## SEARCH APIs & DEVELOPER TOOLS

# The most extensive search toolkit for developers

Fast, flexible tools, robust APIs, and the trusted power of Elasticsearch allow development teams to build Search AI applications with text search, vector search, hybrid search, semantic search, and other machine learning capabilities — all to your exact specifications.

Power multilingual relevance at scale, natively in Elasticsearch. Jina embeddings and rerankers deliver high-precision GPU-accelerated inference across 30+ languages for search, RAG, and AI agents.

Hybrid conversational search is ready for production, enabling powerful RAG and conversational search experiences.

Learn how to easily utilize Elasticsearch to build advanced search experiences.

## Elasticsearch — the most widely deployed vector database

#### Copy to try locally in two minutes

Copy to clipboard

```
curl -fsSL https://elastic.co/start-local | sh
```

## Firm footing for building any search experience

For decades, developers have relied on the speed, scale, and relevance of Elasticsearch for building their most important search functionality.

## FLEXIBLE INGESTION

### Any platform, any data, anywhere

Index, enrich, and sync data your way with connectors, open crawler, API, or JSON import.

## ANALYZE. TUNE. REPEAT

### Real-time intelligence, actionable insights

Get visibility into user behavior with behavioral analytics to make necessary improvements and adjustments.

## Future-proof search

### ML & vector search-powered

Add proprietary data to LLMs and generative AI for more relevance and accuracy. Find similar data instantly with vector search powered by machine learning.

## Semantic Search

### Multilingual search with Jina AI models

Get GPU-accelerated multilingual retrieval and reranking directly in Elasticsearch with native Jina AI or third-party models.

## Geospatial

### Blazing fast geospatial queries

Store and query geospatial data at top speed with Elasticsearch. Use Kibana to visualize, detect anomalies, and easily solve location-based challenges.

## Hybrid Search

### A search technique for the best of both worlds

Combine lexical keyword search with the contextual understanding of semantic search with Reciprocal Rank Fusion (RRF) to deliver a unified, superior result set.

## Retrieval Augmented Generation

## Enhance your RAG workflows with Elasticsearch

Discover how using Elastic for RAG workflows enhances generative AI experiences. Easily sync to real-time information using proprietary data sources to get the best, most relevant generative AI responses.

## COMPOSABILITY

## Semantic search made simple

Implement semantic search in minutes syncing real-time data from proprietary sources for relevant responses. Use Jina AI models on Elastic Inference Service (EIS) or the inference API to apply a model of your choice. Then connect to an index with the semantic_text data type, sync, and start building.

## Retrievers

## Abstract away with retrievers

Use retrievers (standard, kNN, RRF), now generally available (GA), to handle complex search operations. Easily integrate them into retriever trees, allowing modular, composable search pipelines. Test different retrieval strategies, fine-tune scoring, apply filters, and optimize performance while maintaining backward compatibility with traditional queries.

#### We speak your language

Choose your preferred client. Elasticsearch supports your programming language of choice with native APIs.