> ## Documentation Index
> Fetch the complete documentation index at: https://docs.qwedai.com/llms.txt
> Use this file to discover all available pages before exploring further.

# QWED vs RAG for LLM verification

> Compare QWED and RAG for LLM verification, grounded responses, AI reliability, and high-stakes agent workflows.

RAG and QWED address different failure modes.

RAG improves what the model can reference. QWED verifies whether the model's final claim or action is correct.

## Core difference

| Tool | Primary job      | Best at                                                        |
| ---- | ---------------- | -------------------------------------------------------------- |
| RAG  | Retrieve context | Private knowledge, recent information, document grounding      |
| QWED | Verify outputs   | Deterministic validation, policy enforcement, tool-call checks |

## When RAG is enough

Use RAG when the model needs:

* Access to private documents
* Recent facts or changing policies
* Better grounding from source material

## When you need QWED

Use QWED when the model must:

* Produce correct calculations from retrieved data
* Obey policy and approval rules
* Verify tool calls before execution
* Prevent prompt injection from turning retrieved context into unsafe actions

## Best-practice stack

Use both together:

1. RAG retrieves the relevant documents.
2. QWED verifies the answer, decision, or action derived from those documents.

## Related docs

* [LLM verification with formal methods](/advanced/llm-verification)
* [QWED vs Guardrails AI](/advanced/qwed-vs-guardrails)
* [QWED vs Guardrails, RAG, and RLHF for LLM verification](/advanced/comparison)
* [Prompt injection defense and QWED security hardening](/advanced/security-hardening)