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RAG (Retrieval Augmented Generation) with LlamaIndex, Elasticsearch and Mistral
Generative AI

RAG (Retrieval Augmented Generation) with LlamaIndex, Elasticsearch and Mistral

Learn to implement a RAG system using LlamaIndex, Elasticsearch and locally running Mistral.

Srikanth Manvi

Elasticsearch open Inference API adds support for Cohere’s Rerank 3 model
IntegrationsHow ToVector SearchGenerative AI

Elasticsearch open Inference API adds support for Cohere’s Rerank 3 model

“Elasticsearch integrates semantic reranking with Cohere’s Rerank models, with the inclusion of Rerank into our open Inference API.”

Serena Chou

Max Hniebergall

Building a RAG System With Gemma, Hugging Face & Elasticsearch
Generative AI

Building a RAG System With Gemma, Hugging Face & Elasticsearch

Learn to construct an RAG system with Elasticsearch for semantic search and question-answering on private data. Fetch relevant documents as a Context window and leverage the Gemma model for accurate answers.

Ashish Tiwari

Introducing Elasticsearch vector database to Azure OpenAI Service On Your Data (preview)
Generative AI

Introducing Elasticsearch vector database to Azure OpenAI Service On Your Data (preview)

Microsoft and Elastic partner to add Elasticsearch (preview) as an officially supported vector database and retrieval augmentation technology for Azure OpenAI On Your Data, enabling users to build chat experiences with advanced AI models grounded by enterprise data.

Aditya Tripathi

Avatar Assisted & Dialogue Driven Voice To RAG Search
Generative AIVector Search

Avatar Assisted & Dialogue Driven Voice To RAG Search

Explore movie discovery with 'Avatar-Assisted Voice Search: Semantic Movie Finding with Elasticsearch'. This demo showcases a seamless integration of speech-to-text, Elasticsearch's semantic search capabilities, Azure OpenAI's RAG, and a synthesized avatar for responses. Experience a more sophisticated way to find movies through voice commands and interactive AI technology, making your search both efficient and engaging.

Sunile Manjee

Retrieval Augmented Generation (RAG) using Cohere Command model through Amazon Bedrock and domain data in Elasticsearch
Generative AIIntegrations

Retrieval Augmented Generation (RAG) using Cohere Command model through Amazon Bedrock and domain data in Elasticsearch

Learn how to implement Retrieval Augmented Generation (RAG) using Cohere Command model via Amazon Bedrock & domain data in Elasticsearch.

Uday Theepireddy

Meor Amer

Ayan Ray

James Yi

Domain specific generative AI: pre-training, fine-tuning, and RAG
Generative AI

Domain specific generative AI: pre-training, fine-tuning, and RAG

Explore strategies for integrating domain-specific knowledge into large language models (LLMs) through pre-training, fine-tuning, and RAG.

Steve Dodson

Retrieval Augmented Generation (RAG)
Generative AI

Retrieval Augmented Generation (RAG)

Learn about Retrieval Augmented Generation (RAG) and how it can help improve the quality of an LLM's generated responses by providing relevant source knowledge as context.

Joe McElroy

Elasticsearch as a GenAI Caching Layer
Generative AIVector SearchHow To

Elasticsearch as a GenAI Caching Layer

Explore how integrating Elasticsearch as a caching layer optimizes Generative AI performance by reducing token costs and response times, demonstrated through real-world testing and practical examples.

Jeff Vestal

Baha Azarmi