by ibrhdotme
This is a simple workflow that grabs HackerNews front-page headlines from today's date across every year since 2007 and uses a little AI magic (Google Gemini) to sort 'em into themes, sends a neat Markdown summary on Telegram. How it works Runs daily, grabs Hacker News front page for this day across every year since 2007. Pulls headlines & dates. Uses Google Gemini to sort headlines into topics & spot trends. Sends a Markdown summary to Telegram. Set up steps Clone the workflow. Add your Google Gemini API key. Add your Telegram bot token and chat ID. **Built on Day-01 as part of the #100DaysOfAgenticAi Fork it, tweak it, have fun!**
by Milorad Filipović
How It works It's very important to come prepared to Sales calls. This often means a lot of manual research about the person you're calling with. This workflow delivers the latest news about businesses you are about to interact with each day. Scans Your Calendar**: Each morning, it reviews your Google Calendar for any scheduled meetings or calls with companies. Fetches Latest News**: For each identified company, it searches the web for the most recent and relevant news articles using newsapi.org Delivers Insights**: You receive personalized emails via Gmail, each dedicated to a company you're meeting with that day, containing a curated list of news headlines, brief descriptions, and direct links to full articles. Setup steps The workflow requires you to have the following accounts set up in their respective nodes: Google Calendar GMail Besides those, there are a few parameters in the node called Setup that can be used to tweak the workflow:
by Extruct AI
Who’s it for: Sales teams, marketers, and analysts who need to quickly access all the social media and public profile links for any company. How it works / What it does: When you enter a company into the form, this workflow automatically searches for and collects all available links to the company’s social media accounts, review sites, and public profiles from sources like Crunchbase and Zoominfo. All discovered URLs are added directly to your Google Sheet. How to set up: Create an Extruct account at www.extruct.ai/. Open the Extruct table template, find the table ID in your browser’s address bar, and copy it. Make a copy of the provided Google Sheets template to your own Google Drive. In n8n, paste the table ID into the variables node of your flow. Set up Bearer authentication in every HTTP Request node using your Extruct API token (found on the API page in Extruct). In the Google Sheets node, paste the link to your copied template and connect your Google account. Run the flow once to load the fields, then map the output fields to the correct columns in your sheet. Activate the flow and start adding companies via the form. Requirements: Extruct account and API token Extruct table template Google account with Google Sheets How to customize the workflow: You can add your own columns to the Extruct table and your Google Sheet. Just add the new column in both places and map it in the Google Sheets node in n8n.
by Matthieu
LinkedIn Profile Enrichment Automation Who is this for? This template is perfect for sales teams, recruiters, marketing professionals, and business development specialists who need to gather comprehensive LinkedIn profile data at scale. Ideal for lead generation teams building prospect databases, recruiters sourcing candidate information, sales professionals researching prospects, and marketing teams creating targeted outreach campaigns. What problem does this workflow solve? Manually collecting detailed information from LinkedIn profiles is incredibly time-consuming and prone to inconsistency. Visiting each profile individually to extract names, job titles, experience, education, skills, and contact details can take hours for even small prospect lists. This automation eliminates the tedious manual data entry while ensuring consistent, comprehensive profile enrichment. What this workflow does This workflow automatically enriches a list of LinkedIn profile URLs by extracting comprehensive professional data including: Personal details** (first name, last name, headline, location) Professional status** (hiring status, open to work indicators) Network metrics** (connections, followers count) Work experience** (up to 5 most recent positions with company details, dates, and roles) Education background** (up to 3 educational institutions with degrees and dates) Skills and languages** (complete skill sets and language proficiencies) Professional summary** (profile description and bio) The enriched data is automatically organized and updated in your Google Sheets database with structured formatting for easy analysis and outreach. Setup Create a Ghost Genius API account and obtain your API key for cookieless LinkedIn profile scraping Configure HTTP Request credentials with Header Auth using your Ghost Genius API key Set up your Google Sheets database using the provided template with columns: URL, Firstname, Lastname, Tagline, Location Connections, Followers, Hiring?, Open to work? Summary, Languages, Skills Experience 1-5, Education 1-3 Configure Google Sheets OAuth2 credentials following n8n's authentication setup guide Add LinkedIn profile URLs to the first column of your Google Sheet to begin enrichment Test the workflow with a small batch before processing larger lists How to customize this workflow Adjust batch processing settings** to handle larger volumes by modifying the batch size and interval timing Add data validation rules** to filter out incomplete or invalid profiles before processing Integrate with CRM systems** like HubSpot or Salesforce to automatically sync enriched data Set up automated scheduling** to regularly re-enrich profiles and capture profile updates Add email notifications** to alert when enrichment batches are completed or encounter errors Customize data mapping** to include additional profile fields or reorganize the output structure Add duplicate detection** to prevent re-processing the same profiles multiple times
by Marth
How it works This workflow runs on a daily schedule. It starts by scraping real estate-related queries from Google using Apify. The organic search results are parsed and summarized into a single text block. That text is then sent to an AI model (GPT-4o) which extracts the top 3 pain points faced by real estate agents based on current online sentiment. The workflow compares today's insights with yesterday's data stored in Airtable to detect recurring or new pain points. Finally, it sends a summary notification via Telegram and stores the current day's insights into Airtable for trend tracking. How to set up Clone or import the workflow into your n8n instance. Get an Apify API token and insert it into the HTTP Request node. Create an Airtable base with a table containing two fields: "Date" (text) and "Summary" (long text). Copy the Base ID and Table ID into the Airtable nodes. Connect your Telegram bot and replace the chat ID in the Telegram node. Set up OpenAI credentials with GPT-4o or GPT-4o-mini for the LLM node. Run once manually to test, then activate the schedule trigger to run daily. (Optional) Extend the flow to generate cold outreach emails based on pain points, or sync to Notion/CRM.
by Yaron Been
Scrape Indeed Job Listings for Hiring Signals Using Bright Data and LLMs How the flow runs Fill the form with job position you're hunting for. Bright data's scraper will scrape Indeed based on your requirments. Workflow waits for the snapshot. Data returns as JSON. Jobs append to Google Sheets. Each row goes to an LLM to analyze if you're a good fit for the job (based on your prompts). The LLMswrites YES or NO next to each job opportunity, helping you find job posts that are relevant to you. What you need Google Sheets with our template. Bright Data dataset and API key. OpenAI key for GPT‑4o mini (or any other LLM). n8n with required nodes. Form fields To Fill Job Location** – city or region. Keyword** – role or skills. Country** – two‑letter code. Setup steps Copy the sheet template link. Import the JSON workflow. Add your credentials in nodes. Test the form manually. Add a schedule if desired. Bright Data filter example [ { "country": "US", "domain": "indeed.com", "keyword_search": "Growth Marketer", "location": "Miami", "date_posted": "Last 24 hours" } ] Tips -Choose Last 24 hours often. -Increase wait time for big snapshots. -Narrow keywords to save credits. **Need help? **Email me anytime: Yaron@nofluff.online YouTube: @YaronBeen LinkedIn: https://www.linkedin.com/in/yaronbeen/ Bright Data Docs: https://docs.brightdata.com/introduction
by Jimleuk
This n8n workflow demonstrates a simple approach to improve chat UX by staggering an AI Agent's reply for users who send in a sequence of partial messages and in short bursts. How it works Twilio webhook receives user's messages which are recorded in a message stack powered by Redis. The execution is immediately paused for 5 seconds and then another check is done against the message stack for the latest message. The purpose of this check lets use know if the user is sending more messages or if they are waiting for a reply. The execution is aborted if the latest message on the stack differs from the incoming message and continues if they are the same. For the latter, the agent receives the buffered messages up to that point and is able to respond to them in a single reply. Requirements A Twilio account and SMS-enabled phone number to receive messages. Redis instance for the messages stack. OpenAI account for the language model. Customising the workflow This workflow should work for other common messaging platforms such as Whatsapp and Telegram. 5 seconds too long or too short? Adjust the wait threshold to suit your customers.
by Leonardo Grigorio
Youtube Video This n8n workflow is designed to assist YouTube content creators in identifying trending topics within a specific niche. By leveraging YouTube's search and data APIs, it gathers and analyzes video performance metrics from the past two days to provide insights into what content is gaining traction. Here's how the workflow operates: Trigger Setup: The workflow begins when a user sends a query through the chat_message_received node. If no niche is provided, the AI prompts the user to select or input one. AI Agent (Language Model): The central node utilizes a GPT-based AI agent to: Understand the user's niche or content preferences. Generate tailored search terms related to the niche. Process YouTube API responses and summarize trends using insights such as common themes, tags, and audience engagement metrics (views, likes, and comments). YouTube Search: The youtube_search node runs a secondary workflow to query YouTube for relevant videos published within the last two days. It retrieves basic video data such as video IDs, relevance scores, and publication dates. Video Details Retrieval: The workflow fetches additional details for each video: Video Snippet: Metadata like title, description, and tags. Video Statistics: Metrics such as views, likes, and comments. Content Details: Video duration, ensuring only content longer than 3 minutes and 30 seconds is analyzed. Data Processing: Video metadata is cleaned, sanitized, and stored in memory. Tags, titles, and descriptions are analyzed to identify patterns and trends across multiple videos. Output: The workflow compiles insights and presents them to the user, highlighting: The most common themes or patterns within the niche. URLs to trending videos and their respective channels. Engagement statistics, helping the user understand the popularity of the content. Key Notes for Setup: API Keys**: Ensure valid YouTube API credentials are configured in the get_videos, find_video_snippet, find_video_statistics, and find_video_data nodes. Memory Buffer**: The window_buffer_memory node ensures the AI agent retains context during analysis, enhancing the quality of the generated insights. Search Term Customization**: The AI agent dynamically creates search terms based on the user’s niche to improve search precision. Use Case: This workflow is ideal for YouTubers or marketers seeking data-driven inspiration for creating content that aligns with current trends, maximizing the potential to engage their audience. Example Output: For the niche "digital marketing": Trending Topic: Videos about "mental triggers" and "psychological marketing." Tags: "SEO," "Conversion Rates," "Social Proof." Engagement: Videos with over 200K views and high likes/comment ratios are leading trends. Video links: https://www.youtube.com/watch?v=video_id1 https://www.youtube.com/watch?v=video_id2
by Aditya Gaur
Who is this template for? This template can be used by any automator who wants to create a workitem(incident/user story/bugs) in azure devops whenever an alert raised by systems. How it works Each time an alert raised in system( for ex: Elastic raises an alert for missing host or domain). Workflow reads an alert and creates a workitem in azure devops Workflow can be customized to send any required information as possible in azure devops Setup Instructions Azure DevOps Organization and Project:** Make sure you have access to an Azure DevOps organization and a project where the work item will be created. Personal Access Token (PAT):** You need a Personal Access Token with permissions to create work items. You can generate a PAT from the Azure DevOps user settings.
by darrell_tw
How it works Fetch all workflows from your n8n instance. Filter workflows that contain nodes with a modelId setting. Extract the node names, model IDs, model names, workflow names, and workflow URLs. Save the extracted information into a connected Google Sheet. Set up steps Connect your n8n API credentials. Connect your Google Sheets account. Replace "Your n8n domain" with your actual domain URL. Use this Google Sheet template to create a new sheet for results. Setup typically takes 5 minutes. Be cautious: if you have over 100 workflows, performance may be impacted. Notes Sticky notes inside the workflow provide extra guidance. This workflow clears old sheet data before writing new results. Make sure your n8n instance allows API access. Result Example Update: It didn't detect the AI model in tool originally. Now it's fixed! Update 20250429: Support 1.91.0 with open node directly! Optimize the url with node id.
by simonscrapes
What this workflow does: This flow uses an AI node to generate Seed Keywords to focus SEO efforts on based on your ideal customer profile. You can use these keywords to form part of your SEO strategy. Outputs: List of 20 Seed Keywords Setup Fill the Set Ideal Customer Profile (ICP) Connect with your credentials Replace the Connect to your own database with your own database Pre-requisites / Dependencies You know your ideal customer profile (ICP) An AI API account (either OpenAI or Anthropic recommended) More templates and n8n workflows >>> @simonscrapes
by David Roberts
AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow performs reliably, by running a test dataset containing different inputs through the workflow. By calculating a metric (score) for each input, you can see where the workflow is performing well and where it isn't. How it works This template shows how to calculate a workflow evaluation metric: whether a specific tool was called by an agent. We use an evaluation trigger to read in our dataset It is wired up in parallel with the regular trigger so that the workflow can be started from either one. More info We make sure that the agent outputs the list of tools that it used We then check whether the expected tool (from the dataset) is in that list Finally we pass this information back to n8n as a metric