Category: AI
Articles tagged AI
Phi-3 small models, Elastic & RAG: Creating a smart ordering system
Deploying Phi-3 models on Azure AI Studio and using them with Elastic Open Inference Service to create a RAG application.
GenAI for Customer Support — Part 3: Designing a chat interface for chatbots... for humans
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 designing a GenAI chatbot interface.
Building multilingual RAG with Elastic and Mistral
Building a multilingual RAG application using Elastic and Mixtral 8x22B model
Mistral AI embedding models now available via Elasticsearch Open Inference API
Learn more about how to use Mistral embeddings with Elastic built search experiences!
Protecting Sensitive and PII information in RAG with Elasticsearch and LlamaIndex
How to protect sensitive and PII data in a RAG application with Elasticsearch and LlamaIndex.
GenAI for Customer Support — Part 2: Building a Knowledge Library
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!
Build AI conversational search for your customer success application with Elasticsearch and OpenAI
Learn how to build an AI conversational search for customer success applications using Elasticsearch and OpenAI.
Build a RAG application with Elasticsearch's semantic_text and Amazon Bedrock
Learn how to build a RAG application using Elasticsearch's semantic_text mapping type and Amazon Bedrock without leaving Elastic.
Elasticsearch open inference API adds Amazon Bedrock support
Elasticsearch open inference API added Amazon Bedrock support. Here's how to use Amazon Bedrock models via Elasticsearch's open inference API.
Playground: Experiment with RAG using Bedrock Anthropic Models and Elasticsearch in minutes
Explore Elastic's Playground and learn how to use it to experiment with RAG applications using Bedrock Anthropic Models & Elasticsearch.
Search complex documents using Unstructured.io and Elasticsearch vector database
Learn how to ingest and search complex proprietary documents with Unstructured.io and Elasticsearch for RAG applications.
