OpenAI Chat Model node
Microsoft Outlook Trigger node

Reply to Outlook Emails with OpenAI

Published 5 days ago

Created by

ryanh
Ryan

Categories

Template description

Who is this template for?

This template is for any Microsoft Outlook user who wants a trained AI agent to reason and reply on their behalf. Teach your agent tone and writing style to replicate your own, or develop a persona for a shared inbox.

Requirements

  • Outlook with authentication credentials
  • OpenAI account with authentication credentials
  • A few sample email replies of various lengths and topics

How it works:

  1. Connect your Outlook account.

Screenshot 20250305 at 5.27.06 PM.png

  1. Select (filter) which email sender(s) your trained AI agent will reply to.

[Tip: pick a sender that has some repeatability either with a topic (ie. sales) or an individual ([email protected])]

Screenshot 20250305 at 6.22.11 PM.png

  1. Connect your OpenAI account. Choose your AI model (ie. gpt-4o-mini)

Screenshot 20250305 at 5.41.05 PM.png

  1. Add Prompt (User Message) and select "system message" from the option below

Screenshot 20250305 at 5.46.13 PM.png

  1. Update the instructions by filling in your name (or persona), response style, and add full email replies from the topic or individual you want the AI agent to emulate.

[Tip: Add actual replies from your email sent folder, including your greeting and sign off. Paste each email sample between a set of <example> .... </example> tags]

Screenshot 20250305 at 5.47.32 PM.png

  1. Configure the reply (or reply all) to remain within the original email string

Screenshot 20250305 at 6.03.30 PM.png

  1. Test it! Send an email from the address to which your agent wants to respond. Check your sent (or draft) folder for the result.
  2. DRAFT instructions: Instead of the replies sending automatically, you have the option to route them to your draft folder with an easy toggle. Select "add field" at the very bottom and the option will appear. When you are ready to go-live, toggle this setting off.

Screenshot 20250305 at 6.30.21 PM.png

  1. Enjoy all the free time you now have!!
  2. If you have questions or need assistance, email us at: [email protected]

++This template does not include retrieving email addresses out of the message or body of the email.++

Share Template

More AI workflow templates

OpenAI Chat Model node
SerpApi (Google Search) node

AI agent chat

This workflow employs OpenAI's language models and SerpAPI to create a responsive, intelligent conversational agent. It comes equipped with manual chat triggers and memory buffer capabilities to ensure seamless interactions. To use this template, you need to be on n8n version 1.50.0 or later.
n8n-team
n8n Team
HTTP Request node
Merge node
+7

Scrape and summarize webpages with AI

This workflow integrates both web scraping and NLP functionalities. It uses HTML parsing to extract links, HTTP requests to fetch essay content, and AI-based summarization using GPT-4o. It's an excellent example of an end-to-end automated task that is not only efficient but also provides real value by summarizing valuable content. Note that to use this template, you need to be on n8n version 1.50.0 or later.
n8n-team
n8n Team
HTTP Request node
WhatsApp Business Cloud node
+10

Building Your First WhatsApp Chatbot

This n8n template builds a simple WhatsApp chabot acting as a Sales Agent. The Agent is backed by a product catalog vector store to better answer user's questions. This template is intended to help introduce n8n users interested in building with WhatsApp. How it works This template is in 2 parts: creating the product catalog vector store and building the WhatsApp AI chatbot. A product brochure is imported via HTTP request node and its text contents extracted. The text contents are then uploaded to the in-memory vector store to build a knowledgebase for the chatbot. A WhatsApp trigger is used to capture messages from customers where non-text messages are filtered out. The customer's message is sent to the AI Agent which queries the product catalogue using the vector store tool. The Agent's response is sent back to the user via the WhatsApp node. How to use Once you've setup and configured your WhatsApp account and credentials First, populate the vector store by clicking the "Test Workflow" button. Next, activate the workflow to enable the WhatsApp chatbot. Message your designated WhatsApp number and you should receive a message from the AI sales agent. Tweak datasource and behaviour as required. Requirements WhatsApp Business Account OpenAI for LLM Customising this workflow Upgrade the vector store to Qdrant for persistance and production use-cases. Handle different WhatsApp message types for a more rich and engaging experience for customers.
jimleuk
Jimleuk
HTTP Request node
Markdown node
+5

AI agent that can scrape webpages

⚙️🛠️🚀🤖🦾 This template is a PoC of a ReAct AI Agent capable of fetching random pages (not only Wikipedia or Google search results). On the top part there's a manual chat node connected to a LangChain ReAct Agent. The agent has access to a workflow tool for getting page content. The page content extraction starts with converting query parameters into a JSON object. There are 3 pre-defined parameters: url** – an address of the page to fetch method** = full / simplified maxlimit** - maximum length for the final page. For longer pages an error message is returned back to the agent Page content fetching is a multistep process: An HTTP Request mode tries to get the page content. If the page content was successfuly retrieved, a series of post-processing begin: Extract HTML BODY; content Remove all unnecessary tags to recude the page size Further eliminate external URLs and IMG scr values (based on the method query parameter) Remaining HTML is converted to Markdown, thus recuding the page lengh even more while preserving the basic page structure The remaining content is sent back to an Agent if it's not too long (maxlimit = 70000 by default, see CONFIG node). NB: You can isolate the HTTP Request part into a separate workflow. Check the Workflow Tool description, it guides the agent to provide a query string with several parameters instead of a JSON object. Please reach out to Eduard is you need further assistance with you n8n workflows and automations! Note that to use this template, you need to be on n8n version 1.19.4 or later.
eduard
Eduard
Merge node
Telegram node
Telegram Trigger node
+2

Telegram AI Chatbot

The workflow starts by listening for messages from Telegram users. The message is then processed, and based on its content, different actions are taken. If it's a regular chat message, the workflow generates a response using the OpenAI API and sends it back to the user. If it's a command to create an image, the workflow generates an image using the OpenAI API and sends the image to the user. If the command is unsupported, an error message is sent. Throughout the workflow, there are additional nodes for displaying notes and simulating typing actions.
eduard
Eduard
Google Drive node
Binary Input Loader node
Embeddings OpenAI node
OpenAI Chat Model node
+5

Ask questions about a PDF using AI

The workflow first populates a Pinecone index with vectors from a Bitcoin whitepaper. Then, it waits for a manual chat message. When received, the chat message is turned into a vector and compared to the vectors in Pinecone. The most similar vectors are retrieved and passed to OpenAI for generating a chat response. Note that to use this template, you need to be on n8n version 1.19.4 or later.
davidn8n
David Roberts

Implement complex processes faster with n8n

red icon yellow icon red icon yellow icon