Source attribution for AI personalization: keep a claim ledger

Define the decision

A generated summary often separates text from its origin. Later editors may strengthen the language without realizing the source supported only a narrow observation. A claim ledger preserves that boundary and makes updates possible when the source changes.

Work through the procedure

1. Give each proposed factual claim a short identifier and record its exact supporting URL.
2. Summarize the observed fact in your own words and note the review date and entity match.
3. Write permitted wording and explicitly list unsupported extensions, such as assumed ownership or internal difficulty.
4. When editing the message, compare the final sentence with the ledger rather than assuming earlier approval covers stronger new wording.

Worked example

The following is a synthetic example for this procedure, not a customer result or performance benchmark.

Claim C1
Source: verified company services page
Observed: implementation and ongoing support are listed separately
Permitted: 'Your site lists separate implementation and support services'
Not supported: 'Your teams struggle with handoffs'
Review date: actual date the page was checked

Read the result

The unsupported extension is where many plausible drafts go wrong. The ledger makes the difference explicit for both a human writer and an AI prompt. It also helps remove a stale claim without discarding unrelated verified information about the company.

Check before moving on

1. Ensure URLs open to the actual supporting page.
2. Avoid citing a source that merely repeats an unverified claim from elsewhere.
3. Recheck high-impact facts such as current role, availability and pricing near send time.

Limits and next action

This is a manual evidence record, not automatic citation generation in Zintara. Do not insert a long source dump into a short email merely to look researched. Use enough recipient-facing context for honesty while keeping the detailed review evidence available internally.

Source: Zintara AI writing and review context