Verify AI cold email claims at the sentence level before approval

Define the decision

Claim verification is narrower than reviewing a draft's overall quality. Break compound statements apart so one supported clause does not conceal another unsupported one. Numerical results, customer references and compatibility promises deserve the same scrutiny as prospect-specific facts.

Work through the procedure

1. Extract factual and commercial claims from the final draft.
2. Check identity, date and scope against the relevant source or approved internal evidence.
3. Classify each claim as supported, needs narrower wording or unsupported.
4. Revise or remove failed claims and repeat the check on the changed sentence.

Worked example

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

Draft: 'Your new European offices use our supported system and need faster reporting.'
Claim 1: new offices — source and date required
Claim 2: system in use — separate evidence required
Claim 3: reporting need — not established by either fact
Approved rewrite may retain only the verified office reference and ask an ownership question.

Read the result

The split prevents a plausible sentence from passing as one indivisible fact. It also reveals when the draft contains no meaningful supported personalization. A commercial promise needs evidence from the seller's current capability, not merely a source about the prospect.

Check before moving on

1. Review implied guarantees and causal language.
2. Keep approved evidence accessible to the next reviewer.
3. Do not use model confidence as a substitute for source inspection.

Limits and next action

This is a manual verification method, not automatic fact certification in Zintara. Some claims require specialist or authorized commercial review. When the evidence cannot be resolved, remove the claim or hold the draft.

Source: Zintara product context; procedures and examples are editorial guidance