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Pietro Mele

Pietro Mele is a Software Engineer and Search Consultant at Adelean, with deep expertise in machine learning and hybrid search. Focused on building effective search solutions, he is a lifelong learner and active contributor to the tech community.

Beyond his daily engineering work, he is an official OpenSearch Ambassador and an international public speaker. He further drives the local ecosystem as a co-organizer of both the OpenSearch Paris User Group and the Search, Data and AI meetup.

Articles of Pietro

A Complete Guide to run Jina V5 natively in OpenSearch

14/03/2026

Want to use the newest Jina V5 model in OpenSearch? This guide walks you through the entire process—from downloading and packaging the ONNX weights to successfully registering the model without errors.

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Voxxed Days CERN 2026, where science and technology meet

12/02/2026

On the occasion of this year's edition of Voxxed Days CERN, the iconic Science Gateway in Meyrin transformed once again into a gathering place for software developers, architects, and tech enthusiasts. This one-day event, part of the global Voxxed Days series, focused on software craftsmanship, security and, of course, AI.

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ElasticON Paris 2026, the future is agentic.

28/01/2026

Elastic{ON} Paris 2026 arrived with a bold promise of shaping the future of search. From the stage of the Maison de la Mutualité, one message stood out clearly the future of Elasticsearch is agentic. Beyond this vision, the event delivered concrete product updates, architectural evolutions, and real-world use cases that show how Elastic is evolving across search, observability, and security.

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Towards the future of search with OpenSearch

07/09/2025

Search is evolving faster than ever, and technologies like OpenSearch are leading the way. In this blog, we’ll explore the latest OpenSearch features such as agents and the Model Context Protocol, that unlock new superpowers for building next-generation rag applications.

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AI, Big Data, and Search. Welcome to Berlin Buzzwords 2025

27/06/2025

Berlin Buzzwords 2025 unites leading voices in AI, Big Data, Search, and Scalable Data Infrastructure, all anchored around open-source innovation. From GPUs for LLMs to data sovereignty, from search platforms to real‑time pipelines, this is where ideas meet engineering and where tomorrow’s data landscape takes shape.

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Fine-tuning relevance, reranking techniques in hybrid search

17/04/2025

In this post, we explore how reranking methods like RRF, min-max normalization, L2, and atan boost the performance of hybrid search systems by combining semantic and lexical approaches.

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ElasticON 2025 in Paris

22/01/2025

ElasticON has returned to the capital with plenty of new features and exciting talks. This article wraps up the event.

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Mastering vector search at scale

30/11/2024

Lessons learned from managing a six-billion-vector database, including challenges, insights, and optimization tips.

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A practical guide to prompt engineering

30/09/2024

In recent times, we often hear more and more about prompt engineering. But what exactly is this technique? When and how can we use it?

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Voxxed Days Luxembourg 2024

28/06/2024

This year again, Voxxed Days did not disappoint expectations. Inside this article, you will find a summary of the talks we attended as viewers and as speakers.

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Connecting your LLM to OpenSearch through connectors.

07/05/2024

Recently, OpenSearch implemented connectors, a functionality that enables connecting a machine learning model without the need to internally deploy it to the cluster. In this blog article we will discover how to use connectors and implement a rag through the utilization of connectors and agents.

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Understanding the differences between sparse and dense semantic vectors

31/01/2024

More and more frequently, we hear about semantic search and new ways to implement it. In the latest version of OpenSearch (2.11), semantic search through sparse vectors has been introduced. But what does sparse vector mean? How does it differ from dense matrix? Let's try to clarify within this article.

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A guide to a full Open-Source RAG

01/12/2023

Delving into Retrieval-Augmented Generation (RAG). In this article we explore the foundational concepts behind RAG, emphasizing its role in enhancing contextual understanding and information synthesis. Moreover, we provide a practical guide on implementing a RAG system exclusively using open-source tools and large language model.

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The Art of Image Vectorization - A Guide with OpenSearch

01/10/2023

BLIP-2 is a model that combines the strengths of computer vision and large language models. This powerful blend enables users to engage in conversations with their own images and generate descriptive content. In this article, we will explore how to leverage BLIP-2 for creating enriched image descriptions, followed by indexing them as vectors in Opensearch.

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NLP in OpenSearch

18/06/2023

A practical guide about how to import and use NLP models into OpenSearch for text analysis and inference in your search and analytics workflows

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Diving into NLP with the Elastic Stack

01/04/2023

An overview about NLP and a practical guide about how it can be used with the Elastic stack to enhance search capabilities.

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Exploring Vector Search with JINA. An Overview and Guide

06/02/2023

Learn about vector search and how to implement it using JINA library, including document arrays for vector embedding, image embedding, and more.

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Question answering,a more human-based approach to our research on all.site.

19/01/2023

Everything about Question-Answering and how to implement it using a flask and elasticsearch.

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