Federated SharePoint searches with Azure OpenAI Service On your data
Using Azure OpenAI Service on your data with Elastic as vector database.
GenAI for customer support — Part 5: Observability
This series gives you an inside look at how we're using generative AI in customer support. Join us as we share our journey in real-time, focusing in this entry on observability for the Support Assistant.
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.
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.
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.
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.
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.
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.
Comparing ELSER for retrieval relevance on the Hugging Face MTEB Leaderboard
This blog compares ELSER for retrieval relevance on the Hugging Face MTEB Leaderboard.
Automating traditional search with LLMs & Elastic Query DSL
Learn how to use LLMs to write Elastic Query DSL and query structured data with filters.
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
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.