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Common Expression Language (CEL): How the CEL input improves data collection in Elastic Agent integrations
Elasticsearch Labs

Common Expression Language (CEL): How the CEL input improves data collection in Elastic Agent integrations

Learn how the Common Expression Language differs from other programming languages, how we’ve extended it for Filebeat’s CEL input, and the flexibility it gives you to express data collection logic in Elastic Agent integrations.

Chris Berkhout
Entity resolution with Elasticsearch & LLMs, Part 2: Matching entities with LLM judgment and semantic search
Elasticsearch Labs

Entity resolution with Elasticsearch & LLMs, Part 2: Matching entities with LLM judgment and semantic search

Using semantic search and transparent LLM judgment for entity resolution in Elasticsearch.

Jessica Moszkowicz
Elasticsearch vector search is up to 8x faster than OpenSearch
Elasticsearch Labs

Elasticsearch vector search is up to 8x faster than OpenSearch

Exploring filtered vector search benchmarks of OpenSearch vs. Elasticsearch and why vector search performance is critical for context-engineered systems.

Sachin Frayne
Elastic AutoOps now free for all: What you get with it
Elasticsearch Labs

Elastic AutoOps now free for all: What you get with it

Elastic AutoOps is now free for all self-managed clusters. Learn what you get with it and how it compares to Stack Monitoring.

Valentin Crettaz
Build a "chat with your website data" agent with Jina Embeddings v5 and Elasticsearch
Elasticsearch Labs

Build a "chat with your website data" agent with Jina Embeddings v5 and Elasticsearch

Learn how to build a working, grounded "chat with your website" experience in under an hour by using Elasticsearch Serverless, Jina Embeddings v5, Elastic Open Web Crawler, and Elastic Agent Builder.

Ugo Sangiorgi
jina-embeddings-v5-text: Compact state-of-the-art text embeddings for search and intelligent applications
Elasticsearch Labs

jina-embeddings-v5-text: Compact state-of-the-art text embeddings for search and intelligent applications

Introducing jina-embeddings-v5-text models, including jina-embeddings-v5-text-small and jina-embeddings-v5-text-nano, and explaining how to use these multilingual embedding models via Elastic Inference Service (EIS).

Scott Martens
Ensuring semantic precision with minimum score
Elasticsearch Labs

Ensuring semantic precision with minimum score

Improve semantic precision by employing minimum score thresholds. The article includes concrete examples for semantic and hybrid search.

Mattias Brunnert
Dependency management on Kubernetes
Elasticsearch Labs

Dependency management on Kubernetes

How to streamline dependency management on Kubernetes using Renovate CLI and Argo Workflows.

Nikos Fotiou
Better text analysis for complex languages with Elasticsearch and neural models
Elasticsearch Labs

Better text analysis for complex languages with Elasticsearch and neural models

Using neural models and the Elasticsearch inference API to improve search in Hebrew, German, Arabic, and other morphologically complex languages.

Noam Schwartz
An open‑source Hebrew analyzer for Elasticsearch lemmatization
Elasticsearch Labs

An open‑source Hebrew analyzer for Elasticsearch lemmatization

An open-source Elasticsearch 9.x analyzer plugin that improves Hebrew search by lemmatizing tokens in the analysis chain for better recall across Hebrew morphology.

Lily Adler
Elasticsearch 9.3 adds bfloat16 vector support
Elasticsearch Labs

Elasticsearch 9.3 adds bfloat16 vector support

Exploring the new Elasticsearch element_type: bfloat16, which can halve your vector data storage.

Simon Cooper
AI agents that perform actions: Automating IT requests with Agent Builder and Workflows
Elasticsearch Labs

AI agents that perform actions: Automating IT requests with Agent Builder and Workflows

Using Elastic Agent Builder and Workflows to create an AI agent that automatically performs IT actions, such as laptop refreshes.

Sri Kolagani