Elasticsearch Labs

Elasticsearch Labs is the one-stop destination for developers to learn how to easily utilize Elasticsearch to build advanced search experiences including generative AI, embedding models, reranking capabilities and more.

Featured Articles
ES|QLQuery Languages

One query, three data sources: ES|QL subqueries get FROM, TS and ROW

Filter application logs by live metric behavior and combine indexed data with inline test values. Your filter lists pull from time-series data on the fly, so nothing is hard-coded.

Fang Xing
ES|QLQuery Languages

One ES|QL query instead of two: WHERE IN subquery replaces the copy-paste loop in Elasticsearch

Fang Xing
AutoOpsVector DatabaseOperations

The mystery stress your heap chart can't see: AutoOps now watches vector off-heap memory

Valentin Crettaz
Vector Database

Elasticsearch vector search is up to 8x faster than OpenSearch

Sachin Frayne
Agentic AIAI tools

Agent Builder, beyond the chatbox: Introducing Augmented Infrastructure

Alexander Wert
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Get Started

We've gathered top resources to help you start with Elasticsearch, from beginner tutorials to advanced tool integrations.

Tutorials

Long-form guides to get you started

Examples

Long-form guides to get you started

Integrations

Connect to your favourite tools

Blogs

Developer insights, thought leadership, and how-to’s

New to Elastic?

New to Elastic? Start with the Elasticsearch docs to learn the fundamentals. When you're ready, come back to Elasticsearch Labs for more advanced content using our latest innovations.

Get started with Elasticsearch

Examples

Practical how-to guides, interactive notebooks, and sample apps to get you started.

Apps

OpenAI embeddings in Elasticsearch
Vector DatabaseAI
Chatbot RAG Reference App
AIVector Database
Relevance Workbench
Vector DatabaseAIRelevance

Glossary

Definitions and reference material for every term, concept, and acronym used across the Elasticsearch Labs library.

Go to glossary

Notebooks

Using Cohere for RAG and Rerank in Elasticsearch
AI

Semantic search using the Inference API with the Cohere service
AI

Semantic search with ELSER in Elasticsearch
Vector DatabaseRelevance

Load and search with a multilingual model
Vector Database

Semantic search using the Inference API with the OpenAI service
AI

Semantic search quick start
Vector Database

Integrations

Seamlessly connect with leading AI and machine learning platforms to enhance your search capabilities and drive powerful, intelligent applications with Elasticsearch.

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Amazon Bedrock

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Aryn.ai

Aryn is an AI-powered document parsing and ETL system for complex, unstructured data like PDFs, HTML, presentations, and more. It can process 30+ file formats and extract tables, images, and more with high quality. You can use Aryn to chunk documents, extract metadata, create vector embeddings, and load your Elasticsearch vector and keyword indexes with high-quality data.

Anthropic

Anthropic is an AI lab whose research and products put safety at the frontier. As a public benefit corporation, Anthropic is dedicated to ensuring the world safely makes the transition through transformative AI. Their multidisciplinary team creates reliable, interpretable, and steerable AI systems. Anthropic’s flagship product is Claude, a family of foundational AI models designed for enterprise applications. Learn more about Anthropic at anthropic.com.

Jina AI

Jina AI develops and distributes compact, high-performance Search Foundation models for multilingual text and image processing.

LlamaIndex

Use LlamaIndex with Elastic as a data source, embedding model, vector store, index store, KV store, or document store.

Vectorize.io

Use Vectorize to optimize your RAG workflows with Elasticsearch as the vector database.

OpenAI

Integrate OpenAI with Elastic by leveraging OpenAI's embedding models, the chat completions API or other advanced integration options.

Red Hat Openshift

Red Hat Openshift AI is a flexible, scalable AI and ML platform that enables enterprises to create and deliver AI-enabled applications at scale across hybrid cloud environments.

Microsoft Azure AI Services

Microsoft’s Azure OpenAI Service provides REST API access to OpenAI's powerful language models, which can be easily adapted to your specific tasks. The model catalog in Azure AI Studio features hundreds of models across model providers such as Azure OpenAI service, Mistral, Meta, Cohere, Nvidia, and Hugging Face, including models trained by Microsoft

Ready to build state of the art search experiences?

Sufficiently advanced search isn’t achieved with the efforts of one. Elasticsearch is powered by data scientists, ML ops, engineers, and many more who are just as passionate about search as you are. Let’s connect and work together to build the magical search experience that will get you the results you want.

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