A convincing answer can still be wrong. Evaluate whether it matches current source material and helps a person complete the actual task.
Build a test set from everyday work
Collect questions from the people who will use the system, including different ways of asking the same thing. For each, record the expected answer, source, conditions, and responsible reviewer. Avoid testing only examples chosen for a demonstration.
Check the evidence behind the answer
Open the cited document and verify that it supports the statement, numbers, and exceptions. Check versions and effective dates. A citation is useful only when the reader can locate the relevant passage and is allowed to view it.
Test missing information and ambiguity
Ask about a rule that is absent, a question missing necessary details, and conflicting documents. A useful response should explain its limits, request clarification, or direct the person to an owner rather than inventing a confident procedure.
Verify permissions and sensitive cases
Use different roles to test both answers and document access. Information restricted to one group should not appear in another group’s response. Test attempts to make the system ignore its rules or disclose restricted material.
Keep reviewing after launch
Classify failures: missing documents, poor retrieval, outdated content, or an incorrect answer. Assign owners, fix causes, and rerun the same questions after changes. Start with a small group, retain human escalation, and track practical usefulness alongside accuracy.
Before you start
- Prepare real questions and expected evidence.
- Test missing, ambiguous, and conflicting information.
- Check answers and source access for different roles.
- Assign review, updates, and regression checks.
Your next step
Bring representative questions and the documents that should answer them. We can define a pilot with clear acceptance criteria and a way to improve it over time.
AI knowledge base systems · Contact us
Features, third-party support, fees, and delivery scope are subject to assessment and the current agreement.
Further reading
Answering the same questions every day? Where to start with an AI knowledge base
References and example assumptions
References follow the Traditional Chinese edition. Numerical scenarios illustrate calculation methods; they are not customer results, service quotes, or guarantees. Monetary examples are in New Taiwan dollars (TWD). Cover images illustrate service concepts.