Elasticsearch accelerates building AI search apps on serverless

Today we are announcing the availability of Elasticsearch Serverless in technical preview, which features:

• A developer-focused experience that simplifies creating AI-driven search with intuitive onboarding and relevant code examples, all as a fully managed service

• Cloud native, serverless architecture separating compute from data with the Search AI Lake

• Elasticsearch project creation in just a few clicks to try out new AI search features

Early access customers have used this new self-service option for a range of use cases — from internal analytics to building generative AI applications and conducting machine learning tasks.

We want to get generative AI innovation into developers’ hands faster. Going forward, you will see many new features, integrations, and techniques exposed in serverless before they are released to Elastic Cloud and Elastic’s self-hosted versions. Building prototypes and exploring the value of new features early in your project lifecycle helps you accelerate projects so you can get them into production sooner — all with a pay-as-you-go consumption model.

Finally, we are adding a specific profile for serverless projects that is optimized for vector storage and retrieval. Vectors need careful optimization, including byte quantization, to ensure that more low latency searches can be executed on a higher density of vectors and dimensions in memory. Low latency vector searches are critical for powering real-time end-user search experiences. Search Labs is your source for best practices and announcements of new features — which you can immediately try with Elasticsearch Serverless.

Developers want simple endpoints to integrate with so they can build new AI applications — without management or administration tasks. Elasticsearch Serverless is an ideal platform to build generative AI experiences using RAG workflows. The power of Elasticsearch with no overhead lets developers focus on what they care about. The service scales up and down as you apply more or less load, optimizing your spend automatically — you are only invoiced for the consumption used.

• Sign up for a free Cloud trial from the Elastic Cloud Console on AWS.

• Create and launch a serverless project for Elasticsearch.

• Follow this step-by-step guide to select, install, configure, and test your client.

• Ingest data and build your first search query.

• Transform and enrich your data.

The release and timing of any features or functionality described in this post remain at Elastic's sole discretion. Any features or functionality not currently available may not be delivered on time or at all.

In this blog post, we may have used or referred to third party generative AI tools, which are owned and operated by their respective owners. Elastic does not have any control over the third party tools and we have no responsibility or liability for their content, operation or use, nor for any loss or damage that may arise from your use of such tools. Please exercise caution when using AI tools with personal, sensitive or confidential information. Any data you submit may be used for AI training or other purposes. There is no guarantee that information you provide will be kept secure or confidential. You should familiarize yourself with the privacy practices and terms of use of any generative AI tools prior to use. 

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