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Integrations - Elasticsearch Labs

Integrations

June 5, 2025

Making sense of unstructured documents: Using Reducto parsing with Elasticsearch

Demonstrating how Reducto's document processing can be integrated with Elasticsearch for semantic search.

Making sense of unstructured documents: Using Reducto parsing with Elasticsearch
First to hybrid search: with Elasticsearch and Semantic Kernel

May 21, 2025

First to hybrid search: with Elasticsearch and Semantic Kernel

Hybrid search capabilities are now available in the .NET Elasticsearch Semantic Kernel connector. Learn how to get started in this blog post.

Get set, build: Red Hat OpenShift AI applications powered by Elasticsearch vector database

May 21, 2025

Get set, build: Red Hat OpenShift AI applications powered by Elasticsearch vector database

The Elasticsearch vector database is now supported by the ‘AI Generation with LLM and RAG’ Validated Pattern. This blog walks you through how to get started.

Spring AI and Elasticsearch as your vector database

Spring AI and Elasticsearch as your vector database

Building a complete AI application using Spring AI and Elasticsearch.

Unstructured data processing with NVIDIA NeMo Retriever, Unstructured, and Elasticsearch

May 8, 2025

Unstructured data processing with NVIDIA NeMo Retriever, Unstructured, and Elasticsearch

Learn how to build a scalable data pipeline for unstructured documents using NeMo Retriever, Unstructured Platform, and Elasticsearch for RAG applications.

Using AutoGen with Elasticsearch

April 24, 2025

Using AutoGen with Elasticsearch

Learn to create an Elasticsearch tool for your agents with AutoGen.

Using LlamaIndex Workflows with Elasticsearch

April 21, 2025

Using LlamaIndex Workflows with Elasticsearch

Learn how to create an Elasticsearch-based step for your LlamaIndex workflow.

Elasticsearch vector database for native grounding in Google Cloud’s Vertex AI Platform

April 9, 2025

Elasticsearch vector database for native grounding in Google Cloud’s Vertex AI Platform

Elasticsearch is now publicly available as the first third-party native grounding engine for Google Cloud’s Vertex AI platform and Google’s Gemini models. It enables joint users to build fully customizable GenAI experiences grounded in enterprise data, powered by the best-of-breed Search AI capabilities from Elasticsearch.

Using CrewAI with Elasticsearch

April 8, 2025

Using CrewAI with Elasticsearch

Learn how to create an Elasticsearch agent with CrewAI for your agent team and perform market research.

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