Category: AI

Articles tagged AI

Filters

GraphQL meets Elasticsearch: Building scalable, AI-ready apps with Hasura DDN

GraphQL offers an efficient and flexible way to query data. This blog will explain how Hasura DDN works with Elasticsearch to make high performing and metadata-driven access to data.

Praveen Durairaju

GitHub Assistant: Interact with your GitHub repository using RAG and Elasticsearch

This blog introduces a GitHub Assistant using RAG with Elasticsearch to enable semantic code queries, providing insights into GitHub repositories, which can be extended to PRs feedback, issues handling, and production readiness reviews.

Fram Souza

From PDF tables to insights: An alternative approach for parsing PDFs in RAG

An alternative approach to parsing PDF tables for RAG, overcoming the limitations of highly normalized formats like CSV and JSON.

Sunile Manjee

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.

Juan Bustos

Which job is the best for you? Using LLMs and semantic_text to match resumes to jobs

Learn how to use Elastic's LLM Inference API to process job descriptions, and run a double hybrid search to find the most suitable job for your resume.

Han Xiang Choong

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.

David Pilato

Comparing ELSER for retrieval relevance on the Hugging Face MTEB Leaderboard

This blog compares ELSER for retrieval relevance on the Hugging Face MTEB Leaderboard.

Aris Papadopoulos

Automating traditional search with LLMs & Elastic Query DSL

Learn how to use LLMs to write Elastic Query DSL and query structured data with filters.

Han Xiang Choong

Quickly create RAG apps with Vertex AI Gemini models and Elasticsearch playground

Quickly create a RAG app with Vertex AI Gemini models and Elasticsearch playground

Jeff Vestal

Vertex AI integration with Elasticsearch open inference API brings reranking to your RAG applications

Google Cloud customers can use Vertex AI embeddings and reranking models with Elasticsearch and take advantage of Vertex AI’s fully-managed, unified AI development platform for building generative AI apps.

Tim Grein

Elasticsearch open inference API for Google AI Studio

Elasticsearch open inference API adds support for Google AI Studio

Jeff Vestal

Adding AI summaries to your site with Elastic

How to add an AI summary box along with the search results to enrich your search experience.

Gustavo Llermaly

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.

Try it yourself