Build an n8n AI Agent for Email Triage

What an Email Triage Agent Actually Does

The agent monitors one or more inboxes via IMAP or Gmail. Every new message gets pulled into an n8n workflow, parsed for content and metadata, then sent to an LLM for classification. The LLM returns a priority level (urgent, high, normal, low) and a category (support, sales, billing, internal, spam). Based on that output, the workflow routes the email: urgent support tickets go straight to Slack, sales inquiries get forwarded to your CRM, and spam gets archived automatically.

No rules engine. No keyword matching that breaks the moment someone phrases things differently. The LLM understands context, so "our production database is down" gets flagged urgent even if the subject line says "quick question."

Architecture: LLM, Tools, and Memory

The core n8n ai agent workflow has four layers:

Trigger: An IMAP or Gmail trigger node polls for new messages every 60 seconds. You can also use a webhook if your email provider supports push notifications.

Preprocessing: A code node strips HTML, extracts the plain-text body, sender address, subject line, and any previous thread context. Keeping the payload clean reduces token usage and improves classification accuracy.

LLM Classification: The cleaned email hits an OpenAI or Anthropic node with a system prompt that defines your categories and priority rules. The prompt includes examples of each category so the model has clear boundaries. You return structured JSON—not free text—so downstream nodes can parse it reliably.

Routing: A switch node reads the JSON output and branches accordingly. Urgent emails trigger a Slack message and create a ticket in Linear or Jira. Sales inquiries push a contact into HubSpot. Low-priority messages get labelled and archived in Gmail.

For teams handling high volume, add a simple memory layer: store sender history in a Postgres table so the agent can factor in past interactions. A sender who emailed three times this week about the same issue should escalate automatically.

Example Prompt and Output

Here is a concrete system prompt you would use in the LLM node:

"You are an email triage assistant. Classify the following email into exactly one category: support, sales, billing, internal, spam. Assign a priority: urgent, high, normal, low. Return JSON only: {"category": "...", "priority": "...", "summary": "..."}. An email is urgent if it mentions downtime, data loss, security breach, or a deadline within 24 hours."

Given an email with subject "API returning 500 errors since this morning" from a known customer, the agent returns:

{"category": "support", "priority": "urgent", "summary": "Customer reports 500 errors on API since morning, likely production incident"}

That output triggers a Slack alert in #incidents and creates a P1 ticket in Linear. Total time from email received to ticket created: under 10 seconds.

Limitations and Edge Cases

LLMs are not perfect classifiers. Sarcasm, ambiguous language, and emails that span multiple categories will occasionally get misrouted. A message that is both a billing complaint and a cancellation threat needs human judgement.

Thread context is another challenge. If someone replies to a sales thread with a support issue, the agent may classify based on the original thread topic. Stripping thread history and classifying only the latest reply helps, but it loses context.

Token costs add up at scale. If you process 1,000 emails per day, budget for the API spend. Use a smaller model (GPT-4o mini or Claude Haiku) for classification—you do not need a frontier model to sort emails.

Finally, false urgency is real. The agent will flag anything mentioning "ASAP" or "urgent" as high priority, even when it is not. Tune your prompt with negative examples to reduce this.

When to Hire an Agency

A basic triage workflow takes a few hours to build in n8n. But production-grade email triage—with sender reputation scoring, multi-language support, n8n integrations with your existing CRM and ticketing tools, custom escalation logic, and proper error handling—takes real engineering time. If email is a core business process, the cost of getting it wrong outweighs the cost of getting help.

An experienced n8n automation team can build, test, and deploy a triage agent that handles your specific edge cases from day one. No trial-and-error with prompt engineering. No broken workflows at 3 AM.