RAG answer QA

Human review for grounded AI answers.

RAG systems can still cite the wrong passage, miss caveats, or answer beyond the retrieved evidence. Use human reviewers to check whether an answer is actually supported by its sources.

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Review checklist

Does each answer claim appear in the retrieved sources?
Are citations specific and relevant?
Are missing caveats or uncertainty notes needed?
Did the answer combine sources incorrectly?
Is the answer safe to show a customer or operator?

Useful for

Support bots, internal knowledge assistants, sales research, compliance-heavy content, policy answers, customer-facing AI search, and agent-generated summaries.

Deliverable

Ask for pass/revise/high-risk status, unsupported claim list, citation/source notes, corrected answer, and reviewer confidence.

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Suggested budget

Start with $50–$200 for a focused answer batch. Larger RAG audits can justify $200–$500+ depending on source complexity and number of answers.

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