In this article, you will learn how to build a deterministic, multi-tier retrieval-augmented generation system using knowledge graphs and vector databases. Topics we will cover include: Designing a three-tier retrieval hierarchy for factual accuracy. Implementing a lightweight knowledge graph. Using prompt-enforced rules to resolve retrieval conflicts deterministically. Beyond Vector Search: Building a Deterministic 3-Tiered Graph-RAG System Image by Editor Introduction: The Limits of Vector RAG Vector databases have long since become the cornerstone of modern retrieval augmented generation (RAG) pipelines, excelling at retrieving long-form text based on semantic similarity. However, vector databases are notoriously “lossy” when it comes to atomic facts, numbers, and strict entity relationships. A standard vector RAG system might easily confuse which team a basketball player currently plays for, for example, simply because multiple teams appear near the player’s name in latent space.…