About the author
Jeffrey Rengifo is a software developer focusing on improving search experiences using Elasticsearch. He specializes in GenAI and aims to innovate by creating new tools to help optimize different processes and solve everyday problems.
Author’s articles
May 4, 2026
How to measure and improve Elasticsearch search recall: from 0.43 to 0.75 with hybrid search
Learn how to measure and improve search recall in Elasticsearch by combining BM25 lexical search with Jina AI vector embeddings, using the rank_eval API to validate the improvement with real numbers.
March 31, 2026
From judgment lists to trained Learning to Rank (LTR) models
Learn how to transform judgment lists into training data for Learning To Rank (LTR), design effective features, and interpret what your model learned.
March 27, 2026
Creating an Elasticsearch MCP server with TypeScript
Learn how to create an Elasticsearch MCP server with TypeScript and Claude Desktop.
March 23, 2026
Using Elasticsearch Inference API along with Hugging Face models
Learn how to connect Elasticsearch to Hugging Face models using inference endpoints, and build a multilingual blog recommendation system with semantic search and chat completions.
March 18, 2026
AI agent memory: Creating smart agents with Elasticsearch managed memory
Learn how to create smarter and more efficient AI agents by managing memory using Elasticsearch.
January 29, 2026
Building human-in-the-loop (HITL) AI agents with LangGraph and Elasticsearch
Learn what human-in-the-loop (HITL) is and how to build an HITL system with LangGraph and Elasticsearch for a flight system.
January 7, 2026
Implementing an agentic reference architecture with Elastic Agent Builder and MCP
Explore an agentic reference architecture with Elastic Agent Builder, MCP, and semantic search to build a security agent for automated threat analysis.
December 18, 2025
Building a local RAG personal knowledge assistant with LocalAI and Elasticsearch
Learn how to create a private, offline local RAG personal knowledge assistant that can summarize meetings and internal reports using e5-small for embeddings and dolphin3.0-qwen2.5-0.5b for completions in Elasticsearch.
December 5, 2025
Build a financial AI search workflow using LangGraph.js and Elasticsearch
Learn how to use LangGraph.js with Elasticsearch to build an AI-powered financial search workflow that turns natural language queries into dynamic, conditional filters for investment and market analysis.