A new tutorial demonstrates how to build a powerful Retrieval-Augmented Generation (RAG) system using Google's lightweight Gemma LLM, MongoDB Atlas Vector Search, and open-source models like Mistral or Llama 2. This approach significantly lowers the barrier to creating context-aware AI applications by leveraging accessible open-source tools and managed database services. The integration showcases a practical, cost-effective path for developers to implement sophisticated AI without relying solely on proprietary APIs.