Mohamed Arbi Nsibi – Medium

Mohamed Arbi Nsibi

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Mohamed Arbi Nsibi

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Aug 3, 2025

How I Built an Agentic RAG System with Qdrant to Chat with Any PDF

Or: How I Built an AI Assistant That Can Read PDFs and Answer Questions Like a Human Would

How I Built an Agentic RAG System with Qdrant to Chat with Any PDF

Mohamed Arbi Nsibi

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Jun 7

TurboQuant: The Compression Shannon Would Approve

Millions of vectors, a fraction of the memory, and almost zero accuracy lost, here’s the math behind it.

TurboQuant: The Compression Shannon Would Approve

Mohamed Arbi Nsibi

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Jun 3

Qdrant 1.18: Faster, Smarter, and Easier Vector Search

1. A More Flexible Future for Vector Databases

Qdrant 1.18: Faster, Smarter, and Easier Vector Search

Mohamed Arbi Nsibi

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Apr 20

Models Decay. Systems Don’t Have To

Notes on MLOps, LLMOps, and what survives.

Models Decay. Systems Don’t Have To

Mohamed Arbi Nsibi

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Apr 5

A Foundational Guide to Neural Search and Relevance Feedback

Have you ever searched a medical database for ‘lung cancer treatments’ only to get 500 blog posts about ‘clean eating’ because they both…

A Foundational Guide to Neural Search and Relevance Feedback

Mohamed Arbi Nsibi

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Mar 16

One model to find them all : Multimodal Search with Gemini 2 and Qdrant

Build a unified multimodal search engine with Gemini embeddings and Qdrant while reducing vector storage costs using Matryoshka…

One model to find them all : Multimodal Search with Gemini 2 and Qdrant

Mohamed Arbi Nsibi

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Dec 29, 2025

One Vector to Serve Them All: Matryoshka with Qdrant

Slicing is all you need !!!

One Vector to Serve Them All: Matryoshka with Qdrant

Mohamed Arbi Nsibi

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Dec 23, 2025

From Fragile to Agentic RAG with SmolAgents, Chonkie, and Qdrant

When RAG isn’t enough, agentic RAG steps in.

From Fragile to Agentic RAG with SmolAgents, Chonkie, and Qdrant

Mohamed Arbi Nsibi

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Dec 16, 2025

Breaking the Memory Wall: A Quantization Guide

You’re scaling your AI application. Then you hit The Memory Wall!! in this piece we will learn about the Secret to 32x Smaller Embeddings…

Breaking the Memory Wall: A Quantization Guide

Mohamed Arbi Nsibi

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Nov 28, 2025

One Collection to Rule Them All: Efficient Multitenancy in Qdrant

1,000 users. Do you create 1,000 vector databases ?

One Collection to Rule Them All: Efficient Multitenancy in Qdrant

Mohamed Arbi Nsibi

Mohamed Arbi Nsibi

A Machine Learning engineer, graduated from SUP’COM and a top rank on Zindi. I’m passionate about MLOps and Generative AI.

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