This article provides a complete, practical walkthrough of the Filter Manual Send Triggered n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   **Title:**  
   Intelligent Email Automation with AI: Auto-Categorizing Outlook Emails Using n8n
   
   **Meta Description:**  
   Discover how to intelligently auto-categorize and organize your Outlook emails using n8n and AI. This no-code workflow utilizes Microsoft Outlook and Ollama to sort emails into folders with incredible precision.
   
   **Keywords:**  
   n8n workflow, auto-categorize emails, Outlook automation, AI email classification, Ollama AI, LangChain, Microsoft Outlook API, business automation, no-code AI, filter emails automatically
   
   ---
   
   ## Intelligent Outlook Email Organization Using n8n and AI
   
   Managing a busy inbox can quickly become overwhelming—especially for freelancers and professionals who receive dozens, even hundreds, of emails every day. Manually sorting emails by type, client, or urgency is time-consuming and prone to error. That’s where automation meets artificial intelligence to revolutionize email management.
   
   This article explores an innovative n8n automation workflow that uses AI to auto-categorize Outlook emails. Built by Wayne Simpson from nocodecreative.io, this workflow leverages the power of Ollama’s Qwen 2.5:14b language model and the Microsoft Outlook API to sort inbound messages into folders like “Actioned”, “Business”, “Community”, “Junk”, and more—all without user intervention.
   
   Let’s break down how this workflow works and the value it delivers.
   
   ---
   
   ## The Workflow Overview
   
   At its core, this n8n workflow:
   
   1. Monitors a Microsoft Outlook inbox for unread and unflagged emails.
   2. Prepares the email data by removing HTML and reducing noise.
   3. Sends the parsed information to an AI model for intelligent categorization.
   4. Parses the AI’s output into usable JSON.
   5. Applies categorical labels to the email.
   6. Automatically moves the email into appropriate folders based on classification.
   7. Records errors or edge cases for further inspection.
   
   ---
   
   ### Step 1: Identifying Emails to Process
   
   The workflow begins by scanning the Outlook inbox with specific filters:
   
   ```plaintext
   flag/flagStatus eq 'notFlagged' and not categories/any()
   ```
   
   This ensures only new, unprocessed emails are subject to categorization—avoiding messages already sorted or marked as important.
   
   The Microsoft Outlook node is configured to return key metadata fields such as subject, body, sender, and importance. Emails satisfying the criteria are then looped through for processing.
   
   ---
   
   ### Step 2: Email Sanitization
   
   Emails are often cluttered with HTML formatting and extraneous data. To enable accurate AI categorization, the workflow:
   
   - Converts HTML content to Markdown.
   - Strips unnecessary characters, whitespace, tags, and promotional markup.
   - Packages the refined email into a clean JSON object containing:
     - Subject
     - Body
     - From and Sender information
     - Importance level
   
   This clean format ensures the AI agent receives only the most relevant information.
   
   ---
   
   ### Step 3: AI Categorization with Ollama
   
   Using the n8n LangChain integration, the cleaned email data is sent to Ollama’s Qwen 2.5:14b model via the Langchain AI Agent node.
   
   The AI prompt instructs the AI to select one of seven predefined categories:
   - action
   - junk
   - receipt
   - SaaS
   - community
   - business
   - other
   
   It must also utilize a single sub-category sparingly for deeper context (e.g., a SaaS email that requires action).
   
   The AI responds with a structured JSON object including:
   - The selected category
   - A sub-category (optional)
   - A short reasoning behind its decision
   
   Example Response:
   ```json
   {
     "subject": "Action required: Account update",
     "category": "SaaS",
     "subCategory": "action",
     "analysis": "The subject mentions 'action required' and relates to account changes from a SaaS provider."
   }
   ```
   
   ---
   
   ### Step 4: Categorizing and Organizing Emails
   
   Using Switch and Set nodes, the email is then updated with the AI-generated category and routed to the appropriate Outlook folder:
   
   Example Mappings:
   - junk → “Junk Email” folder
   - receipt → “Receipt” folder
   - SaaS → “SaaS” folder
   - community → “Community” folder
   - business → “Business” folder
   - action (and read) → moved to “Actioned” folder
   
   Each folder move is handled with Microsoft Outlook’s “move” API operation, reinforcing trustful email organization.
   
   The email metadata is also updated using the “update” operation to label it with the chosen category, enabling future filtering and auditing.
   
   ---
   
   ### Step 5: Handling Errors
   
   If the AI output breaks the expected JSON structure, the automation continues gracefully. A dedicated “Catch Errors” branch collects misformatted outputs, allowing the user to inspect failed classifications later without breaking the entire workflow.
   
   This robustness ensures reliability, even when AI occasionally misbehaves.
   
   ---
   
   ## Benefits of This Approach
   
   - 🕐 Saves Time: Say goodbye to manual email sorting.
   - 🧠 Smart Logic: Uses inbox-specific logic combined with AI for superior categorization.
   - 🔄 Continuity: Processes emails continuously without duplicates.
   - 📥 Scalable: Perfect for independent professionals, small teams, or client-based businesses.
   
   A full setup video is also provided so you can follow along visually. Watch it here:  
   📺 [YouTube Demo - Auto Categorise Outlook Emails with AI](https://www.youtube.com/watch?v=EhRBkkjv_3c)
   
   ---
   
   ## Third-Party APIs and Tools Used
   
   1. **Microsoft Outlook API** – For reading, updating, and moving emails.
   2. **LangChain (Agent Node)** – The orchestrator for feeding prompt workflows into language models.
   3. **Ollama - Qwen2.5:14b Model** – AI model responsible for interpreting and categorizing emails contextually.
   
   ---
   
   ## Conclusion
   
   Harnessing AI and automation with a no-code platform like n8n opens a world of possibilities—especially when it comes to organizing and maintaining your inbox effectively.
   
   This Outlook email auto-categorization workflow is a powerful tool for freelancers, businesses, and productivity enthusiasts. Not only does it eliminate hours of manual sorting, but it does so intelligently, adapting to the type and tone of each message.
   
   Ready to let the robots clean up your inbox? Start building your future-proof email workflow today.
   
   ➡️ Built by: [Wayne Simpson](https://www.linkedin.com/in/simpsonwayne/)  
   🌐 Visit: [nocodecreative.io](https://nocodecreative.io)

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.