AI & RAG Systems·5 min read

RAG vs Decision Trees: Why Document Grounding is the Only Safe Customer Support AI

Why rule-based decision trees fail and how Retrieval-Augmented Generation with strict citation guardrails guarantees zero hallucinations.

The Problem with Traditional Support Bots

Traditional chatbot builders rely on brittle flowchart decision trees. If a customer phrases a question slightly differently, the bot either repeats an unhelpful generic script or gets trapped in a dead-end loop.

How Lune AI Implements Deterministic RAG

Zeqalune's Lune AI replaces manual flowcharts with modern semantic Retrieval-Augmented Generation:

  • Vector Ingestion: Sitemaps, FAQ documents, and PDF manuals are chunked and vectorized in isolated per-workspace indices.
  • Hybrid Semantic Search: When a question arrives, the engine retrieves the exact relevant excerpts from verified documentation.
  • Strict Grounding Guardrails: The LLM is instructed to synthesize answers strictly from retrieved context. If the answer is not present, it gracefully initiates a human handoff instead of hallucinating.
  • Source Citations: Every response includes a direct citation tag, building immediate customer trust.

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