TechDogs-"Elasticsearch Now Available As A Native Grounding Engine On Google Clouds Vertex AI Platform"

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Elasticsearch Now Available As A Native Grounding Engine On Google Clouds Vertex AI Platform

By Business Wire

Business Wire
Overall Rating

Integration streamlines RAG application development and eliminates the need for unnecessary APIs and data orchestration

SAN FRANCISCO--(BUSINESS WIRE)--Elastic (NYSE: ESTC), the Search AI Company, announced that the Elasticsearch vector database is now a natively supported information retrieval engine for Google Cloud’s Vertex AI platform.

“By integrating Elasticsearch as a native grounding engine in Google Cloud’s Vertex AI platform, our joint customers can seamlessly build RAG applications in a single workflow,” said Shay Banon, founder and chief technology officer at Elastic. “This solution enables faster deployment with minimal configuration, giving back time and bandwidth to developers building the next generation of generative AI experiences.”

This feature is currently in Public Preview. Read the Elastic blog to learn how to get started.

About Elastic

Elastic (NYSE: ESTC), the Search AI Company, enables everyone to find the answers they need in real-time using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform, the development platform used by thousands of companies, including more than 50% of the Fortune 500. Learn more at elastic.co.

Elastic and associated marks are trademarks or registered trademarks of Elastic B.V. and its subsidiaries. All other company and product names may be trademarks of their respective owners.


Contacts

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Elastic PR
PR-team@elastic.co

Frequently Asked Questions

What is the significance of Elasticsearch's integration with Google Cloud's Vertex AI?

This integration streamlines the development of Retrieval Augmented Generation (RAG) applications by eliminating the need for complex APIs and data orchestration, leading to faster deployment and reduced development time.

What is a RAG application?

A Retrieval Augmented Generation (RAG) application uses a large language model (LLM) along with an external knowledge base to generate more accurate and relevant responses.

What is the current status of this integration?

This feature is currently in Public Preview. More information can be found on the Elastic blog.

First published on Thu, Apr 10, 2025

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