Enterprise AI Architecture Explained | RAG, Agentic AI, MCP, LLM, Vector Database & Guardrails
Many discussions around Enterprise AI focus on LLMs, RAG, or Agentic AI, but very few explain what actually happens between a user pressing Enter and the AI generating a response. I created a short visual walkthrough th
Many discussions around Enterprise AI focus on LLMs, RAG, or Agentic AI, but very few explain what actually happens between a user pressing Enter and the AI generating a response.
I created a short visual walkthrough that explains the complete Enterprise AI Architecture in simple termsβfrom Redis Cache, Orchestrator, Memory, RAG, Embeddings, Vector Database, Reranking, AI Agents, Guardrails, and Observability to the final LLM response.
π₯ Watch here: https://youtu.be/l8RhKc6-fdo
I'd genuinely appreciate your feedback. Which architectural layer do you think has the biggest impact on production-ready AI systems?
EnterpriseAI #GenAI #RAG #AgenticAI #AIArchitecture
Connect in Linkedin:https://www.linkedin.com/in/msgobinath
Originally published by Dev.to AI. Aggregated on AIWithGhost for educational purposes β full credit and traffic to the original publisher.