Elastic integrates Google Cloud Vertex AI for enhanced AI tools

Elastic has announced new integrations with Google Cloud, enhancing AI capabilities for developers and security professionals.

One of the key updates is the support for Google Cloud's Vertex AI in the Elastic Attack Discovery and AI Assistant for Security. This integration aims to empower security analysts by automating the triage process and improving threat response through the use of Google Cloud's Vertex AI and Gemini models.

Another significant development is the inclusion of support for Google AI Studio within the Elasticsearch Open Inference API. This allows developers to interact more efficiently with Elasticsearch data and facilitates rapid application development using Google's Gemini models, which supports the creation of generative AI experiments.

Additionally, Elastic announced that its Open Inference API and Playground now support Google Cloud's Vertex AI Platform. This integration offers developers the ability to utilise advanced text embedding and reranking features of Vertex AI, simplifying the process of developing production-ready applications within the Elasticsearch vector database.

These advancements are indicative of the increasing synergy between AI and search technologies within the tech industry. Warren Barkley, Senior Director of Product Management for Vertex AI at Google Cloud, commented, "We're excited to collaborate with Elastic to bring Vertex AI and Gemini models to even more developers. As innovation in generative AI and RAG applications continues to grow, this integration with Elasticsearch will enable the Elastic community to easily and effectively harness Vertex AI and our models to build transformative applications."

Shay Banon, Founder and Chief Technology Officer at Elastic, shared his thoughts on the integration, stating, "Our latest integration with Google Cloud's Vertex AI platform makes a unified AI development platform accessible to Elastic developers. Vertex AI and Elasticsearch are proven at a vast scale, and we're looking forward to seeing what developers build with their combined capabilities."

The integration facilitates the storage and utilisation of embeddings in Elasticsearch, enabling developers to refine retrieval processes and leverage proprietary data more efficiently. Google's Gemini models are accessible in the Elastic low-code playground, providing developers with greater options for A/B testing Large Language Models (LLMs), and tuning retrieval and chunking processes.

The support for Vertex AI is available immediately, providing developers with enhanced resources for building and testing innovative applications. The collaboration between Elastic and Google continues to evolve, following previous integrations with Google Gemini 1.5 models via Vertex AI.