RAG made easy with Spring AI + Elasticsearch
Customize your AI chatbot experience with private data. Learn how to build a Retrieval-Augmented Generation (RAG) app with Spring AI and Elasticsearch.
Late chunking in Elasticsearch with Jina Embeddings v2
Using the Jina Embeddings v2 model in Elasticsearch, implementing late chunking, and exploring the pros and cons of long context embeddings models.
Elasticsearch open inference API adds support for IBM watsonx.ai Slate embedding models
How to use IBM watsonx™ Slate text embeddings when building Search AI experiences with Elasticsearch vector database.
Better Binary Quantization (BBQ) vs. Product Quantization
Why we chose to spend time working on Better Binary Quantization (BBQ) instead of product quantization in Lucene and Elasticsearch.
Federated SharePoint searches with Azure OpenAI Service On your data
Using Azure OpenAI Service on your data with Elastic as vector database.
How to use hybrid search for an e-commerce product catalog
Learn how to use hybrid search to build an e-commerce product catalog, using faceting, promotions, personalization and behavioral analytics.
Better Binary Quantization (BBQ) in Lucene and Elasticsearch
How Better Binary Quantization (BBQ) works in Lucene and Elasticsearch.
Hybrid search with multiple embeddings: A fun and furry search for cats!
A walkthrough of how to implement different types of search - lexical, vector and hybrid - on multiple embeddings (text and image). It uses a simple and playful search application on cats.
RaBitQ binary quantization 101
Understand the most critical components of RaBitQ binary quantization, how it works and its benefits. This guide also covers the math behind the quantization and examples.
Unlock the power of your data with RAG using Vertex AI and Elasticsearch
Unlock your data's potential with RAG using Vertex AI and Elasticsearch. This blog series covers data ingestion into Elasticsearch for a robust knowledge base for creating advanced RAG based search applications.
Building a search app with Blazor and Elasticsearch
Learn how to build a search application using Blazor and Elasticsearch, and how to use the Elasticsearch .NET client for hybrid search.
LangChain4j with Elasticsearch as the embedding store
LangChain4j (LangChain for Java) has Elasticsearch as an embedding store. Discover how to use it to build your RAG application in plain Java.