Start with one real case for Grounding and RAG. Record the start and the goal.
Public information should stay clear and consistent. Check copy, sources and data.
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Grounding and RAG: How to measure success
This guide covers Grounding and RAG. Use one real case and keep the next step clear.
What matters in practice
Key rule: Separate external facts from model knowledge and use traceable source context for important answers.
Choose one measure. Compare it before and after the test.
A reliable way to work
Set one question before the test. Decide what result should count.
Name one owner. Record the current state.
Change one point only. Then check the result.
If money, customers or public claims are involved, add a human review.
Check the result again later. Keep only what helps the goal.
Set the goal
- Keep the starting point visible.
- Use facts from the real case.
- Set one clear review point.
- Start with what matters now.
Check the starting point
- Ask when one fact is unclear.
- Separate facts from assumptions.
- Keep the reason for the test visible.
- Check the key facts first.
Change one point
- Return to the start when the result is unclear.
- Change one point only.
- Run a short test.
- Compare the result with the start.
Secure the result
- Record the final state.
- Name the next step.
- Set a date for the next review.
- Keep one owner for the follow-up.
Practical checklist
- Write the goal in one sentence.
- Record the start and one real case.
- Check the key rule.
- Name the owner and approval point.
- Set one measure and one date.
Common mistakes
- Starting without a clear goal.
- Changing several points at once.
- Using a result without a final check.
Concrete example
Example: An SME tests Grounding and RAG with one real case. The team records the start, changes one point and checks the result. Then it plans the next step.
Related guides
At a glance
Four relevant points to understand and check on this page.
What this subject covers
Grounding and RAG: Separate external facts from model knowledge and use traceable source context for important answers.
The rule for this area
AI systems need clear public content, distinct entities and verifiable sources. Extra files do not replace that base.
What this perspective checks
Choose a few metrics that match the goal directly. Compare before and after with the same method.
Check it in practice
Use one real case for Grounding and RAG. Record which rule you tested and whether the result meets the goal.