The primary topic of this article is the evaluation of Elasticsearch query relevance. I build out an Elastic serverless project, generate document and judgment sets via AI, and perform rank evaluation of various query types. Topics covered:
Document chunking is the process of breaking down large documents into smaller segments before they are converted to…
Elastic has been progressively building a very rich Agentic AI framework called Agent Builder. You can essentially…
In this post, I demonstrate the configuration and use of the Jina ClipV2 multi-modal embedder in a hardware store use…
This article walks through four Elasticsearch retriever strategies — from the simplest rank-based fusion to a full…
Through the use of Jina models, we can extract both the lexical and semantic details of unstructured data, such as…
Demonstration of integration of AutoOps to Elastic on Kubernetes I demonstrate deployment of Elastic Cloud on…
A practical walkthrough of GPU-accelerated vector indexing with Elasticsearch In this post, I walk through an…
I cover the deployment of Elastic Cloud Hosted (ECH) and Google Cloud Platform (GCP) Private Service Connect (PSC) via…
This article examines the application of Elasticsearch in the medical field, focusing on the extraction of information…
This is a continuation of the search access control topic I discussed here. That article focused on the implementation…