Airtable workflows
634 results — 181 downloadable workflow files, 453 source-linked n8n references
W📌 Turn your LinkedIn insights into content ideas with Airtable and Real-Time Linkedin Scraper
🚀 Transform LinkedIn Post Reactions into Content Ideas with Airtable 📝 Description This workflow helps you to turn your LinkedIn activity into a powerful content ideation engine. It captures your most recent post reactions on LinkedIn automatically, filters them based on recency, and structures the content into Airtable—ready for brainstorming, inspiration, or publication planning. ⚙️ What It Does Fetches* the latest liked posts from LinkedIn via a public API (rapidapi.com/Real-Time Linkedin Scraper*). Filters** posts to include only those marked as your decided reaction and posted in the last 7 days. Extracts** the post text, author, links and more. Formats** the data into a database-friendly structure. Saves** the output in Airtable for easy tracking, tagging, or team collaboration. 💡 Use Cases Build a content idea vault from posts you admire. Capture inspiration from thought leaders. Identify trends based on what you find insightful. Supercharge your personal brand or newsletter by turning likes into learning. 🛠 Prerequisites Before using this template, make sure you have: ✅ A RapidAPI account and access to the linkedin-api8 endpoint. ✅ Your RapidAPI key and the target Linke
Store Retell transcripts in Sheets, Airtable or Notion from webhook
Automatically store Retell transcripts in Google Sheets/Airtable/Notion from webhook Overview This workflow stores the results of a Retell voice call (transcript, analysis, etc.) once it has ended and been analyzed. It listens for call_analyzed webhook events from Retell and stores the data in Airtable, Google Sheets, and Notion (choose based on your stack). Useful for anyone building Retell agents who want to keep a detailed history of analyzed calls in structured tools. Who is it for For builders of Retell's Voice Agents who want to store call history and essential analytic data. Prerequisites Have a Retell AI Account Create a Retell agent Associate a phone number with your Retell agent Set up one of the following: An Airtable base and table (example: "Transcripts") A Google Sheet with a “Transcripts” tab A Notion database with columns to match the transcript fields Templates: Airtable Google Sheets Notion How it works Receives a webhook POST request from Retell when a call has been analyzed. Filters out any event that is not call_analyzed (Retell sends webhooks for call_started, call_ended and call_analyzed) Extracts useful fields like: Call ID, start/end time, duration, total c
SAI-powered Student Assistant for Course Information via Twilio SMS
This n8n template offers a simple yet capable chatbot assistant who can answer course enquiries over SMS. Given the right access to data, AI Agents are capable of planning and performing relatively complex research tasks to get their answers. In this example, the agent must first understand the database schema, retrieve lists of values before generating it's own query to search over the database. Checkout the example database here - https://airtable.com/appO5xvP1aUBYKyJ7/shr8jSFDaghubDOrw How it works A Twilio trigger gives us the ability to receive SMS input into our workflow via webhook. The message is then directed to our AI agent who is instructed to assist the user and use the course database as reference. The database is an Airtable base. The agent autonomously figures out which tool it needs to use and generates it's own "filter_by_formula" query to search over the available courses. On successful search results, the Agent can then use this information to answer the user's query. The Agent's output is logged in a second sheet of the Airtable base. We can use this later for analysis and lead gen. Finally, the response is sent back to the user through SMS using Twilio. How to
WGet Qualified Leads in One Click from Apollo to Airtable
You Don’t Need More Tools. You Just Need the Right Leads. Why spend $1,000s on lead gen when your perfect leads are already waiting in Apollo? You’ve already filtered the ideal prospects. You know who they are, where they work, and what they do. Now imagine turning that list into enriched, ready-to-contact leads—without paying pricey Apollo's recurring subscription (spoiler: you will pay only 0.60$ per 500 leads). From Filter to Outreach-Ready in Seconds With the Lead Generation System, you just drop your Apollo search URL. The workflow does the rest: ✅ Scrapes all matching contacts from your Apollo filter ✅ Enriches and organizes the data (names, roles, emails, LinkedIns, companies, etc.) ✅ Delivers the final lead list to Airtable—or your CRM of choice No more manual exports. No CSV mess. No VA needed. Just qualified leads, cleaned and ready to go. Perfect For Founders doing DIY outbound Growth marketers scaling cold email Agencies running lead-gen for clients Anyone tired of paying too much for messy, outdated lists Setup Guide I built a step-by-step guide to setup this workflow in 5 to 10 minutes, available here: https://notanothermarketer.gitbook.io/home/templates/lead-generati
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Automate Call Scheduling with Voice AI Receptionist using Vapi, Google Calendar & Airtable
Who is this template for? This template is ideal for small businesses, agencies, and solo professionals who want to automate appointment scheduling and caller follow-up through a voice-based AI receptionist. If you’re using tools like Google Calendar, Airtable, and Vapi (Twilio), this setup is for you. What problem does this workflow solve? Manual call handling, appointment booking, and email coordination can be time-consuming and prone to errors. This workflow solves that by automating the receptionist role: answering calls, checking calendar availability, managing appointments, and storing call summaries—all without human intervention. What this workflow does This Agent Receptionist manages inbound voice calls and scheduling tasks using Vapi and Google Calendar. It checks availability, books or updates calendar events, sends email confirmations, and logs call details into Airtable. The workflow includes built-in logic for slot management, email triggers, and storing call transcripts. Setup Instructions Duplicate Airtable Base: Use this Airtable base templateBASE LINK Import Workflow: Load provided JSON into your n8n instance. Credentials: Connect your Google Calendar and Airtable
Automate Video Creation with Luma AI Dream Machine and Airtable (Part 2)
Automate Video Creation with Luma AI Dream Machine and Airtable (Part 2) Description This is the second part of the Luma AI Dream Machine automation. It captures the webhook response from Luma AI after video generation is complete, processes the data, and automatically updates Airtable with the video and thumbnail URLs. This completes the end-to-end automation for video creation and tracking. 👉 Airtable Base Template 👉 Tutorial Video Setup 1. Luma AI Setup Ensure you’ve created an account with Luma AI and generated an API key. Confirm that the API key has permission to manage video requests. 2. Airtable Setup Make sure your Airtable base includes the following fields (set up in Part 1): Use the Airtable Base Template linked above to simplify setup. Generation ID** – To match incoming webhook data. Status** – Workflow status (e.g., "Done"). Video URL** – Stores the generated video URL. Thumbnail URL** – Stores the thumbnail URL. 3. n8n Setup Ensure that the n8n workflow from Part 1 is set up and configured. Import this workflow and connect it to the webhook callback from Luma AI. How It Works 1. Webhook Trigger The Webhook node listens for a POST response from Luma AI once video g
CWAutomate Video Creation with Luma AI Dream Machine and Airtable (Part 1)
Automate Video Creation with Luma AI Dream Machine and Airtable (Part 1) Description This workflow automates video creation using Luma AI Dream Machine and n8n. It generates dynamic videos based on custom prompts, random camera motion, and predefined settings, then stores the video and thumbnail URLs in Airtable for easy access and tracking. This automation makes it easy to create high-quality videos at scale with minimal effort. 👉 Airtable Base Template 🎥 Tutorial Video Setup 1. Luma AI Setup Create an account with Luma AI. Generate an API key from Luma AI for authentication. Ensure the API key has permission to create and manage video requests. 2. Airtable Setup Create an Airtable base with the following fields: Generation ID** – To match incoming webhook data. Status** – Workflow status (e.g., "Done"). Video URL** – Stores the generated video URL. Thumbnail URL** – Stores the thumbnail URL. Prompt** – The video prompt used in the request. Aspect Ratio** – Defines the video format (e.g., 9:16). Duration** – Length of the video. 👉 Use the Airtable template linked above to simplify setup. 3. n8n Setup Install n8n (local or cloud). Set up Luma AI and Airtable credentials in n8n.
BStartup Funding Research Automation with Claude, Perplexity AI, and Airtable
Startup Funding Research Automation with Claude, Perplexity AI, and Airtable How it works This intelligent workflow automatically discovers and analyzes recently funded startups by: Monitoring multiple news sources (TechCrunch and VentureBeat) for funding announcements Using AI to extract key funding details (company name, amount raised, investors) Conducting automated deep research on each company through perplexity deep research or jina deep search. Organizing all findings into a structured Airtable database for easy access and analysis Set up steps (10-15 minutes) Connect your news feed sources (TechCrunch and VentureBeat). Could be extended. These were easy to scrape and this data can be expensive. Set up your AI service credentials (Claude and Perplexity or jina which has generous free tier) Connect your Airtable account and create a base with appropriate fields (can be imported from my base) or see structure below. Airtable Base Structure Funding Round Base | Field Name | Data Type | Description | |------------|-----------|-------------| | website_url | String | URL of the company website | | company_name | String | Name of the company | | funding_round | String | The funding
WTechnical stock analysis with Telegram, Airtable and a GPT-powered AI Agent
Video Guide I prepared a detailed guide that demonstrates the complete process of building a trading agent automation using n8n and Telegram, seamlessly integrating various functions for stock analysis. Youtube Link Who is this for? This workflow is perfect for traders, financial analysts, and developers looking to automate stock analysis interactions via Telegram. It’s especially valuable for those who want to leverage AI tools for technical analysis without needing to write complex code. What problem does this workflow solve? Many traders desire real-time analysis of stock data but lack the technical expertise or tools to perform in-depth analysis. This workflow allows users to easily interact with an AI trading agent through Telegram for seamless stock analysis, chart generation, and technical evaluation, all while eliminating the need for manual interventions. What this workflow does This workflow utilizes n8n to construct an end-to-end automation process for stock analysis through Telegram communication. The setup involves: Receiving messages via a Telegram bot. Processing audio or text messages for trading queries. Transcribing audio using OpenAI API for interpretation. Gathe
BGenerate AI Prompts with Google Gemini and store them in Airtable
This workflow is designed to generate prompts for AI agents and store them in Airtable. It starts by receiving a chat message, processes it to create a structured prompt, categorizes the prompt, and finally stores it in Airtable. 2. Setup Instructions Prerequisites AI model eg Gemini, openAI etc** Airtable base and table or other storage tool** Step-by-Step Guide Clone the Workflow Copy the provided workflow JSON and import it into your n8n instance. Configure Credentials Set up the Google Gemini(PaLM) API account credentials. Set up the Airtable Personal Access Token account credentials. Map Airtable Base and Table Create a copy of the Prompt Library in Airtable. Map the Airtable base and table in the Airtable node. Customize Prompt Template Edit the 'Create prompt' node to customize the prompt template as needed. Configuration Options Prompt Template:** Customize the prompt template in the 'Create prompt' node to fit your specific use case. Airtable Mapping:** Ensure the Airtable base and table are correctly mapped in the Airtable node. 4. Running and Troubleshooting Running the Workflow Trigger the Workflow: Send a chat message to trigger the workflow. Monitor Execution: Use the
BCWHacker News Job Listing Scraper and Parser
This automated workflow scrapes and processes the monthly "Who is Hiring" thread from Hacker News, transforming raw job listings into structured data for analysis or integration with other systems. Perfect for job seekers, recruiters, or anyone looking to monitor tech job market trends. How it works Automatically fetches the latest "Who is Hiring" thread from Hacker News Extracts and cleans relevant job posting data using the HN API Splits and processes individual job listings into structured format Parses key information like location, role, requirements, and company details Outputs clean, structured data ready for analysis or export Set up steps Configure API access to [Hacker News](https://github.com/HackerNews/API ) (no authentication required) Follow the steps to get your cURL command from https://hn.algolia.com/ Set up desired output format (JSON structured data or custom format) Optional: Configure additional parsing rules for specific job listing information Optional: Set up integration with preferred storage or analysis tools The workflow transforms unstructured job listings into clean, structured data following this pattern: Input: Raw HN thread comments Process: Extract,
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UTM Link Creator & QR Code Generator with Scheduled Google Analytics Reports
UTM Link Creator & QR Code Generator with Scheduled Google Analytics Reports This workflow enables marketers to generate UTM-tagged links, convert them into QR codes, and automate performance tracking in Google Analytics with scheduled reports every 7 days. This solution helps monitor traffic sources from different marketing channels and optimize campaign performance based on analytics data. Prerequisites Before implementing this workflow, ensure you have the following: Google Analytics 4 (GA4) Account & Access Ensure you have a GA4 property set up. Access to the GA4 Data API to schedule performance tracking. Refer to the Google Analytics Data API Overview for more information. Airtable Account & API Key Create an Airtable base to store UTM links, QR codes, and analytics data. Obtain an Airtable API key from your Account Settings. Detailed instructions are available in the Airtable API Authentication Guide. Step-by-Step Guide to Setting Up the Workflow 1. Generate UTM Links Create a form or interface to input: Base URL** (e.g., https://example.com) Campaign Name** (utm_campaign) Source** (utm_source) Medium** (utm_medium) Term** (Optional: utm_term) Content** (Optional: utm_content
CAutomate Pinterest Analysis & AI-Powered Content Suggestions With Pinterest API
Automate Pinterest Analysis & AI-Powered Content Suggestions With Pinterest API This workflow automates the collection, analysis, and summarization of Pinterest Pin data to help marketers optimize content strategy. It gathers Pinterest Pin performance data, analyzes trends using an AI agent, and delivers actionable insights to the Marketing Manager via email. This setup is ideal for content creators and marketing teams who need weekly insights on Pinterest trends to refine their content calendar and audience engagement strategy. Prerequisites Before setting up this workflow, ensure you have the following: Pinterest API Access & Developer Account Sign up at Pinterest Developers and obtain API credentials. Ensure you have access to both Organic and Paid Pin data. Airtable Account & API Key Create an account at Airtable and set up a database. Obtain an API key from Account Settings. AI Agent for Trend Analysis An AI-powered agent (such as OpenAI's GPT or a custom ML model) is required to analyze Pinterest trends. Ensure integration with your workflow automation tool (e.g., Zapier, Make, or a custom Python script). Email Automation Setup Configure an SMTP email service (e.g., Gmail, Ou
WAutomate Sports Betting Data with the Odds API
Automate Sports Betting Data with TheOddsAPI This workflow enables you to create and update a table using TheOddsAPI for sports betting data. It automatically pulls upcoming Ice Hockey games at the start of the day and updates the table with results at the end of the day. You can modify it to retrieve odds and game data for any sport. This setup is particularly useful for sports betting applications, such as tracking the results of a predictive model. It leverages scheduled triggers to activate HTTP requests, which then create or update fields in Airtable by matching on the game ID. Prerequisites Before implementing this workflow, ensure you have the following: TheOddsAPI Account & API Key Sign up at TheOddsAPI and obtain an API key. Ensure you have the correct API permissions to access sports odds and results. Airtable Account & API Key Create an account at Airtable and set up a database. Obtain an API key from the Account Settings page. API Access & Rate Limits Review TheOddsAPI’s rate limits and ensure your account tier allows for scheduled API calls. Confirm that Airtable API limits align with your expected data retrieval frequency. Step-by-Step Guide to Integrating TheOddsAPI
SAI Social Media Caption Creator creates social media post captions in Airtable
Welcome to my AI Social Media Caption Creator Workflow! What this workflow does This workflow automatically creates a social media post caption in an editorial plan in Airtable. It also uses background information on the target group, tonality, etc. stored in Airtable. This workflow has the following sequence: Airtable trigger (scan for new records every minute) Wait 1 Minute so the Airtable record creator has time to write the Briefing field retrieval of Airtable record data AI Agent to write a caption for a social media post. The agent is instructed to use background information stored in Airtable (such as target group, tonality, etc.) to create the post. Format the output and assign it to the correct field in Airtable. Post the caption into Airtable record. Requirements Airtable Database: Documentation AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) Example of an editorial plan in Airtable: Editorial Plan example in Airtable For this workflow you need the Airtable fields "created_at", "Briefing" and "SoMe_Text_AI" Feel free to contact me via LinkedIn, if you have any questions!
Microsoft Outlook AI Email Assistant with contact support from Monday and Airtable
Microsoft Outlook AI Email Assistant Prerequisites 1. Microsoft 365 Login Credentials Provide your Office 365 credentials to connect Outlook. 2. Monday.com Generate an API token and have a board with your contact details. 3. Airtable Obtain an API key (or personal access token) and set up a base to store: Contacts (populated by the Monday.com sync). Rules & Categories (used by the AI Email Assistant). Use this Airtable base as the template: Airtable AI Email Assistant Template. Define your own rules, categories, and delete rules. 4. OpenAI API Key Sign up for OpenAI if you don’t already have an account. Generate a new API key at OpenAI API Keys. What the System Does 1. Daily Contact Sync (Monday.com → Airtable) Runs once a day to pull the latest contacts from Monday.com and store or update them in Airtable. 2. AI Email Categorisation & Prioritisation Fetches Outlook emails with filters. Cleans and processes email content. Matches emails with known contacts from Airtable. Uses an AI agent to classify, categorise, and prioritise emails. Updates Outlook categories and importance based on AI results. Runs in parallel with Airtable rules & categories retrieval for real-time decision-mak
WVoiceflow Demo Support Chatbot
Submission Overview for Voiceflow Demo Workflow View the YouTube video for this workflow here. Who is this for? This workflow is ideal for businesses and developers using Voiceflow to power AI voice chatbots. It benefits teams that want to enhance chatbot functionality through integrations with platforms like Zendesk, Google Calendar, and Airtable. What problem is this workflow solving? The workflow addresses the need for seamless integration of chatbot interactions with backend systems. It automates customer service tasks such as ticket creation, meeting scheduling, and data reporting, reducing manual effort and enhancing efficiency. What does this workflow do? Customer Lookup:** Checks the database for existing customers and returns relevant details or a "NOT_FOUND" status. Zendesk Ticket Creation:** Automates the creation of support tickets for customer issues. Meeting Scheduling:** Integrates with Google Calendar to provide availability and schedule meetings. Transcript Reporting:** Aggregates interaction data and sends it to Airtable for analysis by the product team. Setup Configure your Voiceflow chatbot to connect to this workflow via a webhook. Set up the required integrati
Sync New Files From Google Drive with Airtable
This workflow automatically fetches newly uploaded files from a specific folder in Google Drive, shares them via email with specified recipients, and logs the file details (name, ID, created time, modified time) into Airtable for easy tracking. It streamlines the process of file sharing and management while keeping track of important metadata in a central place. Step-by-Step Instructions Google Drive Node (Fetch New File) Action: This node fetches newly uploaded files from the specific folder you’ve mentioned in your Google Drive. Configuration: Set the folder ID in the Google Drive node where the files are uploaded. Use the “New File in Folder” trigger to automatically detect new files added to the folder. Send Email Node (Share File via Email) Action: After detecting the new file, this node shares the file via email with the recipient you specify. Configuration: Set the recipient's email address. Include the file URL from the Google Drive node in the email body, allowing easy access to the file. Add the file name as part of the email subject or body to notify the recipient about the new file. Airtable Node (Store File Metadata) Action: This node stores the file’s metadata, such a
HR Job Posting and Evaluation with AI
Workflow Documentation: HR Job Posting and Evaluation with AI Detailed Description The HR Job Posting and Evaluation with AI workflow is designed to streamline and enhance recruitment for technical roles, such as Automation Specialists. By automating key stages in the hiring process, this workflow ensures a seamless experience for both candidates and HR teams. From collecting applications to evaluating candidates using AI and scheduling interviews, this workflow provides an end-to-end solution for recruitment challenges. Who is this for? This workflow is ideal for: HR Professionals**: Managing multiple job postings and candidates efficiently. Recruitment Teams**: Handling large volumes of applications for technical positions. Hiring Managers**: Ensuring structured and objective candidate evaluations. What problem does this workflow solve? Time-Consuming Processes**: Automates repetitive tasks like data entry, CV management, and scheduling. Fair Candidate Evaluation**: Leverages AI to provide objective insights based on resumes and job descriptions. Streamlined Communication**: Ensures timely and personalized candidate interactions, improving their experience. What this workflow doe
BCWAI Data Extraction with Dynamic Prompts and Airtable
This n8n template introduces the Dynamic Prompts Ai workflow pattern which are incredible for certain types of data extraction tasks where attributes are unknown or need to remain flexible. The general idea behind this pattern is that the prompts for requested attributes to be extracted live outside the template and so can be changed at any time - without needing to edit the template. This seriously cuts down on maintainance requirements and is reusable for any number of tables at little cost. Check out the video demo I did for n8n Studio here: https://www.youtube.com/watch?v=_fNAD1u8BZw Check out the example Airtable here: https://airtable.com/appAyH3GCBJ56cfXl/shrXzR1Tj99kuQbyL Looking for the Baserow Version? https://n8n.io/workflows/2780-ai-data-extraction-with-dynamic-prompts-and-baserow/ How it works Given we have an "input" field for context and a number of fields for the data we want to extract, this template will run in the background to react to any changes to either the "input" or fields and automatically update the rows accordingly. The key is that Airtable fields have a special property called the "field description". In this pattern, we use this property to allow the
WGet Daily Weather and Save It in Airtable
This smart automation workflow created by the AI development team at WeblineIndia, helps with the daily collection and storage of weather data. Using the OpenWeatherMap API and Airtable, this solution gathers vital weather details such as temperature, humidity, and wind speed. The automation ensures daily updates, creating a dependable historical record of weather patterns for future reference and analysis. Steps: Set Schedule Trigger Configure a Cron node to trigger the workflow daily, for example, at 7 AM. Fetch Weather Data (HTTP Request) Use the HTTP Request node to retrieve weather data from the OpenWeatherMap API. Include your API key and query parameters (e.g., q=London, unit=metric) to specify the city and desired units. Parse Weather Data Utilize a JSON Parse node to extract key weather details, such as temperature, humidity, and wind speed, from the API response. Store Data in Airtable Use the Airtable node to insert the parsed data into the designated Airtable table. Ensure proper mapping of fields like temperature, humidity, and wind speed. Save and Execute Save the workflow and activate it to ensure weather data is fetched and stored automatically every day. Outcome Th
Store Form Submission in Airtable
This workflow, developed by our AI developers at WeblineIndia, is designed to automate the process of capturing form submissions and storing them in Airtable. By leveraging automation, it eliminates manual data entry, ensuring a smooth and efficient way to handle form data. The purpose of creating this workflow is to streamline data management, helping businesses save time, reduce errors, and maintain an organized, structured database for easy access and future use. Steps: Trigger on Form Submission (Form Node)** What It Does: Activates the workflow whenever a form is submitted. How to Set It Up: Use the Form Submission Trigger node to detect new form submissions. This ensures the workflow starts automatically when a user fills out the form. Store Data in Airtable (Airtable Node)** What It Does: Transfers the form data into an Airtable base. How to Set It Up: Use the Airtable Node to map form fields to corresponding columns in your Airtable table, storing the data accurately. Finalize and Activate** What It Does: Completes the setup to automate data storage upon form submission. How to Set It Up: Save and activate the workflow. Once active, it will automatically record all new form
AI Agent to chat with Airtable and analyze data
Video Guide I prepared a detailed guide that shows the entire process of building an AI agent that integrates with Airtable data in n8n. This template covers everything from data preparation to advanced configurations. Youtube Link Who is this for? This workflow is designed for developers, data analysts, and business owners who want to create an AI-powered conversational agent integrated with Airtable datasets. It is particularly useful for users looking to enhance data interaction through chat interfaces. What problem does this workflow solve? Engaging with data stored in Airtable often requires manual navigation and time-consuming searches. This workflow allows users to interact conversationally with their datasets, retrieving essential information quickly while minimizing the need for complex queries. What this workflow does This workflow enables an AI agent to facilitate chat interactions over Airtable data. The agent can: Retrieve order records, product details, and other relevant data. Execute mathematical functions to analyze data such as calculating averages and totals. Optionally generate maps for geographic data visualization. Dynamic Data Retrieval: The agent uses user p
WAI Agent for project management and meetings with Airtable and Fireflies
Video Guide I prepared a comprehensive guide detailing how to create a Smart Agent that automates meeting task management by analyzing transcripts, generating tasks in Airtable, and scheduling follow-ups when necessary. Youtube Link Who is this for? This workflow is ideal for project managers, team leaders, and business owners looking to enhance productivity during meetings. It is particularly helpful for those who need to convert discussions into actionable items swiftly and effectively. What problem does this workflow solve? Managing action items from meetings can often lead to missed tasks and poor follow-up. This automation alleviates that issue by automatically generating tasks from meeting transcripts, keeping everyone informed about their responsibilities and streamlining communication. What this workflow does The workflow leverages n8n to create a Smart Agent that listens for completed meeting transcripts, processes them using AI, and generates tasks in Airtable. Key functionalities include: Capturing completed meeting events through webhooks. Extracting relevant meeting details such as transcripts and participants using API calls. Generating structured tasks from meeting d