GL

Gustavo Llermaly

Search Consultant

Author’s articles

Using Elastic and Apple's OpenELM models for RAG systems

November 28, 2024

Using Elastic and Apple's OpenELM models for RAG systems

How to deploy and test the new Apple Models and build a RAG system using Elastic.

Late chunking in Elasticsearch with Jina Embeddings v2

November 22, 2024

Late chunking in Elasticsearch with Jina Embeddings v2

Using the Jina Embeddings v2 model in Elasticsearch and exploring the pros and cons of long context embeddings models.

Phrase synonyms like a boss with the synonyms API

November 19, 2024

Phrase synonyms like a boss with the synonyms API

Learn how to use phrase synonyms with the synonyms API in real scenarios.

Federated SharePoint searches with Azure OpenAI Service On your data

November 15, 2024

Federated SharePoint searches with Azure OpenAI Service On your data

Using Azure OpenAI Service on your data with Elastic as vector database.

Building a search app with Blazor and Elasticsearch

October 9, 2024

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.

Adding AI summaries to your site with Elastic

September 26, 2024

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.

Phi-3 small models, Elastic & RAG: Creating a smart ordering system

August 13, 2024

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.

Building multilingual RAG with Elastic and Mistral

Building multilingual RAG with Elastic and Mistral

Building a multilingual RAG application using Elastic and Mixtral 8x22B model

Build a RAG application with Elasticsearch's semantic_text and Amazon Bedrock

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.

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