OpenAI Grounded Lead Scoring Webhook (n8n Workflow)

Ground your AI lead scoring in real submission data—then get an accepted or quarantined verdict

This OpenAI Grounded Lead Scoring Webhook n8n workflow receives inbound lead submissions, uses OpenAI to score and categorize them as structured JSON, and verifies every claimed attribute against the original payload—returning either accepted or quarantined results.

What this workflow does

• Receives a lead via Webhook: accepts an inbound lead payload through an n8n webhook as a POST request.
• Applies a grounding policy: sets allowed categories, exempt judgment fields, numeric tolerance, and optional derivable fields used to validate model outputs.
• Normalizes identification: lowercases and trims the submitted email for consistent identification.
• Scores and categorizes with OpenAI: sends the lead to an OpenAI chat model and parses the response into a required JSON schema (including score, category, confidence, and optional fields like seats and headcount).
• Grounding verification: compares each non-exempt value produced by the model against the original submission and only accepts values that appear in the payload (or are explicitly allowed derivations).
• Returns a JSON verdict: responds with an accepted/quarantined status, the normalized email, and grounding evidence—or the reason for quarantine.

Use cases

• Protect lead pipelines from AI hallucinations by quarantining leads when seats/headcount or category claims aren’t supported by the incoming payload.
• Standardize lead scoring in an n8n automation workflow for SaaS operators who need consistent, structured scoring outputs.
• Implement reliable AI-assisted routing (high/medium/low) with confidence tracking and auditable grounding evidence.

Technical details

• Nodes/stack: webhook, set, code, sticky note, respond to webhook, and n8n-nodes-langchain / LLM (OpenAI chat model integration).
• OpenAI integration: configure an OpenAI API credential on the OpenAI chat model node and select the model you want to use.
• Output: structured JSON parsing + grounding checks driven by “Set grounding policy.”