productivity, according to Kulkarni.

“Now I can automate things that in the past involved human beings reading through documents and forwarding the analysis onto the next person in the chain,” he said. “That journey is happening today, and I expect that people are going to go through that curve, going from search to semantic, to RAG [and] then agentic workflows.”

Elastic has also demonstrated a commitment to privacy, governance and scalability through innovations such as better binary quantization. This technique reduces memory requirements for vector embeddings by 32 times, making AI solutions more cost-effective and efficient, according to Kulkarni.

“Even today, the cost of inferencing is pretty high,” he said. “We are constantly making our vector database more and more efficient. Just two weeks ago, we released a capability called better binary quantization. [It] represents an entire vector embedding in a single bit without compromising on the accuracy of the results that you can get. It’s a very advanced algorithm [and] we are the first in the industry to be out with it.”

In the security domain, Elastic’s AI-driven tools, powered by AI-powered data search, are bridging gaps in cybersecurity expertise. By automating complex threat detection and analysis, Elastic equips new security professionals with capabilities that would otherwise take years to develop, Kulkarni explained.

“[We’ve applied] that to the other domains that we play in, observability and security,” he said. “In security, we applied those same concepts to create a functionality called Attack Discovery, and that basically gives a security operations center analyst … instead of just dealing with alerts, it turns all of those alerts, correlates them and shows you the actual attacks that are going on in their environment.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s “Cloud AWS re:Invent coverage”:

Photo: SiliconANGLE