RAG Pipelines in Practice: Building Production Retrieval-Augmented Generation — Visual Explainer

ChatGPT doesn't know your company -- here's how to fix that? Let's break it down visually. A visual breakdown of RAG Pipelines in Practice: Building Production Retrieval-Augmented Generation. We explain the core concept, how it works under the hood, why it matters for modern AI systems, and how it connects to the broader landscape of large language models and system design. In this visual explainer, we cover: → Rag pipeline production architecture → Chunking strategies for rag → Hybrid search vector keyword rag → Reranking in retrieval augmented generation → Rag evaluation metrics and failure modes 🧠 Topic: RAG Pipelines in Practice: Building Production Retrieval-Augmented Generation 📚 Series: Understanding Intelligence by arcGenesis A researcher-style deep dive into the concepts powering modern AI and systems. Timestamps: See description for chapter markers. #retrieval-augmented #machinelearning #techexplained #architecture #arcgenesis #strategies #production #generation #llamaindex #evaluation #pipelines #practice: 🔗 Sources & papers: 📎 PremAI - Building Production RAG Architecture (2026) — https://www.premai.io/blog/building-produc... 📎 AlphaCorp - RAG Pipeline Architecture: Seven Stages — https://alphacorp.ai/blog/rag-pipeline-arc... 📎 Unstructured - Best Practices for RAG in Production — https://unstructured.io/insights/rag-syste... 📎 Dev.to - Build a Production-Ready RAG System (2026) — https://dev.to/dharshan_a_23835c7dc05682/b... 📎 Atolio - Enterprise RAG in 2026: Challenges and Best Practices — https://www.atolio.com/blog/enterprise-rag... 🔔 Subscribe for deep visual explainers on AI, LLMs, and system design! © arcGenesis — Making complex tech visual.