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Draft the policy, map it to the rule, and find the gap before the regulator or the auditor does.
No credit card · ChatGPT, Claude, Gemini, Grok and Perplexity in one place
You already do half of this by hand: ask one model, paste the answer into another to check it. Here is what that turned up on a real task for compliance officers.
Does our current policy cover this new requirement?
Auto Verification caught
The requirement was cited in its pre-amendment wording; the check attached the current text, which added a reporting obligation.
The models disagreed
One model said the existing control covers it.
Another said the control covers detection but nothing covers the reporting timeline.
That gap is exactly what an auditor opens with, and it was found in a draft rather than in a finding.
Find the requirement nothing covers.
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The same policy at the length staff will actually read.
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Ask the models how this fails in practice.
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Facts, timeline, gap, remediation — in the order a reviewer reads them.
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Open MultipleChat and turn on AI Collaboration.
Paste the requirement and your control alongside each other.
Read the Disagreements list — a split is usually a genuine ambiguity in the rule.
Verify every citation before it goes into a policy or a board paper.
Routinely. A model's knowledge has a date and regulations do not respect it. Every citation goes through verification, and anything it cannot support against a current source is flagged rather than passed on.
On paid plans nothing you enter trains a model and providers do not retain it. Enterprise adds data isolation, SSO and audit logs if your framework requires them.
The opposite, if you keep the record: what was checked, what the verification found, and where the models disagreed. That is a stronger paper trail than a draft with no provenance.
Not on its own. Use research mode so claims come with live sources attached, and treat anything without a source as unverified.
Yes. Upload it and ask for the obligations that apply to your activity, in a table, with the paragraph reference for each.
It is good at the first pass and finds things people skim past. It will also miss context only you have, which is why the second model matters.
No. It drafts, maps and pressure-tests. Where two models read a clause differently, that is the one to take to counsel.
MultipleChat gives compliance officers ChatGPT, Claude, Gemini, Grok and Perplexity in one workspace — and has them check each other before you use the answer.
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