Shruti KaushikHR tech companies check AI drafts by saving bias audit status with auditor and date, which features make or support decisions, ATS integrations, data residency and outcome statistics with definitions. Marketing and sales drafts are then run through a claim check that flags fairness, compliance and time-to-hire claims the saved record cannot back.
Where AI drafts go wrong for HR tech companies
Hiring technology is among the most scrutinized uses of AI. New York City's Local Law 144 requires a bias audit of automated employment decision tools and notices to candidates, and its enforcement has itself been audited by the state comptroller. An assistant writing marketing copy has no regard for any of this. It writes "bias-free hiring", "independently audited" and "fully compliant" as freely as it writes adjectives.
Outcome claims are the other half. "Reduces time to hire by half" depends on the definition of hire, the customers measured and the period. A buyer's HR and legal teams will ask. The saved fact should carry the answer.
Claims an AI draft might invent for HR tech companies
These examples are invented for this page to show the pattern. They describe no real company, customer or result.
- "Eliminates bias from hiring" with no audit or definition.
- "Independently audited for bias" when no audit has been completed.
- "Cuts time to hire by 50%" with no measured population.
- "Integrates with every major ATS" when three integrations exist.
- "All data stays in the EU" when sub-processors are elsewhere.
The facts HR tech companies would save once
A saved fact is one sentence you can stand behind, with its source and date. Anything a draft claims that matches none of them is flagged.
- Bias audit status: auditor, date, scope, where the summary is published.
- Which product features make or substantially assist decisions, and which do not.
- ATS and HRIS integrations, live or planned.
- Data residency and sub-processors.
- Outcome statistics with the definition and period.
- Candidate notice language used in regulated jurisdictions.
The workflow
- Save audit status and feature scope. Name legal as owner of anything about compliance.
- Draft web copy, RFP answers and sales emails in your assistant.
- Run the claim check. Paste the audit summary as source text when a draft mentions results.
- Send flagged fairness and compliance claims to legal for sign-off by private link.
- Publish, and keep the approval record.
The method is the one on the draft fact check page: Klype extracts the figures, guarantees, vague authority and stories in a draft, matches each to your saved facts and any source text you paste, flags what it cannot back, and keeps an approval record. It is rule-based, so the same text gets the same answer, and it never publishes or sends anything.
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What the check does not do
It compares claims with the facts you saved and any source text you paste. It does not browse the web, does not verify outside claims and does not replace legal, compliance or editorial review where your work needs it. When it finds nothing checkable, it says nothing was verified, so you still read every draft before it goes out.
Sources
Each source is cited for the single point made above. Klype does not give legal advice; ask your counsel how any rule applies to you.
Common questions
Does the check say whether a tool is covered by Local Law 144?
No. That is a legal question. The check ensures what you say about audits matches what you saved.
Can it check an RFP response?
It checks the statements in the text against saved facts. Long RFPs can be run in sections.
What if the audit is in progress?
Save it as in progress with the date it began. A draft that says audited is flagged.
Where to go next
Read how the check works on the draft fact check page, or try the free post checker without signing up. Related guides: Klype for healthtech companies, Klype for legal tech companies, and Klype for B2B edtech companies. The full list is on the hub.