AI Workflows
Artificial Intelligence tools and workflows
Automate LinkedIn Post Creation from Articles Using Dumpling AI and GPT-4o
Streamline your LinkedIn content strategy by automatically generating posts from curated articles. This workflow leverages Dumpling AI and GPT-4o to extract insights and create engaging posts with accompanying images.
n8n$9.99Integrate OpenRouter with n8n for Dynamic LLM Model Selection
Enable dynamic selection and configuration of LLM models in n8n versions prior to 1.78 using OpenRouter. This workflow allows you to leverage various LLM models by configuring OpenAI nodes with OpenRouter-specific settings.
n8n$4.99Automate Daily LinkedIn Job Matches via Email
Streamline your job search by automatically receiving top LinkedIn job matches in your inbox daily, tailored to your resume and preferences.
n8n$14.99Automate Your Tweet Scheduling with Google Sheets Integration
This workflow enables users to automate the posting of tweets based on data stored in a Google Sheet. By leveraging a scheduled trigger, it fetches tweets from a designated Google Sheets document at defined intervals, ensuring a steady flow of con...
n8n$11.47Transform YouTube Playlists into Interactive Chatbot Knowledge Bases
This n8n workflow converts YouTube playlists or individual videos into interactive knowledge bases, allowing users to chat with the content and receive summaries and insights without watching the videos.
n8n$24.99Automate Dynamic Video Creation with Luma AI and Airtable
This workflow automates the creation of dynamic videos using Luma AI and n8n, storing results in Airtable for easy access and tracking. It leverages custom prompts and random camera motions to generate visually engaging videos efficiently.
n8n$4.99Generate SEO-Friendly Arabic Articles and Save to Notion
This workflow automatically creates in-depth, SEO-friendly Arabic articles based on any keyword you provide. It researches the topic, generates a full article outline, writes every section in Arabic, and saves the final article directly to your Notion workspace—all in a few clicks. --- ### How It Works - **Step 1:** You submit a simple web form with your keyword and (optionally) an article title. - **Step 2:** The workflow researches the topic using advanced AI, gathers trending questions from Google, and creates a detailed, structured outline. - **Step 3:** Each section of the article is written in Arabic by AI, following best SEO practices and including real FAQs. - **Step 4:** The completed article is automatically formatted and saved to your Notion database, ready for review or publishing. --- ### Setup Instructions - **What you need:** - An **OpenAI API key** (for AI-powered writing and outline generation) - An **OpenRouter API key** (for research via Perplexity/Sonar AI) - A **Notion account** and **Notion API integration** (for saving articles) - A **DataForSEO account** (for fetching Google People Also Ask questions) - **How to set up:** 1. Import the workflow into your n8n instance. 2. Connect your API credentials for OpenAI, OpenRouter, Notion, and (optionally) DataForSEO. 3. Update your Notion database ID in the workflow settings. 4. Deploy the workflow. Fill out the web form to generate your first article. - **Setup time:** 10-20 minutes if you already have your accounts. --- **Tip:** You can fully customize the outline and writing prompts for your target audience or topic. The workflow is modular—easy to adapt for different languages or content styles.
n8n$14.99Automate AI Music and Video Creation from Telegram Ideas
This workflow automates the creation of AI-generated music tracks, cover art, and music videos from ideas submitted via Telegram, managing the process through Google Sheets.
n8n$19.99Automate SRT Subtitle Translation with Google Translate
This workflow automates the translation of SRT subtitle files from one language to another using Google Translate, streamlining the process for content creators and translators.
n8n$9.99Automate Purchase Order Processing from Outlook Excel Attachments Using AI
Streamline the processing of purchase order submissions by automatically extracting and validating data from XLSX attachments in Outlook emails using AI.
n8n$14.99Automate Strava Activity Titles and Descriptions with AI
This n8n workflow connects Strava with an AI service to automatically generate personalized titles and descriptions for new cycling activities, enhancing your Strava posts without manual effort.
n8n$9.99Automate YouTube Video Summaries to Obsidian via Dropbox
Automatically fetch YouTube videos from a playlist, generate detailed summaries using OpenAI, and save them as Markdown files in Dropbox for seamless integration with Obsidian.
n8n$14.99Evaluate AI Agent Response Correctness with OpenAI and RAGAS Methodology
### This n8n template demonstrates how to calculate the evaluation metric Correctness which in this scenario, measures, compares, and classifies the agent's response against a set of ground truths. The scoring approach is adapted from the open-source evaluations project [RAGAS](https://docs.ragas.io/) and you can see the source here [https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_correctness.py](https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_correctness.py) ### How it works - This evaluation works best where the agent's response is allowed to be more verbose and conversational. - For our scoring, we classify the agent's response into 3 buckets: True Positive (in answer and ground truth), False Positive (in answer but not in ground truth), and False Negative (not in answer but in ground truth). - We also calculate an average similarity score on the agent's response against all ground truths. - The classification and the similarity score are then averaged to give the final score. - A high score indicates the agent is accurate, whereas a low score could indicate the agent has incorrect training data or is not providing a comprehensive enough answer. ### Requirements - n8n version 1.94+ - Check out this Google Sheet for a sample data [https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing](https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing)
n8n$14.99Automate Daily Meeting Summaries with Google Gemini AI and Slack
This workflow automates the process of summarizing daily meetings using Google Gemini AI and sends the summaries to a specified Slack channel. It retrieves events from Google Calendar, processes them with the AI model, and delivers concise summaries at a scheduled time.
n8n$9.99Voice-Activated Workflow Automation with Vagent.io, Notion, and Google Calendar
Enable seamless voice interaction with AI agents to automate tasks and manage calendars using Vagent.io, Notion, and Google Calendar.
n8n$14.99Ideal Customer Profile (ICP) Generation: AI, Firecrawl, Gemini, Telegram
# Purpose & Audience This workflow is designed to save hours of manual research for digital marketers, media buyers, copywriters, and business strategists. It empowers users to quickly understand their target customers' behaviors, pain points, desires, and communication preferences by leveraging AI-powered web scraping and natural language processing. Whether you're crafting ad campaigns, refining audience segments, or creating compelling content, this tool provides a powerful shortcut to uncovering your dream buyer's profile directly from the source website and delivered via Telegram. ## How It Works? 1. **Telegram Trigger:** A user sends a message to the Telegram bot, e.g., *"Hey, scrape this website https://www.company.com and find me their ICP. You can scrape 2 pages at most."* 2. **Parameter Extraction:** An AI model processes the message to extract two key parameters: - The company URL - The number of pages to scrape (capped at 3) 3. **Conditional Scraping:** Based on the number of pages: - If 1 page, the workflow calls Firecrawl's /scrape endpoint to scrape that single page. - If more than 1 page, it calls Firecrawl's /crawl endpoint to scrape up to the specified number of pages. 4. **Content Retrieval:** After scraping, the content is fetched and passed to an AI language model. 5. **ICP Generation:** The AI analyzes the website content and answers nine detailed questions about the dream buyer, such as: - Where the dream buyer hangs out online and offline - Their biggest frustrations and challenges - Their hopes, fears, and preferred communication methods - The language and phrases they use - A typical day in their life - What makes them happy 6. **Output Delivery:** The generated ICP is sent back to the user via Telegram in a natural, easy-to-understand format. ### Setup Instructions To get this workflow up and running, you will need the following API credentials: 1. **Telegram Bot API** - Create a free Telegram bot using @BotFather on Telegram. - Follow the prompts to create a new bot and get your API token. - Use this token to create Telegram credentials in n8n. 2. **Firecrawl API** - Sign up for a free account at https://www.firecrawl.dev/. - Obtain your API token from the Firecrawl dashboard. - Create a Header Auth credential in n8n using this token to authenticate your HTTP Request nodes for scraping. 3. **OpenAI or Google Gemini API** - For AI-powered analysis, you need access to a large language model API. - You can use OpenAI's API (free tier available) by signing up at https://platform.openai.com/ and generating an API key. - Alternatively, use Google Gemini if you have access. - Create the corresponding credential in n8n and connect it to the AI nodes in the workflow. ## What It Does? 1. Converts a simple Telegram message into structured scraping instructions. 2. Scrapes website content intelligently, respecting user-defined page limits. 3. Uses AI to deeply analyze business websites and generate actionable customer insights. 4. Provides marketers and media buyers with rich, detailed ICPs that can be used for copywriting, ad targeting, audience research, and content creation. 5. Automates a traditionally time-consuming research process into a seamless conversational experience. ## Summary This workflow enables you to generate a detailed Ideal Customer Profile (ICP) for any company by simply sending a message to a Telegram bot. Using natural conversational language, users provide a company URL and specify how many pages (up to 3) to scrape from the website. The workflow intelligently extracts these parameters, scrapes the website content using Firecrawl's API, and then leverages an AI language model to analyze the content and produce a comprehensive ICP. The ICP answers key questions about the company's dream buyer, helping marketers, media buyers, and copywriters understand their target audience deeply without manual research.
n8n$14.99Automate Voice Cloning with Zyphra Zonos API via n8n
Effortlessly convert text to natural-sounding speech using AI voice cloning with Zyphra Zonos API. Ideal for developers and content creators seeking consistent voice output.
n8n$14.99Evaluate RAG Response Accuracy with OpenAI: Document Groundedness Metric
### This n8n template demonstrates how to calculate the evaluation metric RAG document groundedness, which in this scenario, measures the ability to provide or reference information included only in retrieved vector store documents. The scoring approach is adapted from [https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_groundedness](https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_groundedness) ### How it works - This evaluation works best for an agent that requires document retrieval from a vector store or similar source. - For our scoring, we need to collect the agent's response and the documents retrieved and use an LLM to assess if the former is based off the latter. - A key factor is to look out for information in the response which is not mentioned in the documents. - A high score indicates LLM adherence and alignment, whereas a low score could signal inadequate prompt or model hallucination. ### Requirements - n8n version 1.94+ - Check out this Google Sheet for a sample data [https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing](https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing)
n8n$14.99Automate Research Idea Generation from PDFs Using InfraNodus
This workflow identifies content gaps in PDF documents and generates research questions using InfraNodus GraphRAG, helping researchers bridge knowledge gaps efficiently.
n8n$14.99Extract Pay Slip Data with LINE Chatbot and Geminio to Google Sheets
## Workflow Overview: Extracting text from an image using AI is worthwhile because it requires no code. It incorporates the Google Gemini 2.0 Flash model for important text extraction from images. If you code without AI, you have to use multiple conditions and may cause a lot of bugs, but with Google Gemini, you don't need any coding, and if the Pay Slip is different, Gemini will extract it automatically. ## Workflow Description: 1. The user uses the Line Messaging API to send a Pay Slip image or message to the chatbot. Create a Line Business ID from here: [Line Business](https://account.line.biz/login). 2. Classify the message as either an image or text. 3. If the message is a Pay Slip image, it will be processed using Gemini 2.0 Flash EXP and extract important information and respond in JSON format without coding by using the following prompt: Analyze the image and then return in JSON Response that has the only following values: **Status, From, To, Date, Amount**.  To get the Google AI Studio API Key, you can find it from the following link: [Google AI Studio API Key](https://aistudio.google.com/apikey). 4. Create Google Sheets which include the fields **(Status, From, To, Date, Amount)** that we have created related to the AI prompt [Google Sheets](http://docs.google.com/spreadsheets) as the following example:  5. If the message is text, it will process using the Gemini 2.0 Flash EXP model as the AI Assistant; else if the message is an image, it will extract the important fields, then reply to the user and insert into Google Sheets. ## Key Features: * **Extract text from image with No Code** - Without N8N, we have to write code to extract text from an image, but with N8N and Google Gemini 2.0 Flash EXP together, we don't need to code, and it will process all slip vendors or other document vendors. * **Multipurpose Chatbot** - This chatbot accepts both text and image, so we don't have to create many chatbot accounts. * **Reduce human error** - This workflow lets any officer verify document status when the job ends. **Note:** You can change the information by changing your prompt and also Google Sheets Column names relatively.
n8n$14.99Firecrawl Website Content Extractor
# Firecrawl Website Content Extractor (n8n Workflow) This n8n automation workflow uses **Firecrawl API** to extract structured data (e.g., quotes and authors) from web pages - such as [Quotes to Scrape](https://quotes.toscrape.com/) - and handles retries in case of delayed extraction. --- ## Workflow Overview ### Purpose: - Crawl and extract **structured web data** using Firecrawl - Wait for asynchronous scraping to complete - Retrieve and validate results - Support retries if content is not ready --- ## Step-by-Step Node Breakdown ### 1. **Manual Trigger** - Node: `When clicking test workflow` - Used to **manually test** or execute the workflow during setup or debugging. --- ### 2. **Firecrawl Extract API Request** - Node: `Extract` - Sends a `POST` request to `https://api.firecrawl.dev/v1/extract` - Payload includes: - `urls`: List of pages to crawl (`https://quotes.toscrape.com/`) - `prompt`: Extract all quotes and their corresponding authors from the website. - `schema`: JSON schema defining expected structure (`quotes[]`, each with `text` and `author`) > Uses an **HTTP Header Auth** credential for Firecrawl API --- ### 3. **Wait for 30 Seconds** - Node: `30 Secs` - Gives Firecrawl time to finish processing in the background - Prevents hitting the API before results are ready --- ### 4. **Get Results** - Node: `Get Results` - Performs a `GET` request to the status URL using `{{ $(Extract).item.json.id }}` to retrieve extraction results. --- ### 5. **Condition Check** - Node: `If` - Checks if the `data` array is empty (i.e., no results yet) - If **data is empty**: - Waits **10 more seconds** and retries - If **data is available**: - Passes data to the next step (e.g., processing or storage) --- ### 6. **Retry Delay** - Node: `10 Seconds` - Waits briefly before sending another `GET` request to Firecrawl --- ### 7. **Edit Fields (Optional Output Formatting)** - Node: `Edit Fields` - Placeholder to structure or format the extracted results (quotes and authors) --- ## Sticky Note: Firecrawl Setup Guide Included as an embedded reference: - [10% Firecrawl Discount](https://firecrawl.link/nateherk) - Instructions to: - Add Firecrawl API credentials in **n8n** - Use Firecrawl Community Node for **self-hosted** instances - Set up the schema and prompt for targeted data extraction --- ## Key Features - API-based crawling with schema-structured output - Smart waiting + retry mechanism - AI prompt integration for intelligent data parsing - Flexible for different URLs, prompts, and schemas --- ## Sample Output Schema ```json { "quotes": [ { "text": "The world as we have created it is a process of our thinking. It cannot be changed without changing our thinking.", "author": "Albert Einstein" }, { "text": "It is our choices, Harry, that show what we truly are, far more than our abilities.", "author": "J.K. Rowling" } ] } ```
n8n$4.99Integrate Medium API with MCP Server for AI Agents
Transform the Medium API into an MCP-compatible interface to streamline interactions with AI agents, offering 32 operations for advanced users.
n8n$19.99Automate HTML Document Creation and Hosting with AI and AWS S3
This workflow automates the creation of HTML documents using AI and hosts them on AWS S3. It leverages AI to dynamically generate content and style, offering a flexible and efficient solution for web content delivery.
n8n$9.99Automate AI-Ready Dataset Creation for LLMs Using Bright Data, Gemini, and Pinecone
This workflow automates the extraction, formatting, and storage of web data into AI-ready vector datasets, ideal for training large language models (LLMs). It utilizes Bright Data for web scraping, Gemini for data processing, and Pinecone for vector storage.
n8n$14.99
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