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Check AI answers against company documents to save money

This guide explains how to use a cheaper AI assistant to answer questions, check its work against company documents, and only pay for a more expensive AI or ask a human when the first answer fails.

Original by OpenRouterEvaluation

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Credits

“Cut LLM Cost with a Jev-Verified Cascade” by OpenRouter. Read the original source.

This expanded guide is an AI-narrated adaptation prepared by JevMade. It expands the source’s essential ideas, examples and caveats in JevMade’s own words and is not a word-for-word reading. The synthetic voice does not imitate the author or imply their endorsement.

Our summary

This guide shows how to build a system that answers customer questions using a cheaper AI assistant. Businesses use this setup to save money on software costs while making sure the messages sent to users are actually based on official company documents.

A basic AI assistant writes a draft answer using retrieved source documents. Then, Jev—an AI tool that chooses from options rather than writing an answer—checks if the draft uses the evidence and addresses the question. Failed drafts go to a stronger AI or a human.

This approach is useful for customer support teams who want to lower their software bills safely. However, the results happened in a small test of fifty questions. The system still sent some answerable questions to a human, meaning it will not perfectly handle every message.

Key takeaways

  1. Require the AI assistant to actually answer the customer's question instead of just repeating facts.
  2. Record every choice the software makes so you can track your total costs and mistakes.
  3. Send the message to a human worker if neither the cheap nor the expensive AI succeeds.

The fifty-question trial is a small and noisy test, not a guarantee of zero mistakes. It also handed off two answerable questions to a human instead of solving them.

OpenRouter cookbook · Source reviewed

Read the original guide Opens the author’s site in a new tab.