Classify and route customer feedback with GPT-4o, Gemini, and guardrails

The full end-to-end workflow that chains all patterns together. This template processes customer feedback from intake to team routing, with normalization, validation, native guardrails, AI classification, and confidence-based branching at every step.

What you'll do Send customer feedback through a webhook and watch it flow through every stage. See the data get normalized, validated, and scanned by n8n's native Guardrails node for jailbreak attempts and PII. Watch the AI classify feedback (bug report, feature request, praise, complaint, question) with a confidence score and generate a personalized response draft. See AI-generated responses pass through output guardrails that check for NSFW content and secret keys before reaching users. Watch high-confidence results route automatically: bug reports and feature requests to the product team, complaints to customer success, and praise to marketing as testimonial candidates.

What you'll learn How to chain normalization, validation, native guardrails, AI, and routing into a single pipeline How to use n8n's Guardrails node for both input screening (jailbreak, PII, secret keys) and output screening (NSFW, secret keys) How confidence-based branching separates high-confidence results from items that need human review How Switch nodes route classified feedback to the right destination (product team, customer success, or marketing) How every step between AI nodes is deterministic and inspectable How all these patterns work together in a production-ready workflow

Why it matters This is the complete picture. Individual patterns are useful on their own, but the real power comes from combining them into a pipeline where AI handles the judgment calls and everything else follows explicit, testable rules. Import this template as your starting point and connect your own integrations.