0-30%
Usually less concerning, but still verify if the context matters. A clean score does not prove human authorship.
Business
Business writing fails when it sounds generic, over-friendly, too polished or disconnected from the customer’s actual situation. A humanizer can help, but only if it protects facts, keeps brand voice and avoids leaking sensitive information.
Score reading
Use the score to decide what to inspect. Short text, formulaic writing, non-native English, heavy editing and translated drafts can all move the result.
Usually less concerning, but still verify if the context matters. A clean score does not prove human authorship.
Read highlighted passages. Look for repeated sentence shapes, vague claims, generic intros and a rhythm that feels too uniform.
Review seriously, but do not punish automatically. Ask for drafts, notes, revision history and context before drawing conclusions.
Use cases
| Draft type | AI problem | Humanized fix |
|---|---|---|
| Customer email | Vague empathy and filler apologies. | Specific issue, clear next step, accountable tone. |
| Proposal | Generic value claims. | Client-specific pains, scope and measurable outcomes. |
| Support reply | Too long or evasive. | Short answer, steps, escalation path. |
| Internal memo | Over-polished and empty. | Decision, tradeoffs, owner and deadline. |
Workflow
Do not paste secrets, customer data or contract details unless the tool is approved for that data.
Tell the model who will read it and what outcome you need.
Check names, numbers, promises, dates and legal claims before sending.
Related guides
These pages cover the common user paths around detectors, false positives, humanizers and policy.
FAQ
Yes, if the draft is reviewed, facts are verified and privacy rules are followed.
Secrets, customer personal data, unreleased financials, legal strategy or anything your company policy forbids.
MultipleChat can help when a team wants several AI models to rewrite and critique the same draft side by side, but final review remains human.