AI Disclosure Checker Workflow (n8n + Groq) with Data Table

Automatically verify AI disclosure clarity in your content (n8n + Groq)

The AI Disclosure Checker Workflow (n8n + Groq) with Data Table scans AI-generated text for an approved AI-transparency disclosure phrase, then uses Groq to judge whether the disclosure is clear and easily noticed. It logs the result and returns a verdict you can act on immediately.

What this workflow does

• Receives input either from another n8n workflow (as a sub-workflow input) or from a manual n8n form submission.
• Loads approved disclosure phrases from an n8n Data Table and scans the content for an exact phrase match.
• Evaluates disclosure clarity with Groq by sending the channel, any matched phrase, and the full content to the Groq chat model (openai/gpt-oss-120b).
• Produces a final verdict in one of: DISCLOSED, DISCLOSED_UNLISTED, MISSING, or MANUAL_REVIEW, including a confidence score and an optional suggested one-sentence disclosure when missing.
• Logs every run to an n8n Data Table with verdict, channel, excerpt, suggestion, phrase, confidence, and notes.
• Returns results either to a completion page (when triggered by the test form) or back to the calling workflow (verdict, found phrase, and suggestion).

Use cases

• Content compliance checks for AI-generated blog posts, landing pages, or product descriptions before publishing.
• SaaS workflows where an authoring step calls n8n to verify AI disclosure policy compliance.
• Operations review queues that route borderline cases to MANUAL_REVIEW with confidence and suggested wording.

Technical details

• n8n nodes: if, set, code, form, data table, sticky note
• Groq integration: Groq API credential + Groq Chat Model node
• Data Tables: one for your approved disclosure phrases; one for logging run results

Set up in minutes: add your Groq credential, create/select the disclosure-phrases Data Table, and populate it with the exact disclosure wordings you want detected.