Search Outlook emails with natural language queries using GPT-4o

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This workflow allows you to search your Outlook mailbox with natural language . You type what you’re looking for (e.g., “invoice from last week”), and the workflow: 1. Uses OpenAI to generate a sea...

Best for

AI RAG automation workflows
Multimodal AI automation workflows
advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.chattrigger, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.merge, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.microsoftoutlook

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Robert Breen.

Original n8n.io source

1.1 Workflow description

Title: Search Outlook emails with natural language queries using GPT-4o
Workflow name: Search Outlook emails with natural language queries using GPT-4o

This workflow allows you to search your Outlook mailbox with natural language. You type what you’re looking for (e.g., “invoice from last week”), and the workflow:

Uses OpenAI to generate a search query.
Searches Outlook emails and ranks them by relevance.
Outputs results in a simple table with score + link to each email.

👉 The number of results can be changed (default: 5).

⚙️ Setup Instructions

1️⃣ Set Up OpenAI Connection

Go to OpenAI Platform
Navigate to OpenAI Billing
Add funds to your billing account
Copy your API key into the OpenAI credentials in n8n

2️⃣ Set Up Outlook Connection

In n8n → Credentials → New → Microsoft Outlook OAuth2 API
Log in with your Outlook account & approve access
Attach this credential to the Search Outlook node in the workflow
(Optional) Change the limit parameter in the node if you want more/less than 5 results

📬 Contact Information

Need help customizing this workflow or building similar automations?

📧 [email protected]
🔗 Robert Breen
🌐 ynteractive.com

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - When chat message received

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.3

Block 2 - Sticky Note21

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 3 - Sticky Note22

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 4 - OpenAI Chat Model5

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 5 - Sticky Note23

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 6 - OpenAI Chat Model6

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 7 - Simple Memory1

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 8 - Structured Output Parser3

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 9 - Merge

Type / Role: n8n-nodes-base.merge - merge
Config choices: Version 3.2

Block 10 - Structured Output Parser5

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 11 - OpenAI Chat Model7

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 12 - Generate Search Term

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2.2

Block 13 - Search Outlook

Type / Role: n8n-nodes-base.microsoftOutlook - microsoftOutlook
Config choices: Version 2

Block 14 - Score if email is relevent to search

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2.2

Block 15 - Output as table for user

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2.2

Block 16 - Convert to one Output

Type / Role: n8n-nodes-base.aggregate - aggregate
Config choices: Version 1

Block 17 - Sticky Note24

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Search Outlook emails with natural language queries using GPT-4o
Complexity	advanced
Nodes	17
Categories	AI RAG, Multimodal AI
Author	Robert Breen
Published	19 Aug 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/7600/7600.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source AI RAG workflows Multimodal AI workflows

Frequently asked questions

What does Search Outlook emails with natural language queries using GPT-4o do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your AI RAG, Multimodal AI use case.

Robert Breen

90 workflows

Nodes

@n8n/n8n-nodes-langchain.chattrigger n8n-nodes-base.stickynote @n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.memorybufferwindow @n8n/n8n-nodes-langchain.outputparserstructured n8n-nodes-base.merge @n8n/n8n-nodes-langchain.agent n8n-nodes-base.microsoftoutlook

Complexity

advanced

Published 19 Aug 2025

Likes 0

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Install path: /data/workflows/7600/7600.json

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Search Outlook emails with natural language queries using GPT-4o

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

⚙️ Setup Instructions

1️⃣ Set Up OpenAI Connection

2️⃣ Set Up Outlook Connection

📬 Contact Information

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - When chat message received

Block 2 - Sticky Note21

Block 3 - Sticky Note22

Block 4 - OpenAI Chat Model5

Block 5 - Sticky Note23

Block 6 - OpenAI Chat Model6

Block 7 - Simple Memory1

Block 8 - Structured Output Parser3

Block 9 - Merge

Block 10 - Structured Output Parser5

Block 11 - OpenAI Chat Model7

Block 12 - Generate Search Term

Block 13 - Search Outlook

Block 14 - Score if email is relevent to search

Block 15 - Output as table for user

Block 16 - Convert to one Output

Block 17 - Sticky Note24

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions