Stephen Batifol

Developer Advocate

Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing.

Engineering

Local Agentic RAG with LangGraph and Llama 3.2

In this blog post, we show you how to build a RAG system using agents with LangChain/ LangGraph, Llama 3.2, and Milvus.

Jun 14, 20249 min read

Engineering

Beyond PGVector: When Your Vector Database Needs a Formula 1 Upgrade

This blog explores why Postgres, with its vector search add-on, pgvector, works well for smaller projects and simpler use cases but reaches its limits for large-scale vector search.

Jan 13, 20256 min read

Engineering

Stop Waiting, Start Building: Voice Assistant With Milvus and Llama 3.2

We'll learn to build a Voice Assistant, a specialized Agentic RAG system designed for voice interactions, with Milvus, Llama 3.2, and other GenAI tools.

Nov 23, 20246 min read

Engineering

Function Calling with Ollama, Llama 3.2 and Milvus

A step-by-step guide on how to integrate Llama 3.2 with external tools like Milvus vector database and APIs to build powerful, context-aware applications.

Jul 30, 20245 min read

Engineering

Kickstart Your Local RAG Setup: A Beginner's Guide to Using Llama 3 LangChain with Ollama and Milvus

Hands on guide to build a Ollama, Llama 3, and Milvus RAG

Apr 19, 20246 min read

Company

Stephen Batifol - Why I Joined Zilliz

Stephen Batifol is the newly joined Developer Advocate at Zilliz.

Mar 06, 20242 min read

Community

Scaling Search for AI: How Milvus Outperforms OpenSearch

Explore how Milvus matches OpenSearch in speed and scalability and surpasses it with its specialized vector search capabilities

Oct 11, 20245 min read

Engineering

ColPali: Enhanced Document Retrieval with Vision Language Models and ColBERT Embedding Strategy

ColPali is an advanced document retrieval model designed to index and retrieve information directly from the visual features of documents, particularly PDFs.

Oct 12, 20247 min read

Engineering

Using Similarity Search - How Not to Lose Meetup Content on the Internet

This tutorial walks you through using the Milvus vector database and sentence transformers to build a smart semantic search for your Meetup content.

Mar 19, 20245 min read