This n8n template helps you turn inbound messages into a clean, deduped queue of actionable tickets.
This n8n template helps you turn inbound messages into a clean, deduped queue of actionable tickets. It includes Slack and Gmail as ready to use examples, but the key idea is the universal intake normalizer: you can plug in other sources later (forms, webhooks, chat tools, other inboxes) as long as you map them into the same normalized schema. Good to know This workflow sends message content to an LLM for classification. Keep sensitive data out of the prompt, and only process messages you are allowed to process. Costs depend on message volume and length, so truncation and tight filters matter. How it works Collect inbound items (Slack and Gmail are included as examples). Normalize each item into one shared JSON format so every source behaves the same. Deduplicate items using a data table so repeats are skipped. Use an AI agent with structured output to score urgency and importance, produce a summary, and draft a reply. Create a Notion ticket for tracking, and optionally notify Slack for high priority items. Setup steps Connect credentials for Slack, Gmail, Notion, and your LLM provider. Choose your Slack channel and set a Gmail filter that keeps volume manageable. Select your Notion database and ensure properties match the field mappings. Create or select a data table and map the unique ID column for deduplication. Adjust the notification threshold and schedule interval to match your workflow. Requirements Slack workspace access (optional if you swap the source) Gmail access (optional if you swap the source) Notion database for ticket creation LLM API credentials Customising this workflow Add new sources by mapping them into the normalizer schema. Truncate long messages before the AI step to reduce cost. Change categories, scoring, and thresholds to match your operating model. An n8n automation workflow template by Paul Karrmann.
Paul Karrmann
web
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