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Validate AI-generated outputs before your workflow acts on them. This template sends a support ticket through AI classification, parses the JSON response, and checks that categories, urgency levels, and confidence scores are all within valid ranges.
What you'll do
- Send a support ticket to the AI for classification.
- Watch the Code node parse and validate the AI's JSON response against a defined schema.
- See how valid outputs continue through the workflow while invalid ones get flagged.
What you'll learn
- How to structure AI prompts to return valid JSON
- How Code nodes parse and validate AI output against expected schemas
- How to check confidence scores, valid categories, and urgency levels programmatically
- How to build retry and fallback paths for malformed AI responses
Why it matters
AI models don't always return what you expect. A confidence score of "high" instead of 0.95, a missing category field, or a malformed JSON response can silently break downstream steps. This template catches those failures before they propagate.
This template is a learning companion to the Production AI Playbook, a series that explores strategies, shares best practices, and provides practical examples for building reliable AI systems in n8n.