Template description
This workflow enriches new Pipedrive organization's data by adding a note to the organization object in Pipedrive. It assumes there is a custom "website" field in your Pipedrive setup, as data will be scraped from this website to generate a note using OpenAI. Then, a notification is sent in Slack.
⚠️ Disclaimer
This workflow uses a scraping API. Before using it, ensure you comply with the regulations regarding web scraping in your country or state.
Important Notes
-
The OpenAI model used is GPT-4o, chosen for its large input token capacity. However, it is not the cheapest model if cost is very important to you.
-
The system prompt in the OpenAI Node generates output with relevant information, but feel free to improve or modify it according to your needs.
How It Works
Node 1: Pipedrive Trigger - An Organization is Created
This is the trigger of the workflow. When an organization object is created in Pipedrive, this node is triggered and retrieves the data. Make sure you have a "website" custom field in Pipedrive (the name of the field in the n8n node will appear as a random ID and not with the Pipedrive custom field name).
Node 2: ScrapingBee - Get Organization's Website's Homepage Content
This node scrapes the content from the URL of the website associated with the Pipedrive Organization created in Node 1. The workflow uses the ScrapingBee API, but you can use any preferred API or simply the HTTP request node in n8n.
Node 3: OpenAI - Message GPT-4o with Scraped Data
This node sends HTML-scraped data from the previous node to the OpenAI GPT-4o model. The system prompt instructs the model to extract company data, such as products or services offered and competitors (if known by the model), and format it as HTML for optimal use in a Pipedrive Note.
Node 4: Pipedrive - Create a Note with OpenAI Output
This node adds a Note to the Organization created in Pipedrive using the OpenAI node output. The Note will include the company description, target market, selling products, and competitors (if GPT-4o was able to determine them).
Node 5 & 6: HTML To Markdown & Code - Markdown to Slack Markdown
These two nodes format the HTML output to Slack Markdown.
The Note created in Pipedrive is in HTML format, as specified by the System Prompt of the OpenAI Node. To send it to Slack, it needs to be converted to Markdown and then to Slack Markdown.
Node 7: Slack - Notify
This node sends a message in Slack containing the Pipedrive Organization Note created with this workflow.
Share Template
More Sales workflow templates
+4
OpenAI GPT-3: Company Enrichment from website content
Enrich your company lists with OpenAI GPT-3 ↓
You’ll get valuable information such as:
Market (B2B or B2C)
Industry
Target Audience
Value Proposition
This will help you to:
add more personalization to your outreach
make informed decisions about which accounts to target
I've made the process easy with an n8n workflow.
Here is what it does:
Retrieve website URLs from Google Sheets
Extract the content for each website
Analyze it with GPT-3
Update Google Sheets with GPT-3 data
Lucas Perret
+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
+5
Automated Web Scraping: email a CSV, save to Google Sheets & Microsoft Excel
How it works:
The workflow starts by sending a request to a website to retrieve its HTML content.
It then parses the HTML extracting the relevant information
The extracted data is storted and converted into a CSV file.
The CSV file is attached to an email and sent to your specified address.
The data is simultaneously saved to both Google Sheets and Microsoft Excel for further analysis or use.
Set-up steps:
Change the website to scrape in the "Fetch website content" node
Configure Microsoft Azure credentials with Microsoft Graph permissions (required for the Save to Microsoft Excel 365 node)
Configure Google Cloud credentials with access to Google Drive, Google Sheets and Gmail APIs (the latter is required for the Send CSV via e-mail node).
Mihai Farcas
+7
AI web researcher for sales
Who is this for?
This workflow is for all sales reps and lead generation manager who need to prepare their prospecting activities, and find relevant information to personalize their outreach.
Use Case
This workflow allows you to do account research with the web using AI.
It has the potential to replace manual work done by sales rep when preparing their prospecting activities by searching complex information available online.
What this workflow does
The advanced AI module has 2 capabilities:
Research Google using SerpAPI
Visit and get website content using a sub-workflow
From an unstructured input like a domain or a company name.
It will return the following properties:
domain
company Linkedin Url
cheapest plan
has free trial
has entreprise plan
has API
market (B2B or B2C)
The strength of n8n here is that you can adapt this workflow to research whatever information you need.
You just have to precise it in the prompt and to precise the output format in the "Strutured Output Parser" module.
Detailed instructions + video guide can be found by following this link.
Lucas Perret
+2
Gmail AI Auto-Responder: Create Draft Replies to incoming emails
This workflow automatically generates draft replies in Gmail.
It's designed for anyone who manages a high volume of emails or often face writer's block when crafting responses.
Since it doesn't send the generated message directly, you're still in charge of editing and approving emails before they go out.
How It Works:
Email Trigger: activates when new emails reach the Gmail inbox
Assessment: uses OpenAI gpt-4o and a JSON parser to determine if a response is necessary.
Reply Generation: crafts a reply with OpenAI GPT-4 Turbo
Draft Integration: after converting the text to html, it places the draft into the Gmail thread as a reply to the first message
Set Up Overview (~10 minutes):
OAuth Configuration (follow n8n instructions here):
Setup Google OAuth in Google Cloud console. Make sure to add Gmail API with the modify scope.
Add Google OAuth credentials in n8n. Make sure to add the n8n redirect URI to the Google Cloud Console consent screen settings.
OpenAI Configuration: add OpenAI API Key in the credentials
Tweaking the prompt: edit the system prompt in the "Generate email reply" node to suit your needs
Detailed Walkthrough
Check out this blog post where I go into more details on how I built this workflow.
Reach out to me here if you need help building automations for your business.
Nicolas Chourrout
+9
Actioning Your Meeting Next Steps using Transcripts and AI
This n8n workflow demonstrates how you can summarise and automate post-meeting actions from video transcripts fed into an AI Agent.
Save time between meetings by allowing AI handle the chores of organising follow-up meetings and invites.
How it works
This workflow scans for the calendar for client or team meetings which were held online. * Attempts will be made to fetch any recorded transcripts which are then sent to the AI agent.
The AI agent summarises and identifies if any follow-on meetings are required.
If found, the Agent will use its Calendar Tool to to create the event for the time, date and place for the next meeting as well as add known attendees.
Requirements
Google Calendar and the ability to fetch Meeting Transcripts (There is a special OAuth permission for this action!)
OpenAI account for access to the LLM.
Customising the workflow
This example only books follow-on meetings but could be extended to generate reports or send emails.
Jimleuk
More AI workflow templates
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
+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
+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
+4
OpenAI GPT-3: Company Enrichment from website content
Enrich your company lists with OpenAI GPT-3 ↓
You’ll get valuable information such as:
Market (B2B or B2C)
Industry
Target Audience
Value Proposition
This will help you to:
add more personalization to your outreach
make informed decisions about which accounts to target
I've made the process easy with an n8n workflow.
Here is what it does:
Retrieve website URLs from Google Sheets
Extract the content for each website
Analyze it with GPT-3
Update Google Sheets with GPT-3 data
Lucas Perret
+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
+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.
David Roberts
