INDIA-BASED · INTERNATIONAL DELIVERYsupport@maukaz.com
MAUKAZ — Your Technology Partner
Insights/Knowledge & RAG
EXPANDED GUIDE · Knowledge & RAG

Separating conversation memory from factual knowledge

Conversation history helps maintain context, but it should not automatically become authoritative knowledge. Distinguish user statements from approved sources.

Keep conversation context distinct from approved facts

Conversation history can help resolve pronouns, preferences and the current task. It should not automatically become an authoritative source for policies or company information. Label user-provided statements and distinguish them from maintained documents. Decide what information persists, for how long and for which users or tasks.

Worked example

Illustrative scenario; not a claim of measured client results.

If a user says the refund period is sixty days but the current approved policy states otherwise, the assistant should not silently rewrite the policy from the conversation. It can identify the discrepancy and seek clarification through the appropriate route. Similarly, a temporary project preference should not become a permanent organization-wide rule merely because it appeared in one chat.

Checks, limitations and next decisions

When incorrect assumptions recur, inspect what memory was stored and how it is retrieved. Provide a way to correct or remove stale preferences. Keep user boundaries intact so one person's conversation does not affect another's answers improperly. Evaluate memory on task continuity and accuracy, not only whether the assistant appears to remember more details.

A practical starting point

Work through these checks in order. Use the results to decide what needs to change in your own workflow.

  1. Label information by origin and reliability.
  2. Limit memory to what the workflow needs.
  3. Verify factual claims against maintained sources when consequences matter.

A mistake to avoid

Do not store every conversation indefinitely without a defined purpose and appropriate controls.

How to check progress

Review memory-related errors and whether outdated assumptions persist across sessions.

Your action checklist

Use this checklist while reviewing your own setup. Checkmarks are temporary and stay in this open page.

For the wider decision process, read When retrieval is the right addition to an AI assistant.

Further reading

Official background resources for this topic. The workflow above is general guidance, not a guarantee of a particular result.

AI-assisted editorial content. Examples are illustrative, not client case studies. Read our editorial policy or report a correction.