Have you been monitoring your RAG chatbot every day, wondering whether it is making things up, after expecting it to become your internal encyclopaedia as soon as it was introduced? This is a common issue caused by the complexity of updating AI knowledge, even though organisational policies and manuals change frequently. The moment a chatbot adopts a document incorrectly, it can cause significant confusion through incorrect guidance instead of improving work efficiency.
The first issue to check is the retrieval of incorrect information
The quality of answers from a RAG AI chatbot depends largely on how accurately it finds documents relevant to the question.
Even if a user asks about the latest HR policy, if an older document is selected during the retrieval process, the AI will answer based on that content. No matter how detailed the explanation in the generated answer is, it cannot be used in actual work if the evidence it relies on is incorrect.
Why are files that differ only by year more easily confused?
Corporate policies and work guidelines often have similar titles and overall structures even after revisions. Most sentences in the 2024 and 2026 HR policies may be the same, with only some items—such as the effective date, number of leave days and application deadline—being different.
Because RAG finds documents with meanings similar to the question, it may judge both policies to be highly relevant. If the document’s effective date, version and application status are not separately distinguished, the previous policy may be selected as the basis for the answer.
Clevi Lens is designed to identify even subtle numerical changes and provide accurate information.
Now, without any waiting time, practitioners can easily manage AI knowledge themselves.
Previously, internal AI required users to request updates from developers and wait for the work to be completed.
Now, however, non-developers can easily manage AI knowledge themselves, without any waiting time.
With Clevi Lens, business users can add and edit documents or exclude them from search in the management interface. Non-developers can reflect work changes when needed and check the results of their application.
Reliable internal AI is managed continuously
RAG chatbots need their knowledge to be updated whenever regulations and manuals change. The application status of the latest documents must be managed and superseded materials distinguished so that the chatbot can provide answers aligned with current work standards.
- Register the latest regulations and work manuals
- Manage effective dates and versions for each document
- Exclude expired materials from searches
- Update knowledge with a focus on work 담당자
- Check the knowledge status applied to the chatbot
You can find detailed Clevi Lens features on the product page below.