Airtable and OpenAI integration

Shopify Digital Product Automation (from just and image to complete Shopify product page.) This Shopify Digital Product Automation is an advanced n8n-powered workflow that leverages AI (Google Gemini), Airtable, and Shopify API to generate product details from images and automatically post them to Shopify. It fully automates the process — from uploading images to publishing Shopify products — with minimal manual effort. 💡 Key Advantages Our Shopify Digital Product Automation offers five core advantages: 🔗 Shopify Product Sync — Automatically posts product details including title, description, SEO fields, and matched category to Shopify. ✍️ AI-Powered Product Generation — Gemini analyzes uploaded images and generates engaging, SEO-friendly product titles, descriptions, and metadata. 🗂️ Structured Output — Outputs JSON-ready product data compatible with Shopify, ensuring smooth automation. 📄 Airtable Integration — Tracks uploaded images, analyzed data, and generated products to prevent duplication. 📤 End-to-End Automation — Handles the complete workflow from image upload to Shopify posting without manual intervention. ⚙️ How It Works The workflow follows a step-by-step automated process: Step-by-Step Process Upload Images – Add your digital artwork or poster images to Google Drive and record them in Airtable. Image Analysis – AI fetches new images and analyzes visual elements like characters, series, poster text, and style. Store Analysis Results – Updates analyzed data in Airtable and marks images as Used. Fetch Shopify Collections – Retrieves current collections from your Shopify store for category matching. Generate Product Details – Gemini generates product title, description, matched category, SEO page title, meta description, and URL handle. Save Generated Products – Stores generated product details in Airtable and marks them as generated. Post Products to Shopify – Automatically creates new products in Shopify using the API. Update Status – Marks products as posted in Airtable after successful posting. 🛠️ Setup Steps Required Node Configuration To implement this workflow, configure the following n8n nodes: Trigger Node** – Start workflow manually or via scheduler. Airtable Node** – Fetch raw images and store processed product details. Google Drive Node** – Access image files. HTTP Request Node** – Fetch Shopify collections. Code Node** – Refine AI outputs and format product data. Split & Limit Nodes** – Process images and products in batches. LangChain / Gemini Node** – Generate product titles, descriptions, and SEO data. Shopify Node** – Create products via Shopify API. Status Update Node** – Update Airtable with processing and posting status. 🔐 Credentials Required Before running the workflow, ensure you have the following credentials configured: Shopify Access Token** – For posting products and fetching collections. Gemini API Key** – For AI-powered product generation. Airtable API Key** – For storing and tracking workflow data. Google Drive OAuth** – To access image files. 👤 Ideal For This automation workflow is designed for: Shopify store owners managing hundreds of digital products Ecommerce teams automating product listings Marketing teams needing scalable, AI-driven product content workflows 💬 Bonus Tip The workflow is fully modular and customizable. You can extend it to: Automatically assign prices or discounts Multi-language product description generation Social media promotion of new products Email campaign integration All extensions can be implemented within the same n8n flow, making it a complete digital product automation solution.

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. Gathering and displaying charts based on user-specified parameters. Performing technical analysis on generated charts. Sending back the analyzed results through Telegram. Setup Prepare Airtable: Create simple table to store tickers. Prepare Telegram Bot: Ensure your Telegram bot is set up correctly and listening for new messages. Replace Credentials: Update all nodes with the correct credentials and API keys for services involved. Configure API Endpoints: Ensure chart service URLs are correctly set to interact with the corresponding APIs properly. Start Interaction: Message your bot to initiate analysis; specify ticker symbols and desired chart styles as required.

Who’s it for Recruiting agencies, executive search firms, and in-house talent teams that want to automate candidate sourcing and prequalification. Instead of spending hours searching, scoring, and writing outreach, this workflow turns any job description into a ready-to-use shortlist with personalized messages. Youtube Walkthrough What it does (How it works) This workflow takes a job description (title, description, and location) and runs a complete recruiting automation pipeline: Normalize job titles** and generate variations to widen search coverage. Search candidates** in Apollo (or your CRM / database of choice). Remove duplicates** to keep clean lists. Score candidates** with AI (0–5) and provide concise reasoning across experience, industry, and seniority. Enrich LinkedIn profiles** (name, title, image, location, experience). Create structured candidate assessments** (summary, alignment, red flags, positives). Generate outreach messages** (email + LinkedIn DM) tailored to the candidate. Write to Airtable** for job/candidate tracking and downstream automation. Everything is plug-and-play, with no manual searching or copy-pasting required. Requirements n8n (Cloud or self-hosted) Airtable account + API access Apollo API or your preferred candidate source LLM provider: OpenAI or Anthropic LinkedIn enrichment API (RapidAPI, Apify, etc.) > ⚠️ Do not hardcode API keys in HTTP nodes. Always use Credentials in n8n. Airtable table specifications Create one base (e.g., Candidate Search – From Job Description) with two tables: Jobs Table Job Title (text) Job Description (long text) Job Location (text) Candidates (linked to Candidates table) Candidates Table Core fields: Name, LinkedIn URL, Job Title, Location, Image URL, Job Searches (linked) Assessment fields: Summary Fit Score, Executive Summary, Title Alignment, Skill Alignment, Industry Alignment, Seniority Alignment, Company Type Alignment, Educational Alignment, Potential Red Flags, Positive Signals, Final Recommendation, Next Steps Suggestion Outreach fields: Email Subject, Email Body, LinkedIn Message How to set up Connect credentials Add Airtable, Apollo/CRM, and OpenAI/Anthropic credentials under n8n Credentials. Create Airtable base/tables Follow the above spec for Jobs and Candidates. Match field names exactly to avoid mapping errors. Configure the trigger The workflow starts from a Form/Webhook node. It captures: Job Title (required) Job Description (required) Location (required) Target Companies (optional, comma-separated domains) Job title mutation The workflow uses an AI node to normalize the job title and generate up to 5 variations for broader candidate searches. Candidate search Apollo (or your CRM API) is queried with the generated titles and location filters. Results are deduped. AI scoring & structuring Candidates are scored 0–5 with clear reasoning (experience, industry, seniority, general fit). Profiles are formatted into structured JSON for Airtable. LinkedIn enrichment Enrichment API fetches missing data (geo, image, job history). Candidate assessment An AI model produces a full recruiter-ready evaluation (fit summary, strengths, red flags). Outreach generation The workflow drafts a concise cold email (<75 words) and LinkedIn DM (<60 words), consultative in tone. Write to Airtable All jobs and candidates (with assessments and outreach messages) are logged for review and integration. How to customize Swap Apollo with your CRM** (Greenhouse, Bullhorn, etc.). Adjust scoring prompts** to match your niche (sales, engineering, healthcare). Add custom filters** for target companies or industries. Change outreach tone** to align with your brand voice. Limit by score** (e.g., only push candidates with score ≥4). Security & best practices Store all keys in n8n Credentials (never in nodes). Use Set nodes to centralize editable variables (title, location, filters). Always add sticky notes in your workflow explaining steps. Rename nodes clearly for readability. Troubleshooting No candidates found?** Loosen title variations or broaden location. Low fit scores?** Refine keywords and required skills in scoring prompts. Airtable errors?** Double-check Base ID, Table ID, and field names. API rate limits?** Enable batching/pagination and increase intervals. SEO title: Build candidate shortlists from a job description to Airtable with Apollo, AI scoring, and personalized outreach Keywords: recruiting automation, Apollo people search, candidate enrichment, AI scoring, Airtable recruiting CRM, LinkedIn outreach, n8n workflow template

How it works This powerful automation turns LinkedIn influencer activity into high performing Amazon seller content, fully hands-off. It runs in two phases: AI Content Generator Retrieves influencer usernames from Airtable Scrapes their most recent LinkedIn post via Apify Uses OpenAI (GPT-4o) to generate original Amazon focused post content Generates a branded LinkedIn image using AI (WeSpark visual identity) Saves content & image link to Google Drive Creates a record in Airtable with Status = In review Scheduled Publisher Every day at 4 PM, one post from Airtable with Status = Approved is: Downloaded from Drive Published on LinkedIn Marked as Posted in Airtable ⚙️ Set Up Steps Time to set up:** 15–20 minutes Create two Airtable tables: influencers with UserName (LinkedIn usernames only) posts with fields: Description (text) Image (Drive link) InfluencerUsername InfluencerPost InfluencerPostCreatedAt Status (In review, Approved, Posted, Rejected) Add Google Drive OAuth2 credentials for saving & downloading images Configure OpenAI GPT-4o key (for text + image generation) Set up Apify LinkedIn scraper and add header credentials Link your LinkedIn account (company or personal profile) Workflow Phases AI Generator (Triggered manually) Loops over influencer usernames Scrapes latest LinkedIn post Skips if already stored Uses GPT-4o to: Rewrite the post uniquely for Amazon sellers Generate JSON with text + image prompt Saves AI-generated image to Google Drive Logs post to Airtable with In review status Daily Publisher (Scheduled) Runs every day at 4 PM Filters Airtable for Status = Approved Picks 1 record, downloads image from Drive Publishes to LinkedIn Updates Airtable status to Posted Airtable Setup Example influencers Table: | UserName | | ----------- | | jon-derkits | posts Table: | Description | Image | InfluencerUsername | InfluencerPost | InfluencerPostCreatedAt | Status | | ------------------------------ | ------------- | ------------------ | --------------- | ----------------------- | --------- | | Amazon Listing Optimization... | \[Drive Link] | jon-derkits | \[LinkedIn URL] | 2025-06-18 19:30:01 | In review | Status field options: In review Approved Posted Rejected Example LinkedIn Visuals | Caption | Image | | -------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------- | | Boost Your Amazon ROI! Data-driven strategies are your secret weapon... | View Image | | Boost Sales with 5–10% Higher Conversions! Utilize Enhanced Brand Content and Smart PPC... | View Image | | Grow Your Amazon Business WeSpark – Amazon Consulting Agency... | View Image | | Amazon Growth Strategies Embrace the power of smart optimization... | View Image | ✅ Best For: Amazon agencies and FBA consultants B2B SaaS tools targeting eCommerce LinkedIn ghostwriters and creators Content marketing teams for Amazon sellers

Video Introduction Invoice Processing Automation This template is the automation behind a simple incoming invoice automation tool (AP automation) tool built in Airtable. Link to the Airtable base, and all other tools used, is in notes on the left of the automation. How it works See how it works on video: Full Video Walkthrough 1) We get an email with an invoice attachment: 2) Processes and adds the data to an Airtable interface: 3) Once we approved it and Due date approaches, it shows among Due invoices, where we can track if it's paid. Looking for customization or a custom business app? 📞 Book a Call | 💬 DM me on Linkedin

Who is this for? This template is designed for content creators, marketing teams, educators, or media managers who want to repurpose video content into written blog posts with visuals. It's ideal for anyone looking to automate the process of transforming YouTube videos into professional blog articles and custom images. What problem is this workflow solving? Creating written content from video material is time-consuming and manual. This workflow solves that by automating the entire pipeline: from detecting new YouTube video uploads to transcribing the audio, turning it into an engaging blog post, generating a matching visual, and saving both in Airtable. It saves hours of work while keeping your blog or social feed active and consistent. What this workflow does This automation listens for new YouTube videos added to a Google Drive folder, extracts the full transcript using Dumpling AI, and sends it to GPT-4o to generate a blog post and image prompt. Dumpling AI then turns the prompt into a 16:9 visual. The blog and visual are saved into Airtable for easy publishing or curation. Setup Google Drive Trigger Create a folder in Google Drive and upload your YouTube videos there. Link this folder in the "Watch Folder for New YouTube Videos" node. Enable polling every minute or adjust as needed. Download & Prepare the Video The video is downloaded and converted into base64 format by the next two nodes: Download Video File and Convert Downloaded Video to Base64. Transcription with Dumpling AI The base64 video is sent to Dumpling AI’s extract-video endpoint. You must have a Dumpling AI account and an API key with access to this endpoint: Dumpling AI Docs Generate Blog Content with GPT-4o GPT-4o takes the transcript and generates: A human-like blog post A descriptive prompt for AI image generation Make sure your OpenAI credentials are configured. Generate the Visual The prompt is passed to Dumpling AI’s generate-ai-image endpoint using model FLUX.1-pro. The result is a clean 1024x576 image. Save to Airtable Blog content is stored under the Content field in Airtable. The image prompt is also added to the Attachments column as a visual reference. Ensure Airtable base and table are preconfigured with the correct field names. How to customize this workflow to your needs Change the GPT prompt to alter the tone or format of the blog post (e.g., add bullet points or SEO tags). Modify the Dumpling AI prompt to generate different image styles. Add a scheduler or webhook trigger to run at different intervals or through other integrations. Connect this output to Ghost, Notion, or your CMS using additional nodes. 🧠 Sticky Note Summary Part 1: Transcription & Blog Prompt Watches a Google Drive folder for new video uploads. Downloads and encodes the video. Transcribes full audio with Dumpling AI. GPT-4o writes a blog post and descriptive image prompt. Part 2: Image Generation & Airtable Save Dumpling AI generates a visual from the image prompt. Blog content is saved to Airtable. The image prompt is patched into the Attachments field in the same record. ✅ Use this if you want to automate repurposing YouTube videos into blog content with zero manual work.

💅 AI Agents Generate Content & Automate Posting for Beauty Salon Social Media 📲 Who Is This For? This workflow is for beauty salons who want consistent, high‑quality social media content without writing every post manually. It also suits agencies and automation builders who manage multiple beauty brands and want a reusable, AI‑driven posting system they can adapt per client. What Problem Is This Workflow Solving? Many beauty businesses struggle to post regularly because research, copywriting, and design all take time and marketing skills. This workflow automates research, writing, image creation, and posting, so your channels stay active and relevant while you focus on clients and services. What This Workflow Does Generates short, engaging posts tailored to a beauty‑salon audience (hair, nails, skincare, make‑up, self‑care) using an AI agent. Uses Tavily Internet Search to pull up‑to‑date information and trends based on a reference link or topic. Turns each post into a detailed, photorealistic image prompt and creates a matching visual with an AI image model (for example, gpt‑image‑1 or other connected providers). Automatically sends the final text and image to Telegram, and can be extended to other social platforms from the Split Out node. How It Works Trigger the workflow Scheduled automatic generation:** Run the parent workflow on a schedule (for example, once per day at 9 AM) to publish new content regularly. Google Sheets trigger:** Generate content when a new row with a reference link or topic is added to your sheet. Use it when you manage ideas or briefs in Google Sheets and want the workflow to react as soon as a new idea appears. RSS Feed trigger:** Start the workflow when new items appear in a selected RSS feed. Ideal for turning fresh blog posts, news, or industry updates into social media content or automated summaries. Meta (Facebook/Instagram) webhook:** Use the Meta Reference trigger to fire the workflow on incoming webhooks from Meta (for example, new comments, messages, or events). Helpful when you want to auto‑respond, log activity, or generate follow‑up content from Meta activity. Airtable trigger:** Start the workflow when records in a selected Airtable base/table change (for example, a new idea, brief, or status update), so your posts react instantly to updates in your Airtable content board. Postgres trigger:** Fire the workflow when new rows are inserted or existing rows are updated in a connected PostgreSQL table, letting you drive content generation from events in your app database or Supabase‑style back end. Manual start:* Hit Execute workflow* whenever you want to spin up a batch of posts on demand, test new prompt settings, or debug the flow step by step. Research and generate copy The GENERATE TEXT agent calls Tavily to gather fresh information on the topic. It writes a post under 1024 characters with a hook, practical tips, relevant hashtags, and a closing line with your salon address and contact. Create the visual The GENERATE PROMPT agent converts the post into a single, clear description of the scene (client, service, salon interior, lighting, mood) with a strict “no text on image” rule. An image model such as gpt‑image‑1 or one of the HTTP image APIs renders a matching beauty visual. Distribute the content The Split Out node fans out the result so Telegram receives a photo post with the generated caption. Additional social or content nodes (for example Facebook, LinkedIn, X, template tools) can be wired after this step for multi‑channel posting. How to Customize This Workflow to Your Needs Brand voice** Edit the system message in the GENERATE TEXT node to adjust tone (luxury, friendly, clinical, playful), language, services, and city. Update the final address and phone line to match your salon details. Topics and triggers** Point the Google Sheets Trigger to your own document ID, sheet, and columns for ideas, links, or campaign themes. Use the Schedule Trigger for fully automatic posting or rely on the Manual Trigger for controlled, batch generation sessions. Models and providers** Swap GPT‑5 llm and the default image model for alternatives such as Mistral, Gemini, Anthropic, DeepSeek, or custom HTTP image APIs by enabling the corresponding nodes and adding credentials. Channels and outputs** Connect or remove social nodes after Split Out depending on which platforms you actively use. Add extra processing steps (for example resizing images or adding UTM parameters) before each channel if needed. Visual style** Tweak the GENERATE PROMPT instructions to control composition (close‑up vs. full‑body), color palette, lighting, and overall salon aesthetic, while keeping the constraint of no text or logos in the image.

How it works • Automates multi-platform social media posting (Instagram, YouTube, TikTok, etc.) using AI-generated content • Integrates Airtable, n8n, and Blotato for full content scheduling and publishing • Supports both image and video uploads with dynamic text and account routing Set up steps • Takes ~15–30 minutes to set up depending on how many platforms you connect • Requires Airtable personal access token and Blotato API key • Uses sticky notes throughout the workflow to explain config, tokens, and troubleshooting clearly

> Reach out to me for any setup help/consulting. Automate the curation and sharing of trending GitHub discussions from Hacker News to Twitter and LinkedIn. This workflow leverages AI to generate engaging posts, streamlining your social media content creation and distribution. How it Works Crawl Hacker News for GitHub Posts: The workflow fetches trending GitHub-related discussions from Hacker News. Extract Key Information: Relevant data such as post titles, URLs, and metadata are extracted and filtered to focus only on unposted content. Fetch Additional Details: For each GitHub post, the workflow retrieves extra information from the GitHub repository page to enrich the post content. Generate Social Media Posts: Using AI, the workflow automatically generates tailored posts for Twitter and LinkedIn based on the collected data. Post to Twitter & LinkedIn: The generated content is posted to your Twitter and LinkedIn accounts. Track and Log Posts: Each post is logged in Airtable for tracking, and its status is updated to ensure no duplicate posts are made. Telegram Notification: After posting, a summary of the posts is sent to your Telegram chat for real-time updates. Requirements n8n Account**: Set up and configured. Sign up here. API Credentials**: Valid keys for LinkedIn, Twitter, Airtable, OpenAI, and Telegram. Airtable Base**: Configured with fields such as Title, URL, Post Content, Status, and Timestamp. Get started with Airtable. Telegram Chat ID**: For receiving real-time notifications. Set Up Steps Clone the Workflow: Import the workflow into your n8n environment using the provided JSON. Configure API Credentials: Enter your API keys for LinkedIn, Twitter, Airtable, OpenAI, and Telegram into the respective nodes. Set Up Airtable Base: Create an Airtable base with fields such as Title, URL, Post Content, Status, and Timestamp. Customize Telegram Chat ID: Modify the 'Ping me' node with your Telegram chat ID to receive notifications. Run the Workflow: Activate the workflow to start the automated content curation and posting process. Additional Resources n8n AI Agentic Workflows Guide n8n AI Workflow Tutorial n8n Community Tutorial on Building an AI-Powered Telegram Bot > Note: Chat GPT prompt should/can be tweaked in the step to give the desired behaviour. Sample Posts from my X and LinkedIn -**

Who is it for? This workflow is for marketers, sales teams, and local businesses who want to quickly collect leads (business name, phone, website, and email) from Google Maps and store them in Airtable. You can use it for real estate agents, restaurants, therapists, or any local niche. If you need a professional automation agency to build advanced lead generation systems like this, check out Vision IA's n8n automation services. How it works Scrape Google Maps with Apify Google Maps Extractor. Clean and structure the data (name, address, phone, website). Visit each website and retrieve the raw HTML. Use GPT to extract the most relevant email from the site content. Save everything to Airtable for easy filtering and future outreach. It works for any location or keyword – just adapt the input in Apify. Requirements Before running this workflow, you’ll need: ✅ Apify account (to use the Google Maps Extractor) ✅ OpenAI API key (for GPT email extraction) ✅ Airtable account & base with the following fields: Business Name Address Website Phone Number Email Google Maps URL Airtable Structure Your Airtable base should contain these columns: Airtable Structure | Title | Street | Website | Phone Number | Email | URL | |-------------------------|-------------------------|--------------------|-----------------|------------------------|----------------------| | Paris Real Estate Agency| 10 Rue de Rivoli, Paris | https://agency.fr | +33 1 23 45 67 | [email protected] | maps.google.com/... | | Example Business 2 | 25 Avenue de l’Opéra | https://example.fr | +33 1 98 76 54 | [email protected] | maps.google.com/... | | Example Business 3 | 8 Boulevard Haussmann | https://demo.fr | +33 1 11 22 33 | [email protected] | maps.google.com/... | Error Handling Missing websites:** If a business has no website, the flow skips the scraping step. No email found:** GPT returns Null if no email is detected. API rate limits:** Add a Wait node between requests to avoid Apify/OpenAI throttling. Now let’s take a detailed look at how to set up this automation, using real estate agencies in Paris as an example. Step 1 – Launch the Google Maps Scraper Start with a When clicking Execute workflow trigger to launch the flow manually. Then, add an HTTP Request node with the method set to POST. 👉 Head over to Apify: Google Maps Extractor On the page: https://apify.com/compass/google-maps-extractor Enter your business keyword (e.g., real estate agency, hairdresser, restaurant) Set the location you want to target (e.g., Paris, France) Choose how many results to fetch (e.g., 50) Optionally, use filters (only places with a website, by category, etc.) ⚠️ No matter your industry, this works — just adapt the keyword and location. Once everything is filled in: Click Run to test. Then, go to the top right → click on API. Select the API endpoints tab. Choose Run Actor synchronously and get dataset items. Copy the URL and paste it into your HTTP Request (in the URL field). Then enable: ✅ Body Content Type → JSON ✅ Specify Body Using JSON` Go back to Apify, click on the JSON tab, copy the entire code, and paste it into the JSON body field of your HTTP Request. At this point, if you run your workflow, you should see a structured output similar to this: title subTitle price categoryName address neighborhood street city postalCode ........ Step 2 – Clean and structure the data Once the raw data is fetched from Apify, we clean it up using the Edit Fields node. In this step, we manually select and rename the fields we want to keep: Title → {{ $json.title }} Address → {{ $json.address }} Website → {{ $json.website }} Phone → {{ $json.phone }} URL → {{ $json.url }}* This node lets us keep only the essentials in a clean format, ready for the next steps. On the right: a clear and usable table, easy to work with. Step 3 – Loop Over Items Now that our data is clean (see step 2), we’ll go through it item by item to handle each contact individually. The Loop Over Items node does exactly that: it takes each row from the table (each contact pulled from Apify) and runs the next steps on them, one by one. 👉 Just set a Batch Size of 20 (or more, depending on your needs). Nothing tricky here, but this step is essential to keep the flow dynamic and scalable. Step 4 – Edit Field (again) After looping through each contact one by one (thanks to Loop Over Items), we're refining the data a bit more. This time, we only want to keep the website. We use the Edit Fields node again, in Manual Mapping mode, with just: Website → {{ $json.website }} The result on the right? A clean list with only the URLs extracted from Google Maps. 🔧 This simple step helps isolate the websites so we can scrape them one by one in the next part of the flow. Step 5 – Scrape Each Website with an HTTP Request Let’s continue the flow: in the previous step, we isolated the websites into a clean list. Now, we’re going to send a request to each URL to fetch the content of the site. ➡️ To do this, we add an HTTP Request node, using the GET method, and set the URL as: {{ $json.website }} This value comes from the previous Edit Fields input This node will simply “visit” each website automatically and return the raw HTML code (as shown on the right). 📄 That’s the material we’ll use in the next step to extract email addresses (and any other useful info). We’re not reading this code manually — we’ll scan through it line by line to detect patterns that matter to us. This is a technical but crucial step: it’s how we turn a URL into real, usable data. Step 6 – Extract the Email with GPT Now that we've retrieved all the raw HTML from the websites using the HTTP Request node, it's time to analyze it. 💡 Goal: detect the most relevant email address on each site (ideally the main contact or owner). 👉 To do that, we’ll use an OpenAI node (Message a Model). Here’s how to configure it: ⚙️ Key Parameters: Model: GPT-4-1-MINI (or any GPT-4+ model available) Operation: Message a Model Resource: Text Simplify Output: ON Prompt (message you provide): Look at this website content and extract only the email I can contact this business. In your output, provide only the email and nothing else. Ideally, this email should be of the business owner, so if you have 2 or more options, try for most authoritative one. If you don't find any email, output 'Null'. Exemplary output of yours: [email protected] {{ $json.data }} Step 7 – Save the Data in Airtable Once we’ve collected everything — the business name, address, phone number, website… and most importantly the email extracted via ChatGPT — we need to store all of this somewhere clean and organized. 👉 The best place in this workflow is Airtable. 📦 Why Airtable? Because it allows you to: Easily view and sort the leads you've scraped Filter, tag, or enrich them later And most importantly… reuse them in future automations ⚙️ What we're doing here We add an Airtable → Create Record node to insert each lead into our database. Inside this node, we manually map each field with the data collected in the previous steps: | Airtable Field | Description | Value from n8n | | -------------- | ------------------------ | ------------------------------------------ | | Title | Business name | {{ $('Edit Fields').item.json.Title }} | | Street | Full address | {{ $('Edit Fields').item.json.Address }} | | Website | Website URL | {{ $('Edit Fields').item.json.Website }} | | Phone Number | Business phone number | {{ $('Edit Fields').item.json.Phone }} | | Email | Email found by ChatGPT | {{ $json.message.content }} | | URL | Google Maps listing link | {{ $('Edit Fields').item.json.URL }} | 🧠 Reminder: we’re keeping only clean, usable data — ready to be exported, analyzed, or used in cold outreach campaigns (email, CRM, enrichment, etc.). ➡️ And the best part? You can rerun this workflow automatically every week or month to keep collecting fresh leads 🔁. Need Help Building an Automated Lead Generation System? This workflow is a solid foundation for scraping Google Maps and extracting contact emails automatically. If you want to go further with AI-powered lead qualification, multi-channel outreach, and automatic follow-ups, our agency builds custom lead generation systems that run 24/7. 👉 Explore our lead generation automation services: Vision IA – Automated Lead Generation Agency We help B2B companies and agencies scale their prospecting without hiring more people—everything from data collection to booking qualified meetings happens on autopilot. Questions about this workflow or other automation solutions? Visit Vision IA or reach out for a free consultation.

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 does This workflow automates the following steps: Form Submission: Collects candidate information via a structured application form. Data Storage: Stores applicant details in Airtable for centralized tracking. CV Management: Automatically uploads resumes to Google Drive for easy access and organization. AI-Powered Candidate Evaluation: Scores candidates based on their resumes and job descriptions using OpenAI, providing actionable insights. Interview Scheduling: Automates scheduling based on candidate and interviewer availability. Communication: Sends customized emails to candidates for interview invitations and feedback. Setup Prerequisites To use this workflow, you’ll need: n8n Account**: To create and run the workflow. Airtable Account**: For managing applicant data. Google Drive Account**: For storing candidate CVs. OpenAI API Key**: For AI-powered candidate scoring. SMTP Email Account**: For sending candidate communications. Setup Process Airtable Configuration: Create a base in Airtable with tables for Applicants and Job Positions. Google Drive Setup: Create a folder for CV storage and ensure you have write permissions. Integrate Airtable in n8n: Use the Airtable API key to connect Airtable to n8n. Integrate Google Drive in n8n: Authorize Google Drive to enable CV storage automation. OpenAI Integration: Add your OpenAI API key to n8n for candidate scoring. Email Configuration: Set up your SMTP email account in n8n for sending notifications and invitations. How to customize this workflow Tailor the workflow to fit your unique recruitment needs: Edit Job Descriptions: Adjust the form parameters to match the specific role and qualifications. Refine AI Evaluation Criteria: Modify OpenAI prompts to reflect the skills and competencies for the desired position. Personalize Email Templates: Update email content to match your organization’s tone and branding. Add New Features: Incorporate additional steps like feedback collection or integration with other HR tools. Conclusion The HR Job Posting and Evaluation with AI workflow simplifies and automates the recruitment process, enabling HR teams to focus on engaging with candidates rather than handling administrative tasks. With its powerful integrations and customization options, this workflow helps organizations hire efficiently while improving the candidate experience.

Who is this for? Anyone curating before/after text examples in a spreadsheet and wanting a push-button path to a fine-tuned GPT model—without touching curl. Works with Google Sheets or Airtable. What problem does it solve? Manually downloading CSVs, converting to JSONL, uploading, and polling OpenAI is a slog. This flow automates the whole loop: grab examples flagged Ready, build the JSONL file, start the fine-tune, then log the resulting model ID back to a registry sheet/table for reuse. How it works | # | Node | Purpose | |---|------|---------| | 1 | Schedule Trigger | Runs weekly by default (change as needed). | | 2a | Get Examples from Sheet | Pulls rows where Ready = TRUE from your Google Sheet. Uses the JSONL-Template Sheet as the expected column layout. | | 2b | Get Examples from Airtable (disabled) | Alternate source for Airtable users. | | 3 | Create JSONL File (Code) | Converts each example to chat-format JSONL and splits into train.jsonl / val.jsonl (80/20). | | 4 | Upload JSONL | Uploads the training file to OpenAI (purpose: fine-tune). | | 5 | Begin Fine-Tune | Starts a fine-tune job on gpt-4o (editable). | | 6 | Wait → Check Job → IF | Polls every minute until status = succeeded. | | 7a | Write Model to Sheet | Appends the new model ID + meta to your Model Registry sheet. | | 7b | Write Model to Airtable (disabled) | Equivalent logging step for Airtable. | Setup steps Import & connect credentials Import the JSON flow into n8n. Add your OpenAI API key. Google Sheets: create an OAuth2 credential and link it to both Sheets nodes. Airtable (optional): create a Personal Access Token and attach it to the Airtable nodes. Copy the template sheet Duplicate the JSONL-Template Sheet linked above into your own Drive. Required columns (exact names): | systemPrompt | userPrompt | assistantResponse | Ready | Tick Ready = TRUE for rows you want to include. Create the registry sheet/table Google Sheet (or Airtable table) named Model Registry with columns: Model ID, Training Examples, Epochs, Batch Size, Learning Rate, Finished At. Tweak model & schedule Change the base model in Begin Fine-Tune if desired. Adjust the Schedule Trigger for daily / on-demand runs. Test it Mark a few examples Ready = TRUE. Run the flow manually. Check OpenAI for the new fine-tune job and confirm the model ID is logged in your registry. Resources n8n Docs – <https://docs.n8n.io/> OpenAI Fine-Tuning – <https://platform.openai.com/docs/guides/fine-tuning> Google Sheets API – <https://developers.google.com/sheets/api> Airtable API – <https://airtable.com/api> Extending the flow Webhook trigger** – swap the schedule for a webhook to train on demand. Multi-source merge* – enable both Sheets *and Airtable nodes to combine datasets. Auto-deploy** – save the new model name to an env-var or Secrets Manager for downstream generation workflows.

Multi-Platform AI Sales Agent with RAG, CRM Logging & Appointment Booking This workflow acts as a 24/7 sales agent, engaging leads across WhatsApp, Instagram, Facebook, Telegram, and your website. It intelligently transcribes audio messages, answers questions using a knowledge base, and uses modular sub-workflows to manage your CRM in Airtable and book appointments in Google Calendar. Who Is It For? This solution is designed for service-based businesses that require a sophisticated, multi-channel lead management and appointment booking system. Agencies, consultants, and clinics** looking to automate lead qualification and booking across text and voice messages. Sales teams** needing a robust system that separates CRM and calendar logic for easier management and scalability. Advanced n8n users** who want a powerful, agent-based framework that can be easily customized and extended. Key Features & Workflow This system is composed of a parent workflow that orchestrates the conversation and calls specialized sub-workflows (agents) to perform specific tasks. Omni-Channel Engagement:* Greets and converses with leads naturally on Website Chat, WhatsApp, Instagram, Facebook, and Telegram*. Voice Message Transcription:* Automatically transcribes incoming audio/voice notes from WhatsApp and Telegram* into text, allowing the AI to understand and respond without manual intervention. RAG-Powered Intelligence:* The AI agent draws answers from your dedicated PostgreSQL Knowledge Base (RAG)*, providing accurate information about your services, pricing, and process. A built-in tool allows you to load new knowledge documents from Google Drive. Modular CRM Agent (Sub-Workflow):* When the conversation requires CRM actions (like creating a contact or updating an opportunity), the main agent calls a dedicated Airtable CRM sub-workflow* to handle the task. Modular Calendar Agent (Sub-Workflow):* To book appointments, the main agent calls a separate Google Calendar sub-workflow*, which manages event creation, updates, and deletions. What You'll Need This workflow framework requires credentials for the following services: An AI provider (OpenAI is used for the main agent, transcription, and embeddings). PostgreSQL** database with the pgvector extension (for RAG and chat memory). Airtable** account (for the CRM sub-workflow). Google Calendar** account (for the Calendar sub-workflow). Telegram Bot** credentials. A Meta Developer Account (for WhatsApp, Instagram & Facebook). (Optional) Google Drive for loading knowledge documents. (Optional) Google Gemini for embeddings. How to Set It Up This is a modular system. You must set up the sub-workflows first. Deploy Sub-Workflows: Create two new, separate workflows using the provided templates for the CRM Agent and the Calendar Agent. Configure the credentials (Airtable, Google Calendar) within those workflows, then save and activate them. Link Sub-Workflows in Main Workflow: Return to this main workflow. In the "CRM Agent" and "Consultation Agent" tool nodes, select the new workflows you just created from the dropdown list. Configure Main Credentials: Securely add the remaining credentials (OpenAI, PostgreSQL, Telegram, and your Meta App) in this main workflow. Personalize the AI Agent: In the "Update Agent Details" node, fill in your business name, the agent's persona name, and your key services to customize the AI's personality. Load Your Knowledge (Optional): To populate the RAG database, use the manual trigger path starting with "When clicking ‘Execute workflow’" to download a document from Google Drive and insert it into your PostgreSQL vector store. Activate: Configure your channel-specific details (e.g., Phone Number ID in WhatsApp nodes), save the workflow, and activate it. Demo CRM Table: View on Airtable

Overview This workflow automates the end-to-end process of creating, optimizing, and publishing content on WordPress. It integrates AI-powered tools, Airtable, and WordPress plugins to generate high-quality, on-brand posts effortlessly. Perfect for content creators, marketers, and business owners looking to save time and scale their content strategy. Features Content Creation: AI-Powered Content:** Generates SEO-friendly blog posts with structured headings, relevant keywords, and meta descriptions. Custom Prompts:** Tailor the AI-generated content to match your brand’s tone and voice. SEO Optimization: RankMath Plugin Integration:** Updates RankMath SEO with focus keywords and meta descriptions, ensuring your content is search-engine optimized. Content Management: Airtable Integration:** Organizes content ideas, drafts, and publishing schedules in one place. Easily scalable for teams or solo creators. Visuals: Branded Featured Images:** Automatically generates on-brand images for every post. Publishing: Effortless Formatting:** Adapts content to fit your WordPress theme and schedules it for publication. Workflow Steps Trigger: Initiated manually or on a schedule. Content Management: Retrieves and organizes ideas from Airtable. Content Generation: Generates AI-driven blog content tailored to your audience. SEO Optimization: Automatically updates RankMath with SEO details. Featured Image Creation: Produces on-brand images for the post. Publishing: Formats and schedules the post on WordPress. Prerequisites API Keys: OpenAI Airtable WordPress REST API RankMath SEO Plugin Custom Code: Add a small update to your WordPress theme’s functions.php file to enable seamless automation. Customization Replace Airtable with another content management system if preferred. Adjust AI prompts to reflect different tones, styles, or industries. Add integrations for additional plugins, analytics, or storage services. Usage Import the workflow into your n8n instance. Configure API credentials for WordPress, Airtable, OpenAI, and RankMath. Update your functions.php file with the provided code snippet. Customize prompts and Airtable structure for your content needs. Trigger the workflow manually or set it on a schedule. Notes Experiment with Airtable views or add filters for more granular control over your content pipeline. Extend the workflow to include social media posting or analytics tracking. For questions, refer to n8n documentation or reach out to the creator. Tools Used Airtable OpenAI GPT WordPress REST API RankMath SEO Plugin Feel free to adapt and extend this workflow to meet your specific needs! 🎉

Overview This n8n workflow automates the creation of 9:16 aspect ratio images optimized for short-form video content and thumbnails. It integrates multiple tools to retrieve content, generate scripts, and create AI-generated imagery. Key Features Trigger Workflow Manually The workflow starts when triggered manually in n8n. Retrieve Brand Guidelines Fetch brand elements like style, tone, and guidelines from Airtable. SEO Keywords and Blog Post Retrieval Retrieves blog posts and associated SEO keywords from Airtable to form the basis of image content. Content Preparation Uses GPT-4 to prepare a 4-scene script and thumbnail prompts for short-form videos. AI Image Generation Uses Leonardo.ai API to generate: Thumbnail Images Scene-specific Images (9:16 Aspect Ratio) Airtable Asset Management Generated assets (images) are saved back into Airtable with metadata like URLs and file sizes. Tools and Integrations n8n**: Workflow automation platform. OpenAI**: Generates scripts and prompts (GPT-4O-MINI). Leonardo.ai**: AI tool for improving prompts and generating high-quality images. Airtable**: Used as a data source for brand guidelines, blog posts, and to store generated assets. Workflow Steps Manual Trigger Initiate the workflow. Retrieve Brand and SEO Guidelines Fetch essential brand elements like tone, style, and keywords. Filter and Fetch Blog Content Search for blog posts relevant to selected SEO keywords. Script Preparation Use GPT-4 to generate a script with image prompts for scenes and thumbnails. Image Generation Call Leonardo.ai to create: Scene Images in 9:16 Aspect Ratio. A Thumbnail Image with an improved prompt. Store Assets Save generated assets (images) to Airtable for future use. Workflow Structure Nodes Breakdown: Manual Trigger**: Start the workflow. Get Brand Guidelines**: Pull brand-related information (style, tagline, tone, etc.) from Airtable. Set Guidelines**: Prepare fetched data. Get SEO Keywords**: Retrieve keywords to filter relevant content. Keyword Filter*: Filter results for specified keywords (e.g., *"AI Automation"). Script Prep**: Generate 4-scene scripts and prompts with GPT-4. Leo - Improve Prompt**: Improve image prompts for clarity and detail. Leo - Generate Image**: Create AI-generated images for scenes and thumbnails. Wait Nodes**: Ensures Leonardo image generation is complete. Add Asset Info**: Store the generated images back into Airtable with metadata. API Credentials Required Ensure the following credentials are configured in n8n: OpenAI API Key Leonardo.ai API Key Airtable API Token Output Generated Images**: High-quality AI-generated images with a 9:16 aspect ratio. Saved Metadata**: Asset details (URLs, sizes, types) stored in Airtable. Usage Import this workflow into n8n. Set up your Airtable API, Leonardo.ai API, and OpenAI API credentials. Run the workflow manually. Monitor image generation and check the Airtable output for results. Tags OpenAI** RunwayML** Leonardo** Airtable** Video Automation** Author AlexK1919 AI-Native Workflow Architect More Workflow Templates YouTube Channel Connect with Alex

LinkedIn DM Automation Overview Effortlessly scale personalized LinkedIn outreach using a no-code automation stack. This template provides a powerful, user-friendly system for harvesting leads from LinkedIn posts and managing outreach—all within Airtable and n8n. Features & Highlights Actionable Input:** Simply enter a LinkedIn post URL to kickstart the engine—no browser scraping or manual work needed. Lead Harvesting:** Automatically scrape commenters, likers, and profile data using Unipile’s API access. Qualification Hub:** Easily review and qualify leads right inside Airtable using custom filters and statuses. Automated Campaign Flow:** n8n handles the sequence—from sending connection requests (adhering to LinkedIn limits) to delivering personalized DMs upon acceptance. Unified Dashboard:** Monitor campaign progress, connection status, and messaging performance in real time. Flexible & Reusable:** Fully customizable for your own messaging, filters, or UD campaigns—clone, adapt, and deploy. Why Use This Template? ++Zero-code friendly:++ Ideal for entrepreneurs, sales professionals, and growth teams looking for streamlined, scalable outreach. ++Transparent and compliant:++ Built with Airtable UI and compliant API integration—no reliance on browser automation or unofficial methods. ++Rapid Deployment:++ Clone and launch your automation in under 30 minutes—no dev setup required. Setup Instructions Import the template into your n8n workspace. Connect your Airtable and Unipile credentials. Configure LinkedIn post input, filters, and DM templates in Airtable. Run the workflow and monitor results directly from Airtable or n8n. Use Cases Capture inbound leads from your viral LinkedIn posts. Qualify and nurture prospects seamlessly without manual follow-ups. Scale outreach with precision and personalization. YouTube Explanation You can access the video explanation of how to use the workflow: Explanation Video

Who is it for? This workflow is perfect for marketers, sales teams, agencies, and local businesses who want to save time by automating lead generation from Google Maps. It’s ideal for real estate agencies, restaurants, service providers, and any local niche that needs a clean database of fresh contacts, including emails, websites, and phone numbers. ✅ Prerequisites Before starting, make sure you have: Apify account** → to scrape Google Maps data OpenAI API key** → for GPT-4 email extraction Airtable account & base** → for structured lead storage Gmail account with OAuth** → to send personalized outreach emails Your Airtable base should have these columns: | Title | Street | Website | Phone Number | Email | URL | |-------------------------|-------------------------|--------------------|-----------------|------------------------|----------------------| | Paris Real Estate Agency| 10 Rue de Rivoli, Paris | https://agency.fr | +33 1 23 45 67 | [email protected] | maps.google.com/... | 🏡 Example Use Case To keep things clear, we’ll use real estate agencies in Paris as an example. But you can replace this with restaurants, plumbers, lawyers, or even hamster trainers (you never know). 🔄 How the workflow works Scrape Google Maps leads with Apify Clean & structure the data (name, phone, website) Visit each website & extract emails with GPT-4 Save all leads into Airtable Automatically send a personalized email via Gmail This works for any industry, keyword, or location. Step 1 – Scraping Google Maps with Apify Start simply: Open your n8n workflow and choose the trigger: “Execute Workflow” (manual trigger). Add an HTTP Request node (POST method). Now, head over to Apify Google Maps Extractor. Fill in the fields according to your needs: Keyword: e.g., "real estate agency" (or restaurant, plumber...) Location: "Paris, France" Number of results: 50 (or more) Optional: filters (with/without a website, by categories…) Click Run to test the scraper. Then click API → select API endpoints tab. Choose “Run Actor synchronously and get dataset items”. Copy the URL, go back to n8n, and paste it into your HTTP Request node (URL field). Then enable: Body Content Type → JSON Specify Body Using JSON Go back to Apify, click the JSON tab, copy everything, and paste it into the JSON field of your HTTP Request. If you now run your workflow, you'll get a nice structured table filled with Google Maps data. Pretty magical already—but we're just getting started! Step 2 – Cleaning Things Up (Edit Fields) Raw data is cool, but messy. Add an Edit Fields node next, using Manual Mapping mode. Here’s what you keep (copy-paste friendly): Title → {{ $json.title }} Address → {{ $json.address }} Website → {{ $json.website }} Phone → {{ $json.phone }} URL → {{ $json.url }} Now, you have a clean, readable table ready to use. Step 3 – Handling Each Contact Individually (Loop Over Items) Next, we process each contact one by one. Add the Loop Over Items node: Set Batch Size to 20 or more, depending on your needs. This node is simple but crucial to avoid traffic jams in the automation. Step 4 – Isolating Websites (Edit Fields again) Add another Edit Fields node (Manual Mapping). This time, keep just: Website → {{ $json.website }} We've isolated the websites for the next step: scraping them one by one. Step 5 – Scraping Each Website (HTTP Request) Now, we send our little robot to visit each website automatically. Add another HTTP Request node: Method: GET URL: {{ $json.website }} (from the previous node) This returns the raw HTML content of each site. Yes, it's ugly, but we won't handle it manually. We'll leave the next step to AI! Step 6 – Extracting Emails with ChatGPT We now use OpenAI (Message a Model) to politely ask GPT to extract only relevant emails. Configure as follows: Model: GPT-4-1-mini or higher Operation: Message a Model Simplify Output: ON Prompt to copy-paste: Look at this website content and extract only the email I can contact this business. In your output, provide only the email and nothing else. Ideally, this email should be of the business owner, so if you have 2 or more options, try for the most authoritative one. If you don't find any email, output 'Null'. Exemplary output of yours: [email protected] {{ $json.data }} ChatGPT will kindly return the perfect email address (or 'Null' if none is found). Step 7 – Neatly Store Everything in Airtable Almost done! Add an Airtable → Create Record node. Fill your Airtable fields like this: | Airtable Field | Content | n8n Variable | | ------------------ | ------------------------------- | ------------------------------------------ | | Title | Business name | {{ $('Edit Fields').item.json.Title }} | | Street | Full address | {{ $('Edit Fields').item.json.Address }} | | Website | Website URL | {{ $('Edit Fields').item.json.Website }} | | Phone Number | Phone number | {{ $('Edit Fields').item.json.Phone }} | | Email | Email retrieved by the AI agent | {{ $json.message.content }} | | URL | Google Maps link | {{ $('Edit Fields').item.json.URL }} | Now, you have a tidy Airtable database filled with fresh leads, ready for action. Step 8 – Automated Email via Gmail (The Final Touch) To finalize the workflow, add a Gmail → Send Email node after your Airtable node. Here’s how to configure this node using the data pulled directly from your Airtable base (from the previous step): Recipient (To): Retrieve the email stored in Airtable ({{ $json.fields.Email }}). Subject: Use the company name stored in Airtable ({{ $json.fields.Title }}) to personalize the subject line. Body: You can include several fields directly from Airtable, such as: Company name: {{ $json.fields.Title }} Website URL: {{ $json.fields.Website }} Phone number: {{ $json.fields["Phone Number"] }} Link to the Google Maps listing: {{ $json.fields.URL }} All of this data is available in Airtable because it was automatically inserted in the previous step (Step 7). This ensures that each email sent is fully personalized and based on clear, reliable, and structured information.

AI Medical Symptom Checker & Health Assistant A responsible, privacy-focused health information assistant that provides general health guidance while maintaining strict safety protocols and medical disclaimers. ⚠️ IMPORTANT DISCLAIMER This tool provides general health information only and is NOT a substitute for professional medical advice, diagnosis, or treatment. Always consult qualified healthcare providers for medical concerns. 🚀 Key Features Safety First Emergency Detection**: Automatically identifies emergency situations Immediate Escalation**: Provides emergency numbers for critical cases Clear Disclaimers**: Every response includes medical disclaimers No Diagnosis**: Never attempts to diagnose conditions Professional Referral**: Always recommends consulting healthcare providers Core Functionality Symptom Information**: General information about common symptoms Wellness Guidance**: Health tips and preventive care Medication Reminders**: General medication information Multi-Language Support**: Serve diverse communities Privacy Protection**: No data storage, anonymous processing Resource Links**: Connects to trusted health resources 🎯 Use Cases General Health Information: Learn about symptoms and conditions Pre-Appointment Preparation: Organize questions for doctors Wellness Education: General health and prevention tips Emergency Detection: Immediate guidance for critical situations Health Resource Navigation: Find appropriate care providers 🛡️ Safety Protocols Emergency Keywords Detection Chest pain, heart attack, stroke Breathing difficulties Severe bleeding, unconsciousness Allergic reactions, poisoning Mental health crises Response Guidelines Never diagnoses conditions Never prescribes medications Always includes disclaimers Encourages professional consultation Provides emergency numbers when needed 🔧 Setup Instructions Configure OpenAI API Add your API key Set temperature to 0.3 for consistency Review Legal Requirements Check local health information regulations Customize disclaimers as needed Implement required data policies Emergency Contacts Update emergency numbers for your region Add local health resources Include mental health hotlines Test Thoroughly Verify emergency detection Check disclaimer display Test various symptom queries 💡 Example Interactions General Symptom Query: User: "I have a headache for 3 days" Bot: Provides general headache information, self-care tips, when to see a doctor Emergency Detection: User: "Chest pain, can't breathe" Bot: EMERGENCY response with immediate action steps and emergency numbers Wellness Query: User: "How can I improve my sleep?" Bot: General sleep hygiene tips and healthy habits information 🏥 Integration Options Healthcare Websites**: Embed as support widget Telemedicine Platforms**: Pre-consultation tool Health Apps**: General information module Insurance Portals**: Member resource Pharmacy Systems**: General drug information 📊 Compliance & Privacy HIPAA Considerations**: No PHI storage GDPR Compliant**: No personal data retention Anonymous Processing**: Session-based only Audit Trails**: Optional logging for compliance Data Encryption**: Secure transmission 🚨 Limitations Cannot diagnose medical conditions Cannot prescribe treatments Cannot replace emergency services Cannot provide specific medical advice Should not delay seeking medical care 🔒 Best Practices Always maintain clear disclaimers Never minimize serious symptoms Encourage professional consultation Keep information general and educational Update emergency contacts regularly Review and update health information Monitor for misuse Maintain audit trails where required 🌍 Customization Options Add local emergency numbers Include regional health resources Translate to local languages Integrate with local health systems Add specific disclaimers Customize for specific populations Start providing responsible health information today!

Who is this for? This workflow is for content creators, social media managers, marketing teams, and virtual assistants who want to automatically repurpose YouTube videos into ready-to-post social media content. If you need to quickly turn long-form videos into short posts for platforms like Instagram, Facebook, or LinkedIn, this workflow saves you hours of manual work. What problem is this workflow solving? Manually extracting ideas from YouTube videos, writing captions, creating images, and preparing social media posts takes a lot of time and effort. This workflow automates the entire process: it reads the video, generates posts with captions and AI images, and organizes everything into Airtable. It lets you focus more on growing your audience instead of spending hours repurposing content. What this workflow does Watches a YouTube channel RSS feed for new videos. Extracts the video transcript automatically using Dumpling AI. Summarizes and transforms the transcript into 3 social media captions (Instagram, Facebook, LinkedIn) using OpenAI. Generates 3 unique AI image prompts. Sends the prompts to Dumpling AI to create realistic social media images. Saves the captions and attaches the AI images into Airtable, ready for posting. Setup RSS Feed Setup Get your YouTube channel’s RSS feed URL. Insert the URL into the RSS Trigger node. This will monitor for new YouTube uploads automatically. Dumpling AI Setup for Transcript Extraction Sign up at Dumpling AI. Get your Dumpling AI API Key. In the first HTTP Request node after the RSS trigger, insert your API Key (use HTTP Header Authentication). This sends the YouTube URL to Dumpling AI’s /extract-transcript endpoint. OpenAI Setup for Caption and Prompt Generation Get your OpenAI API Key. In the OpenAI node, connect your account. The AI will: Generate 3 platform-specific captions. Generate 3 creative prompts to design images related to the video. Edit Fields Node This node organizes the generated captions and prompts into separate fields for easy Airtable mapping. Captions are split for Instagram, Facebook, and LinkedIn. Dumpling AI Setup for AI Image Generation After the Edit Fields node, the second HTTP Request node sends the image prompt to Dumpling AI’s /generate-image endpoint. This returns a realistic AI-generated image. Airtable Setup for Saving Posts (Without Image First) Create a new base in Airtable with the following fields: Platform (Single select: Instagram, Facebook, LinkedIn) Content (Long text field) Image (Attachment field) Connect your Airtable Personal Access Token to the Airtable node. The Airtable node saves the generated captions into separate records, initially without images. Upload Generated Images Back to Airtable The third HTTP Request node PATCHES the Airtable record. It updates the Image field with the generated AI image from Dumpling AI. Credentials Required Dumpling AI API Key (for transcript extraction and AI image generation) OpenAI API Key (for caption and prompt creation) Airtable Personal Access Token (for inserting and updating records) How to customize this workflow to your needs Change the OpenAI prompt to generate captions in your brand tone (e.g., friendly, professional, witty). Modify the image prompts to match your design style better. Adjust the Airtable base fields if you want to add more platforms or content formats. Add scheduling tools like Buffer or Metricool to automatically post from Airtable. ⚡ Quick Tips Make sure Dumpling AI credits are active to allow transcript and image generation. Set Airtable permissions properly so PATCH requests can update attachments.

HUMAN-IN-THE-LOOP Content Automation Pro with Deep Research & Airtable for Power Users \- Collaborative AI for WordPress Blog Automation The BEST n8n Content Automation workflow in the market is getting even better, now enabling you to have full control over the entire process. It’s time to unlock the power of true collaborative creation with GenAI\! Want to leverage AI automation but don't want to give up full control over the whole content creation process? Get the best of both worlds \- get “Human-in-the-Loop” with this supreme n8n workflow template\! This template blends the power of AI with the crucial oversight of human expertise and intervention, all managed through a central, streamlined Airtable interface. Say goodbye to generic content and hello to high-quality, deeply researched articles published directly to your WordPress site with full control. Check out my Youtube channel for a full walkthrough. What problem is this workflow solving? / Use cases Fully automated content generation tools often lack the nuance, accuracy, and strategic control necessary for truly impactful content. This workflow solves that critical gap by integrating powerful AI capabilities into a structured, human-supervised content creation process managed via a simple interface. It automates the most repetitive and time-consuming tasks – like research gathering, chapter ideations, domain copywriting – while strategically embedding essential human review points at critical junctures. Instead of simply providing a topic and receiving a finished article of uncertain quality, you actively guide the process step-by-step within an interface. You review, refine, and approve AI suggestions for chapters and content before finalizing and publishing. This approach makes it perfect for creating high-quality, deeply researched, and brand-aligned blog posts for WordPress more efficiently, without ever sacrificing essential editorial control. Who is this for? This workflow template is meticulously designed for individuals and teams deeply involved in content creation who seek a powerful blend of AI-driven efficiency and essential human-controlled quality assurance: Content Creators & Bloggers:** Who want to leverage AI for drafting and research but maintain full editorial control. Marketing Teams:** Looking to scale content production efficiently while ensuring brand voice and quality consistency. SEO Specialists:** Needing to produce well-researched, structured, and SEO-optimized content regularly. Agencies:** Managing content creation for multiple clients with a structured, repeatable process. Anyone who prefers a "human-in-the-loop" approach** over fully automated "black box" content generators. How this workflow works This template automates significant portions of the WordPress content creation process, utilizing Airtable as the central hub for management and user interaction, while leveraging AI for research and copywriting. The system is composed of four interconnected n8n flows, each handling a distinct stage of the content lifecycle. In addition, there is a sub-workflow dedicated to the research tool (Perplexity). Content Creation Process in Airtable The entire journey from idea to published post is managed within your Airtable base, offering transparency and control. Progress through each tab sequentially to complete the content creation process and produce a high-quality article that fulfills your requirements. Configure Settings (“Settings” Table): Define global parameters (website details, target audience, writing style, category IDs, about us, CTA etc.) in the “Settings” table. These serve as default inputs for the AI. Create Topics (“Create Topics“ Table): Add a record to the “Create Topics” table for each new blog post idea. Mark the topic as ready by setting its 'Status' field to “To Do” and ticking the 'Execute Flow' checkbox to initiate the first flow. Generate Chapters (“Generate Chapters“ Table): The first flow calls to the sub-workflow to do online research and generates potential chapter outlines based on your topic and settings, saving them to the “Generate Chapters” table. Select Chapters to Write (“Select Chapters“ Table): Review the suggested chapters in the “Select Chapters“ Table. Select the chapters you want to proceed with by setting their 'Status' to “To Do” and ticking the 'Execute Flow' checkbox. Generate Content for selected Chapters (“Generate Content“ Table): The second flow calls to the sub-workflow to research each selected chapter and generates draft content, saving it to the “Generate Content” table, where you have the opportunity to review and modify if necessary. Select Chapter Content (“Select Content“ Table): Review and edit the AI-generated text directly in Airtable. Approve the content for each chapter. Once all necessary content is approved, trigger the third flow for the final assembly by setting the status to “To Do” and ticking the 'Execute Flow' checkbox. Finalize Post (“Finalize Post“ Table): The third flow aggregates the approved content, generates the title, SEO metadata, tags, chapter images and featured image, placing all compiled information in the “Finalize Post” table for your final review. When the final article is ready to be published on your website, mark the status as "To Do" and check the "Ready to Publish" box to activate the fourth and final flow. Publish & Backup Post (“Backup Post“ Table): the fourth flow publishes the post to the website and creates a backup record in the “Backup Post” table, archiving key details including the live URL of the published article. n8n Workflow Functions (JSON Files) The automation is handled by four separate n8n flows, each triggered by specific changes in Airtable: Flow 1 (Topic Initiation & Chapter Generation): Trigger: Monitors the “Create Topics” table; activates when a record's 'Status' is "To Do" AND 'Execute Flow' checkbox is ticked. Action: Fetches settings from Settings. Performs initial research (e.g., via Perplexity). Uses AI to generate chapter outlines. Saves suggestions as new records in the “Generate Chapters” table. Flow 2 (Content Generation & Internal Linking): Trigger: Monitors the “Select Chapters” table; activates when a record's 'Status' is "To Do" AND 'Execute Flow' checkbox is ticked. Action: Fetches chapter details and settings. Gathers internal links (e.g., by parsing sitemap). Performs online/ deep research per chapter. Uses AI to write draft content, incorporating research and links. Saves drafts into corresponding records in the “Generate Content” table. Flow 3 (Post Assembly & Image Generation): Trigger: Monitors the “Select Content” table; activates when all content for a topic is approved and final assembly is triggered when a record's 'Status' is "To Do" AND 'Execute Flow' checkbox is ticked. Action: Fetches all content from the “Generate Content” table. Aggregates text. Uses AI for title, SEO metadata, tags, and image prompts. Generates chapter images and a featured cover image (e.g., via AI image model DALL-E). Converts content to HTML. Saves compiled data and image info into the “Finalize Post” table. Flow 4 (WordPress Publishing & Backup): Trigger: Monitors the “Finalize Post” table; activates when a record is marked Status' is "To Do" AND ‘Post to Website’ checkbox is ticked. Action: Fetches finalized data. Uploads images to WordPress. Creates WordPress post (status set to “published” by default) with content, metadata, tags, and image. Creates a record in the “Backup Post” table, with a link to the post on the website. This modular approach ensures each stage is handled distinctly, orchestrated via updates on Airtable interface. Unique Features Human-in-the-Loop Design:** Guarantees quality and relevance through mandatory user review and approval stages within Airtable for chapters, content, and the final post. Collaborative AI Partnership:** Leverages AI as a powerful assistant for research, structuring, and drafting, significantly boosting productivity while relying on human expertise for refinement and final judgment. Airtable as Interface & Control Center:** Utilizes Airtable as an intuitive interface and central database to manage the entire content lifecycle, offering clear progress tracking and facilitating team collaboration. Deep Research Integration:** Incorporates external research tools (like Perplexity) to ensure content is based on fresh, up-to-date information, crucial for accuracy and authority. Modular n8n Structure:** Simplifies complexity by dividing the process into four manageable, interconnected flows plus one sub-flows, making the system easier to understand, troubleshoot, and customize. Rate-limit Aware:** Includes built-in Wait nodes and logic designed to mitigate API rate limit issues from AI and research tools, enhancing workflow reliability during intensive use. Multiple-Image Generation:** Generates and adds images for each chapter, as well as a featured image for the article. Direct WordPress Integration:** Streamlines publication by automatically sending finalized, formatted content, metadata, tags, and the featured image directly to your WordPress site. Internal Linking:** Embeds internal website links strategically within each chapter and throughout the article, boosting SEO and enhancing user navigation. Integrated Backup:** Provides data security by automatically archiving key post details in Airtable and optionally saving text and image files to Google Drive. Future Features “Deeper Research”:** Plans for multi-level research capabilities to enable the creation of even more comprehensive reports or e-book length content. Content Sample:** Provide content samples for the AI to learn from and mimic in terms of writing style and guidelines. Category-Specific Styling:** Aiming to allow users to define styles per category for the AI to learn and imitate, ensuring greater brand consistency. Advanced Link Insertion:** Developing more sophisticated strategies for inserting relevant internal and external links, including automatic source citation and dynamic internal link density adjustments. Requirements Airtable Account: create a Airtable account for free. WordPress Website: Requires an Application Password with permissions to create posts and upload media. Must have the REST API enabled. OpenAI API Key: Or a key from another compatible AI provider for text and image generation (DALL-E is the default for images). Perplexity API Key: Or an API key for your chosen online research tool. Google Drive: for the optional backup feature to Google Drive. Setup Step-by-Step Import n8n Workflows: Download the .json workflow files and import them into your n8n instance. There is one main/ “month” workflow and one sub/ “child” workflow. Name the workflows to your needs. Get Airtable Base: Duplicate the companion Airtable Base template. Configure Credentials: Add new credentials in n8n for Airtable, WordPress (use Application Password), OpenAI API, PerplexityAI API, and Google (for Drive backup). Connect Workflow Nodes: Open each workflow in n8n and assign the correct credential to every node that requires authentication (Airtable, WordPress, AI, HTTP Request, Google nodes). Link the main workflow to the sub-workflow: Access the Research Tool nodes and establish a connection between the main workflow to sub-workflow. Configure Airtable Nodes: Update all Airtable nodes across all workflows. Verify that all 'Table' and 'Field' names in the nodes exactly match your duplicated base. Populate Airtable Settings: Fill in your specific details in the Settings table of your Airtable base (Website URL, Audience, Style, Category IDs, CTA, etc.). Test Connections: Run manual executions on key nodes within each flow to ensure connections and basic configurations are correct before activating. Activate Workflow: Toggle the "Active" switch ON for the main/ “mother” workflow in your n8n list. No need to activate the sub/ “child” workflow. Start Creating: Go to the Create Topics table in Airtable, add a new topic, go through the process and get amazed by AI magic\! Airtable Database Explanation Airtable is the central hub, acting as the database, user interface, and trigger mechanism for this workflow. Structure:** The base uses linked tables to manage the process: Settings: Global configurations. Create Topics: Initiates new content pieces. Generate Chapters: Stores AI-generated chapter outlines for review. Select Chapters: Facilitates user selection of chapters to write. Generate Content: Stores AI-generated draft content for selected chapters. Select Content: Manages user approval of drafted content before final assembly. Finalize Post: Holds the compiled post (text, metadata, image info) for final review and publish trigger. Backup Post: Archives data (including live URL) of successfully published posts. Workflow Interaction:** User updates trigger fields in Airtable (e.g., sets Status='To Do' & Execute Flow=true). n8n Airtable Trigger nodes detect these specific changes. The corresponding n8n flow runs, fetching data from Airtable. AI and other tools process data and generate outputs. Results are written back to the appropriate Airtable tables/fields. User reviews results in Airtable and triggers the next stage via status AND checkbox updates. Setup:* Using the exact* duplicated Airtable base template is mandatory, as n8n workflows expect specific table and field names. Tips for Pros AI Prompts:** Modify prompts in the AI nodes to refine tone, style, format, or incorporate specific instructions. AI Models:** the workflow is optimized for OpenAI's GPT-4o model due to its consistent performance. While you can replace the AI models in the nodes with alternatives (if you have the credentials for them), keep in mind that the workflow may not function. AI Research Model:** PerplexityAI is the tool of choice for research. The "sonar" model is the default for research in this workflow due to its speed and cost-effectiveness. However, you are welcome to explore Perplexity's other models, such as the "sonar-deep-research" model, which is specifically designed for in-depth research. AI Image Model:** The default AI model for image generation is OpenAI’s Dall-E. However, the outputs of this model are not impressive. While OpenAI's 4o multimodal is expected to be available via API soon, better/ superior image quality can be achieved in the meantime by using alternative AI image models (such as FLUX.1). Airtable Base:** Add or modify fields/tables to match your specific tracking needs, but remember to update corresponding n8n nodes accordingly. 3rd-party Integrations:** Replace research tools, image generators, or modify the final step to publish to a different CMS or add post-publication steps like social sharing. Error Handling:** For production reliability, incorporate an “Error Handling” workflow in n8n for this automation to catch failures and send notifications Important Considerations API Rate Limits:* AI and research tools have usage limits. High volume processing might cause errors. The included Wait* nodes help, but may need adjustment based on your API plans. Testing Costs:** API calls to AI models aren't free. To ensure the workflow runs correctly, start testing with OpenAI's GPT-4o. Once you've confirmed functionality, explore using other AI models which may be cheaper to keep costs down. Be aware that the workflow may not be as reliable with models other than GPT-4o. Keep an eye on your API provider's billing dashboard to monitor usage and costs. Sequential Processing:* The workflow processes one topic fully at a time to ensure stability and manage API limits. For fully automated, parallel processing from a list, consider the alternative template: [“\[n8n\] Content Automation Pro – with DEEP RESEARCH – WordPress Blog Automation”*](https://n8n.io/workflows/3041-wordpress-auto-blogging-pro-with-deep-research-content-automation-machine/).

Who is this for? This workflow is designed for job seekers who want to automate their job application research and resume optimization. It's ideal for professionals who want to match their CVs to new job postings daily, improving the chance of landing interviews without manual work. Use case Problem**: Manually searching for jobs, matching resumes, and updating application records is time-consuming and inefficient. Use Case**: Automatically fetches new job listings based on user preferences, scores them against the user's existing CV, generates a revamped CV tailored for each job, and stores everything neatly into an Airtable database for easy tracking. What this workflow does? Fetches user job preferences from Google Sheets daily. Searches for jobs matching those preferences using Apify’s scraping. Filters job posts that are fresh (posted within 24-48 hours). Scores each job against the user’s current CV using an OpenAI agent. Generates a revamped CV tailored to each job. Stores the job listing, compatibility score, match reason, and revamped CV into Airtable for future use. API Credentials Required Google Sheets API Credentials — for reading user-defined job preferences. Apify API Key — to scrape job postings (e.g., Indeed Scraper Actor). OpenAI API Key — for AI scoring and CV enhancement. Airtable API Key — for job listing and tracking. Setup Google Sheets**: Store your job preferences (like titles, locations, etc.). Apify API**: Set up a scraper for LinkedIn, Indeed, or other job boards. OpenAI API**: Provide access to a GPT model (ideally GPT-4 Turbo) to handle CV scoring and revamping. Airtable**: Create two tables: One for archived jobs (old jobs >48 hours). One for current processed jobs with AI scores and revamped CVs. Columns for Airtable: job_title,company,location,date_posted,job_type,description,link,compatibilityScore,matcReason,revampedCV,newCompatibilityScore,newMatchReason. n8n**: Deploy the full workflow with nodes for triggers, loops, API calls, parsing, and storage. How to customize it for your needs Edit Job Preferences**: Add or update the fields in Google Sheets (Columns: job_title, job_location) to search. Fine-tune AI Prompts**: Adjust the scoring criteria (e.g., favor remote roles, leadership experience, certifications). Customize CV Style**: Configure the AI to generate shorter, more detailed, or industry-specific resumes. Change Storage Destination**: Replace Airtable with Notion, Google Sheets, a CRM system, or even send yourself Slack updates. Expand Job Sources**: Easily swap the job scraper to pull listings from your favorite niche job boards. Why Use This Template? Saves 10+ hours/week on manual job search. Instantly tailor CVs to each application. Centralizes all data across Google Sheets and Airtable. Flexible — customize AI prompts, scoring logic, or expand to multiple users! Need Assistance? For setup guidance, customization, or business inquiries, Email: [email protected]

📚 MOTION TUTOR - AI-Powered Language Learning System Unlock the Power of Language with Personalized AI Learning! MOTION TUTOR is a revolutionary AI-powered language learning platform that adapts to your progress and guides you from basic vocabulary to complex sentence structures. Whether you're a beginner or looking to refine your skills, MOTION TUTOR provides an engaging and structured learning experience. 🎯 Key Features: ✅ AI-Powered Lessons: Receive interactive, real-life conversation-based lessons generated by cutting-edge AI. MOTION TUTOR dynamically adapts content to match your learning pace. ✅ Personalized Progress Tracking: Track your growth effortlessly! The system connects with Airtable to monitor your vocabulary, grammar, and situational language skills, ensuring lessons align with your goals. ✅ Memory Retention for Contextual Learning: With built-in memory capabilities, MOTION TUTOR remembers where you left off and keeps the conversation flowing. No need to repeat or restart — pick up right where you left off! ✅ Real-Time Telegram Integration: Learn on the go! Engage with MOTION TUTOR directly through Telegram and receive instant feedback and lesson suggestions based on your performance. ✅ Structured Learning Path: From mastering essential vocabulary to crafting complex sentences, MOTION TUTOR guides you step-by-step with a well-defined roadmap. Basic Vocabulary & Phrases Basic Grammar Structures Situational Vocabulary Intermediate Grammar Concepts Advanced Vocabulary Complex Sentence Structures ✅ Customized Role-Playing & Practice Scenarios: Practice vocabulary and grammar in context by engaging in situational conversations that simulate real-life interactions. 💡 How It Works: Message on Telegram: Send a message to initiate your learning session. AI Processes Input: MOTION TUTOR analyzes your request and customizes the next lesson. Context Retention: Continuation from previous sessions to ensure seamless learning. Track Progress: Updates and tracks progress in Airtable for personalized learning insights. Receive Feedback: AI-generated lessons and tips sent directly through Telegram. 📡 Why Choose MOTION TUTOR? 🎉 Engaging & Interactive Learning: Learn in a fun and practical way with interactive scenarios. 🚀 AI Adaptation for All Levels: Whether you're learning from scratch or advancing your fluency, MOTION TUTOR customizes content to suit your journey. 📝 Progress You Can Measure: Track your achievements and growth with structured Airtable data. 🔁 Never Lose Track: Memory-powered learning ensures you continue smoothly where you last paused. 🎁 Ideal For: Language learners seeking a personalized, guided learning experience. Professionals preparing for international business communication. Travelers aiming to learn practical vocabulary before their next adventure. Students looking to enhance their grammar and conversation skills. 🚀 Get Started Today! Embrace the future of language learning with MOTION TUTOR and gain the confidence to engage in everyday conversations and complex dialogues effortlessly. Ready to Speak with Confidence? 💬 Connect with MOTION TUTOR on Telegram and Start Learning Today!

Real Estate Price-Reduced Property Opportunity Guide Overview This comprehensive automation solution targets FSBO properties listed on Zillow that have recently had their price reduced, providing both investment analysis and tailored outreach scripts. The workflow gathers comprehensive market data to analyze local trends for each specific city and incorporates this intelligence into personalized communication strategies (more aggressive in buyers' markets, more value-focused in sellers' markets). Key benefits: Identify motivated homeowners who have recently reduced their property prices Prepare data-driven offer strategies based on detailed market conditions Develop effective, personalized communication approaches Create a consistent, automated workflow to find and capitalize on opportunities Requirements Airtable account (free tier works) n8n automation platform OpenAI API key Zillow Rapid API access Basic understanding of automation workflows Step 1: Set Up Airtable Database Create a new Airtable base Set up a table with the following fields: Property ID (primary field) Address Price Status (single select field with options: "Contacted" and "Uncontacted") Phone Number Communication Template Market Analysis Offer Price Investment Metrics (Long text field for detailed financial analysis) Expected Cash Flow (Currency field) Expected ROI (Percentage field) Follow-up Date Set the default Status to "Uncontacted" Generate a Personal Access Token from Airtable settings for API connections Step 2: Configure Zillow API Connection Set up an HTTP request node in n8n to connect to Zillow's Rapid API Configure the search parameters: Listing type: "For Sale By Owner" Location: Your target market Price reduction: true Auction properties: false Add filters to: Exclude properties without contact information Only include listings with recent price reductions Filter by minimum square footage or bedrooms if desired Set maximum days since price reduction (e.g., last 14 days) Step 3: Market Analysis Workflow Our market analysis engine processes Zillow market data to provide strategic insights for each location: Comprehensive Market Indicators**: Current inventory levels and new listing rates Median list price and sale price comparison Days-to-pending metrics (current and historical) Sale-to-list price ratios Percentage of properties selling above/below list price Market Trend Analysis**: 6-month and year-over-year comparative trends Market trend scoring system (-10 to +10 scale) Market cycle position identification (Early, Mid, Late) Seasonal market pattern recognition Strategic Investment Guidance**: Market type classification (Buyer's, Balanced, Seller's) Negotiation power assessment Market timing recommendations Risk evaluation (Low to High scale) Actionable investment strategies based on current conditions This analysis is transformed into actionable advice that directs your negotiation approach and helps you calibrate offers appropriately for market conditions. Step 4: Calculate Investment Metrics Our investment calculator analyzes each Zillow property and its RentZestimate to provide comprehensive financial projections: Purchase & Financing Analysis**: Purchase price and standard acquisition costs (20% down payment, 3% closing costs) Loan amount and monthly mortgage payment (30-year term) Total initial investment calculation Monthly Expense Projections**: Property tax (2% of property value annually) Insurance (0.5% of property value annually) Maintenance reserves (1% of property value annually) Vacancy allowance (8% of rental income) Total monthly expense calculation Rental Income & Returns**: RentZestimate integration (with 1% rule fallback when unavailable) Monthly and annual cash flow projections Cash-on-cash ROI calculation Break-even timeline analysis Investment Quality Filtering**: Automatic filtering to show only positive cash flow properties Property identification with complete details (address, beds, baths, sqft) Full investment metrics breakdown for investor decision-making This calculator ensures you focus only on properties with profit potential, saving you countless hours of manual analysis. Step 5: Generate Communication Templates Create templates that combine: Property details (address, price, features) Market intelligence from your analysis Investment metrics showing the property's potential Configures your templates to include: A professional introduction Reference to the specific property address Mention of the price reduction A strategic cash offer (typically 5-15% below asking) Local market statistics to build credibility A clear call to action (request to visit the property) Step 6: Automated Workflow Set up the complete n8n workflow to: Check for new listings with price reductions daily Run market analysis on each new property Calculate potential investment returns Generate personalized communication templates Upload data to Airtable Flag properties ready for contact Update status to "Contacted" after outreach Troubleshooting If outreach isn't being tracked: Check API connections to Airtable If market data seems incorrect: Verify Zillow API parameters and location settings If offers are too low/high: Adjust your calculation parameters Step by Step tutorial: https://youtu.be/IqVw9CIL254?si=MKE5UY4rD0TOMLPg By following this guide, you'll have a functional system that can identify opportunities, analyze market conditions, and help you create personalized offers to potential sellers—all while minimizing the manual effort required so you can focus on closing deals.

UPDATE This is an updated version of the previous Ultimate Content Generator for WordPress v2. https://n8n.io/workflows/2737-ultimate-content-generator-for-wordpress/ It includes an additional workflow to generate content using Anthropic Claude in addition to OpenAI 4o. I also mofidied it to use the AI Agent Tool node with structured output for more consistent outputs. Lastly, the workflow updates a new table in AirTable with the published blog post url and featured image url. Overview- This workflow automates the end-to-end process of creating, optimizing, and publishing content on WordPress. It integrates AI-powered tools, Airtable, and WordPress plugins to generate high-quality, on-brand posts effortlessly. Perfect for content creators, marketers, and business owners looking to save time and scale their content strategy. Features Content Creation: AI-Powered Content: Generates SEO-friendly blog posts with structured headings, relevant keywords, and meta descriptions. Custom Prompts: Tailor the AI-generated content to match your brand’s tone and voice. SEO Optimization: RankMath Plugin Integration: Updates RankMath SEO with focus keywords and meta descriptions, ensuring your content is search-engine optimized. Content Management: Airtable Integration: Organizes content ideas, drafts, and publishing schedules in one place. Easily scalable for teams or solo creators. Visuals: Branded Featured Images: Automatically generates on-brand images for every post. Publishing: Effortless Formatting: Adapts content to fit your WordPress theme and schedules it for publication. Workflow Steps Trigger: Initiated manually or on a schedule. Content Management: Retrieves and organizes ideas from Airtable. Content Generation: Generates AI-driven blog content tailored to your audience. SEO Optimization: Automatically updates RankMath with SEO details. Featured Image Creation: Produces on-brand images for the post. Publishing: Formats and schedules the post on WordPress. Prerequisites API Keys: OpenAI Claude Airtable WordPress REST API Custom Code: Add a small update to your WordPress theme’s functions.php file to enable seamless automation. Customization Replace Airtable with another content management system if preferred. Adjust AI prompts to reflect different tones, styles, or industries. Add integrations for additional plugins, analytics, or storage services. Usage Import the workflow into your n8n instance. Configure API credentials for WordPress, Airtable, OpenAI, Claude and Slack. Update your functions.php file with the provided code snippet. Customize prompts and Airtable structure for your content needs. Trigger the workflow manually or set it on a schedule. Notes Experiment with Airtable views or add filters for more granular control over your content pipeline. Extend the workflow to include social media posting or analytics tracking. Feel free to adapt and extend this workflow to meet your specific needs! 🎉

This workflow automates the process of gathering LinkedIn advice articles, extracting their content, and generating unique contributions for each article using an AI model. The contributions are then posted to a Slack channel and a NocoDB database for record-keeping. The workflow is triggered weekly to ensure new articles are continuously collected and responded to. Who is this for? This workflow is designed for professionals, marketers, and content creators looking to boost their LinkedIn presence by regularly engaging with LinkedIn advice articles. It’s especially useful for those who want to be seen as a "thought leader" or "top voice" in their niche by contributing relevant and unique advice to trending topics. What problem is this workflow solving? Manually searching for relevant LinkedIn articles, reading through them, and crafting thoughtful contributions can be time-consuming. This workflow solves that by automating the process of finding new articles, extracting key content, and generating AI-powered contributions. It helps users stay consistently active on LinkedIn, contributing value to trending discussions. What this workflow does Triggers Weekly: The workflow is set to run every Monday at 8:00 AM. Search Google for LinkedIn Advice Articles: Uses a predefined Google search URL to find the latest LinkedIn advice articles based on the user's area of expertise. Extract LinkedIn Article Links: A code node extracts all LinkedIn advice article links from the search results. Retrieve Article Content: For each article link, the workflow retrieves the HTML content and extracts the article title, topics, and existing contributions. Generate AI-Powered Contributions: The workflow sends the extracted article content to an AI model, which generates unique, helpful advice for each topic within the article. Post to Slack & NocoDB: The AI-generated contributions, along with the article links, are posted to a designated Slack channel and stored in a NocoDB database for future reference. Setup Google Search URL: Update the Google search URL with the relevant LinkedIn advice query for your field (e.g., "site:linkedin.com/advice 'marketing automation'"). Slack Integration: Connect your Slack account and specify the Slack channel where you want the contributions to be posted. NocoDB Integration: Set up your NocoDB project to store the generated contributions along with the article titles and links. How to customize this workflow Change Search Terms**: Modify the Google search URL to focus on a different LinkedIn topic or expertise area. Adjust Trigger Frequency**: The workflow is set to run weekly, but you can adjust the frequency by changing the schedule trigger. Enhance Contribution Quality**: Customize the AI model's prompt to generate contributions that align with your brand voice or content strategy. Workflow Summary This workflow helps users maintain a consistent presence on LinkedIn by automating the discovery of new advice articles and generating unique contributions using AI. It is ideal for professionals who want to engage with LinkedIn content regularly without spending too much time manually searching and drafting responses.

How it works This workflow captures new form submissions, cleans the data, and stores it securely before applying AI-based lead qualification. It analyzes each message to assign category, score, and priority. Based on this classification, leads are routed to the appropriate response path. The system ensures every lead is saved first, then enriched and responded to automatically. Step-by-step Capture and clean lead data** Typeform Trigger – Listens for new submissions in real time. Sanitize Lead Data – Cleans names, formats emails, and extracts domain. Store lead in database** Create a record – Saves lead details in Airtable with status “New”. Analyze and enrich with AI** AI Lead Analyzer – Uses OpenAI to classify, score, and prioritize leads. Merge – Combines original lead data with AI-generated insights. Route and respond automatically** Route by Category – Directs leads based on AI classification. Send a message – Sends tailored email for sales inquiries. Send a message1 – Sends confirmation email for support requests. Send a message2 – Sends response for partnership inquiries. Send a message3 – Sends fallback response for other categories. Send a message4 – Sends Discord alert for high-priority leads. Why use this? Ensures no lead is lost by storing data before processing Automatically prioritizes high-value opportunities using AI Reduces manual lead qualification and response time Provides personalized responses based on intent Enables real-time team alerts for important leads

Facebook Group Auto-Moderation This workflow automatically monitors Facebook Group posts, analyzes them using AI, detects policy violations, logs incidents, notifies moderators and automatically hides high-severity posts to keep the community clean and safe. This workflow listens to new Facebook Group posts in real time, processes each post individually and sends the post content to AI for moderation.If a post violates group rules (spam, scam, hate, adult content or aggressive promotion), the workflow alerts moderators, stores the violation in Airtable and automatically hides the post if the severity is high. You receive: Real-time AI moderation of Facebook Group posts** Automatic hiding of high-risk content** Slack alerts for moderation actions** Airtable logging for audit and tracking** Ideal for Facebook Group admins who want fast, consistent and automated moderation without manual review of every post. Quick Start – Implementation Steps Connect the Facebook Group Webhook to your n8n instance. Add your Facebook Page Access Token as an environment variable. Connect OpenAI credentials for content moderation. Configure Slack for alerts and Airtable for logging. Test using sample Facebook post data. Activate the workflow. What It Does This workflow automates Facebook Group moderation: Receives new group posts via webhook. Splits and processes posts one by one. Normalizes post data (ID, message, user, time). Sends post content to AI for moderation analysis. Determines: Violation or not Category (spam, scam, hate, adult, etc.) Severity (low / medium / high) Logs violations into Airtable. Sends alerts to Slack. Automatically hides posts marked as high severity. Notifies the team whether auto-hide succeeded or failed. Who’s It For This workflow is ideal for: Facebook Group admins & moderators Community management teams Social media operations teams Platforms handling large group volumes Anyone needing automated moderation at scale Requirements to Use This Workflow To run this workflow, you need: n8n instance** (cloud or self-hosted) Facebook Group Webhook subscription** Facebook Page Access Token** OpenAI API key** Slack workspace** with API access Airtable base** + Personal Access Token How It Works Receive Facebook Post – Webhook captures new group posts. Process Posts – Posts are handled one at a time. Normalize Data – Extracts clean post and user details. AI Moderation – AI analyzes the post for rule violations. Violation Check – Determines whether action is needed. Severity Check – Only high-risk posts are auto-hidden. Hide Post – Facebook API hides the post automatically. Log & Notify – Slack alerts + Airtable records are created. Setup Steps Import the workflow JSON into n8n. Configure the Webhook node and subscribe it to your Facebook Group. Add FB\_PAGE\_ACCESS\_TOKEN in n8n environment variables. Connect OpenAI, Slack and Airtable credentials. Verify Airtable field names match the workflow mapping. Test using pinned sample data. Activate the workflow. How To Customize Nodes Customize Moderation Rules Edit the AI Content Moderation node to: Adjust strictness Add or remove categories Change severity logic Customize Slack Alerts You can add: Emojis Mentions (@channel / @here) Direct links to the Facebook post Customize Auto-Hide Logic Change the Severity High? IF node to: Auto-hide medium severity Disable auto-hide completely Add manual approval steps Add-Ons (Optional Enhancements) You can extend this workflow to: Add moderator approval before hiding posts Auto-ban repeat offenders Track user violation history Generate daily moderation summaries Add sentiment analysis Create dashboards using Airtable Interfaces Support multiple Facebook Groups Use Case Examples 1\. Spam Control Automatically hide promotional or scam posts. 2\. Community Safety Detect hate or adult content instantly. 3\. Moderator Efficiency Reduce manual review workload. 4\. Audit & Compliance Maintain a clear violation history in Airtable. 5\. Large Group Management Scale moderation without adding moderators. Troubleshooting Guide | Issue | Possible Cause | Solution | |----------------------|----------------------------|-------------------------------------------------------| | No posts received | Webhook not subscribed | Verify Facebook webhook setup | | AI result missing | OpenAI error | Check API key & rate limits | | Post not hidden | Token permission issue | Verify Page Access Token permissions | | Slack alert not sent | Invalid Slack credentials | Reconnect Slack API | | Airtable error | Field mismatch | Match Airtable column names exactly | Need Help? If you need help extending this workflow with multi-group moderation, advanced AI rules, dashboards or production-scale automation, our n8n automation experts at WeblineIndia can assist with custom workflow design and deployment.

🧩 Description Automatically qualify, score, and route new leads using a hybrid AI + rule-based scoring engine. This workflow analyzes incoming leads from Airtable, enriches them with OpenAI-powered qualification, applies deterministic business rules, and instantly alerts your sales team in Slack when a high-intent lead is detected. 🎯 Who’s it for Sales teams that want instant alerts for high-intent leads Founders who need automated qualification without hiring SDRs Marketing teams running paid campaigns and capturing inbound leads RevOps teams building structured, explainable scoring systems If you store leads in Airtable and want AI-assisted qualification with fallback logic (not just blind AI scoring), this template is for you. 🤖 What it does This workflow implements a hybrid lead scoring model: Triggers when a new lead is created in Airtable. Normalizes and standardizes lead data. Sends structured context to OpenAI for qualification. Validates the AI response (strict JSON parsing). Falls back to deterministic scoring if AI fails. Combines AI score (50% weight) + rule-based score. Updates Airtable with: Final score (0–100) Hot/Warm/Cold tag AI reasoning Confidence level Sends Slack alerts: 🔥 Hot leads (score ≥ 80) ⚠️ AI scoring failures (manual review required) Unlike basic AI-only scoring, this workflow guarantees reliability by combining LLM reasoning with business logic. 🔄 How it works Lead intake & guardrail Airtable Trigger watches for new records. A guard condition prevents re-processing already scored leads (processed = true). AI qualification engine A structured prompt sends lead context to OpenAI. A code node vlidates and safely parses the JSON. If invalid - fallback scoring is activated + Slack alert. Deterministic scoring layer Business logic evaluates: Company size Role authority (Founder, Executive, Manager) Industry relevance Intent message length The deterministic score is capped at 50. How deteministic scoring works? Larger companies receive higher baseline scores: 1-10: 5 11-50: 10 51-200: 20 201-500": 25 501-1000": 30 1000+: 35 You can increase or decrease these values depending on your Ideal Customer Profile (ICP). Industry boost Technology/Software: 10 SaaS/Cloud Services: 15 Cybersecurity: 20 IT Services/Consulting: 10 If your product is industry-specific, this is where you fine-tune relevance. Role authority boost Decision-making power increases lead quality: Founder → +20 Executive → +20 Manager → +10 Head → +10 The workflow detects these keywords inside the role field and applies the corresponding boost. Intent boost (message length) Longer intent messages imply higher purchase interest: 100 characters → +15 50 characters → +8 Hybrid scoring formula Final Score = (AI Score × 0.5) + Deterministic Score Tag thresholds: 80–100 → Hot 50–79 → Warm 0–49 → Cold CRM update The workflow updates Airtable with: score ai_score deterministic_score tag ai_reason score_confidence processed = true Sales alert logic If: Tag = Hot Score ≥ 80 → Slack sends an immediate notification to the sales team. 📋 Requirements You’ll need: Airtable account (Base with Leads table) OpenAI API credentials Slack bot credentials n8n (Cloud or Self-hosted) No API keys are hardcoded. All credentials use secure n8n credential storage. 🛠️ How to set up Import the workflow. Connect credentials: Airtable OpenAI Slack Update: Airtable Base ID Table name Slack channel Ensure your Airtable table includes: lead_id (unique) first_name (text) last_name (text) email phone job_role (single select) industry (single select) company_size (single select) intent_message (long text) - score (number) ai_score (number) deterministic_score (number) tag (text) ai_tag (text) score_confidence (text) created_at (created time) processed (checkbox/boolean) Activate the workflow. 🎛️ How to customize This template uses a hybrid scoring model, combining: 🤖 AI qualification score (50% weight) 📊 Deterministic rule-based scoring (fully customizable) All deterministic scoring logic can be modified inside the Hybrid Lead Scoring Engine Code node. That node contains the full business rule logic for: Company size scoring Industry boosts Role authority boosts Intent-based scoring Final score calculation formula You can easily adjust: AI scoring weight (currently 50%) Hot lead threshold (currently 80) Slack notification logic AI prompt instructions (to match your ICP) You can also: Add email notifications Route Warm leads to nurturing workflows Push Hot leads into a CRM like HubSpot or Salesforce ✨ Why this template is different Uses AI with validation and fallback Prevents double-processing Preserves explainability (AI reasoning stored in CRM) Avoids over-reliance on LLM output Production-ready structure with clear separation of logic blocks This is not just AI scoring — it’s a resilient, sales-ready qualification engine.

Accelerate your real estate marketing by moving from "photo capture" to "published listing" in seconds. This workflow automates the entire listing process by hosting property photos via UploadToURL, using GPT-4o Vision to write professional MLS descriptions, and parallel-publishing the results to WordPress and Airtable. 🎯 What This Workflow Does Turns on-site property photos into fully-enriched digital listings: 📝 Captures Property Media - Receives a photo (binary or URL) and basic address metadata via Webhook. ☁️ Instant CDN Hosting - UploadToURL converts the photo into a permanent, high-speed CDN link for your website. 👁️ Intelligent Property Analysis - GPT-4o Vision analyzes the image to detect room type, condition scores (1–10), professional feature tags, and lighting quality. ✍️ Automated Copywriting - Generates a 2-3 sentence, MLS-compliant description using professional real estate terminology. ⚡ Parallel Publishing - Simultaneously creates a draft post in WordPress (using Gutenberg blocks) and a new record in your Airtable MLS database. 📲 Instant Agent Confirmation - Sends a Telegram message to the agent with live links to the WordPress draft and Airtable record for immediate review. ✨ Key Features UploadToURL Integration**: Native community node hosting ensures your property photos are web-ready instantly without manual resizing or cloud storage management. Vision-Powered Insights**: AI automatically detects "premium finishes" or "renovation age," providing pricing signals without manual entry. Parallel Execution**: Uses a split-branch logic to publish to multiple platforms at once, significantly reducing total execution time. Unified Response**: A Merge node assembles the final IDs and URLs from all platforms into a single, clean JSON response. Audit-Ready MLS**: Every Airtable record is timestamped and includes the original high-res CDN link for external syndication. 💼 Perfect For Real Estate Agencies**: Managing high-volume listings across multiple agents and neighborhoods. Property Managers**: Quickly documenting unit conditions and updates for internal tracking. Independent Realtors**: Automating their personal website and CRM directly from their smartphone while on-site. Property Photographers**: Delivering "ready-to-publish" assets to clients with AI-generated metadata already attached. 🔧 What You'll Need Required Integrations UploadToURL** - To host property photos and provide CDN links. n8n Community Node** - n8n-nodes-uploadtourl must be installed. OpenAI API** - GPT-4o Vision for professional image analysis and copywriting. WordPress** - Basic Auth or Application Password to create draft posts. Airtable** - Personal Access Token to manage your MLS database. Optional Integrations Telegram** - To receive real-time notifications with links to your new listings. 🚀 Quick Start Import Template - Copy the JSON and import it into your n8n canvas. Install Node - Ensure the UploadToURL community node is installed. Set Credentials - Link your UploadToURL, OpenAI, WordPress, Airtable, and Telegram accounts. Define Variables - Update n8n variables: WP_BASE_URL, AIRTABLE_BASE_ID, and TELEGRAM_CHAT_ID. Prepare Airtable - Ensure your table has columns for Listing ID, Address, Price, and MLS Description. Deploy - Activate the workflow and start publishing properties instantly from the field. 🎨 Customization Options Watermarking**: Insert a node to add your agency logo to photos before they are uploaded to the CDN. Zillow/MLS Sync**: Add a branch to push the AI-generated data to external listing services via API. Virtual Staging**: Route photos through an AI staging service before hosting them on UploadToURL. Price Formatting**: Update the code node to support different currencies or regional price display formats. 📈 Expected Results Save 20-30 minutes per listing** by eliminating manual uploading, writing, and platform syncing. Improved SEO**: Every property photo includes AI-generated Alt-Text and descriptive filenames. Better Accuracy**: AI consistently captures features (like "crown molding" or "natural light") that agents might miss in a rush. Zero Friction**: Agents can go from taking a photo to having a draft live on the website before they leave the property. 🏆 Use Cases Rapid Market Entry A team of agents can document an entire apartment complex in one afternoon, with every room automatically categorized and described in WordPress by the time they get back to the office. Internal Quality Audits Property managers use the condition score (1–10) generated by the AI to prioritize maintenance and renovations across a portfolio. Social Media Teasers The AI-generated "Marketing Blurb" can be used to instantly trigger a second workflow that posts a property "sneak peek" to Instagram or LinkedIn. 💡 Pro Tips Structured Filenames**: The workflow automatically renames files to {listingId}_{address}.jpg for better organization and SEO. Draft Status**: Listings are created as "Drafts" in WordPress by default, allowing for a quick "Human-in-the-loop" review before going live. Lighting Analysis**: Use the AI-detected "Lighting Quality" field to identify photos that might need professional retouching. Ready to automate your real estate pipeline? Import this template and connect UploadToURL to start publishing professional listings faster. Questions about the Airtable schema? The workflow includes detailed sticky notes explaining the exact field types required for the MLS record sync.

Video Introduction Want to automate your inbox or need a custom workflow? 📞 Book a Call | 💬 DM me on Linkedin What This Workflow Does This workflow automatically enriches your Airtable company database with AI-powered research. Whenever a new company is added to your Airtable base, an AI agent searches the web to discover the company's website and generates a concise 1-2 sentence summary of their business activities. The workflow then updates the Airtable record with these findings, eliminating manual research and keeping your data complete and current. Key Benefits Automated data enrichment**: No more manual web searches for company information AI-powered accuracy**: Uses OpenAI with web search capabilities to find reliable, up-to-date information Structured output**: Returns data in a predictable JSON format for consistent record updates Real-time processing**: Triggers immediately when new companies are added Setup Requirements Airtable Configuration: Your Companies table must have a Created time field to trigger the workflow Create an Airtable Personal Access Token at airtable.com/create/tokens with these scopes: data.records:read, data.records:write, and schema.bases:read Ensure your table has fields for Website and Company Details (or modify the field mappings accordingly) OpenAI Setup: Register for an OpenAI account and obtain an API key Add your OpenAI credentials in n8n Workflow Configuration: Update the Airtable Trigger node with your base and table URLs Update the Airtable Update node with your specific base and table information Customize the AI prompt if you need different research parameters or output fields Once published, the workflow runs automatically whenever a new company is added to your table.

Automatically scrape LinkedIn posts with Apify, transform them into optimized tweets and threads using Claude AI, store them in Airtable for approval, and publish to X on a daily schedule. Who is this for This workflow is designed for content creators, social media managers, and personal brand builders who want to maximize their content reach by repurposing LinkedIn posts for X (Twitter) without manual rewriting. What it does This workflow automates the entire LinkedIn-to-X content repurposing pipeline: Weekly scraping: Uses Apify to scrape your recent LinkedIn posts based on configurable parameters stored in Airtable Carousel extraction: If a post contains a carousel/PDF, OpenAI extracts the slide content via OCR AI transformation: Claude (via OpenRouter) converts each LinkedIn post into two X-optimized variations: a standalone tweet and a thread (3-7 tweets) Content storage: Saves both the original posts and generated tweets to Airtable with a "Pending" status for review Scheduled publishing: Daily at 12:30, searches for ‘Approved’ tweets whose publication date has passed and posts them to X Thread handling: Properly chains thread tweets as replies to maintain the conversation structure Requirements Apify account (LinkedIn Profile Posts Scraper actor) Airtable account with configured base OpenAI API access (for carousel OCR) OpenRouter API access (for Claude) X/Twitter API access How to set up Create an Airtable base with three tables: Config, LK Posts, and X Tweets (see table configurations below) Configure the Config table with your LinkedIn profile URL, scraping limits, and tweet scheduling delay Configure the ‘TWEET NOW’ button in Airtable with the following URL formula: Connect your credentials: Apify, Airtable, OpenAI, OpenRouter, and X/Twitter Set the weekly and daily schedule triggers according to your timezone Activate the workflow Config Table | Field Name | Type | Description | |------------|------|-------------| | Name | String | Configuration parameter name | | Type | Single Select | Data type indicator: String, Integer | | String Value | String | Value when Type is "String" | | Integer Value | Number | Value when Type is "Integer" | Configuration parameters to create: profile_url — LinkedIn profile URL to scrape posted_limit — Time range for scraping (possible values: "any", "1h", "24h", "week", "3months", "6months", "year") max_posts — Maximum number of posts to scrape schedule_tweets_days_after_lk — Number of days after LinkedIn post date to schedule the tweet LK Posts Table | Field Name | Type | Description | |------------|------|-------------| | LK Post ID | String | LinkedIn post unique identifier | | Status | Single Select | Post processing status: Scrapped, Converted, Tweeted | | Date | DateTime | Original LinkedIn post publication date | | Content | Long Text | LinkedIn post text content | | Post URL | URL | Link to the original LinkedIn post | | Post Img URL | URL | URL of post image (if any) | | Post Doc URL | URL | URL of carousel/PDF document (if any) | | Carousel Content | Long Text | Extracted text content from carousel slides | X Tweets Table | Field Name | Type | Description | |------------|------|-------------| | Unique ID | Formula | Auto-generated unique identifier | | LK Post ID | String | Reference to the source LinkedIn post | | Status | Single Select | Tweet status: Pending, Approved, Rejected, Tweeted | | Variation | Single Select | Tweet format: Standalone, Thread | | Tweet Nb | Number | Tweet position in thread (0 for standalone, 1-7 for thread tweets) | | Content | Long Text | The tweet text content | | Publication Date | DateTime | Scheduled date/time to publish the tweet | | Post Now | Button | Triggers webhook to post immediately | How to customize AI prompt: Edit the "ConvertPostIntoTweets" node to adjust tone and style LLM model: Replace the OpenRouter node with OpenAI or any other LLM node in "ConvertPostIntoTweets" if you prefer a different model Posting delay: Change schedule_tweets_days_after_lk in the Config table Schedule: Modify "Weekly_OnSunday" and "Daily_AtNoon" triggers Scraping: Adjust max_posts and posted_limit in Config table

WooCommerce Failed Order Fetch, Airtable Logging & Slack Alerts This workflow automatically checks WooCommerce for failed orders on a schedule, processes each order individually, prevents duplicate entries using Airtable, stores new failed orders centrally, and sends clear AI-generated Slack alerts. It ensures clean data, avoids duplicate records and helps teams act quickly on failed payments. Quick Implementation Steps Set your WooCommerce domain in the Set WooCommerce Domain node. Add WooCommerce API Key + Secret in the Fetch Failed Orders From WooCommerce node. Connect your Airtable Base/Table in the Search Records and Save Failed Order to Airtable nodes. Add your OpenAI API key to the AI node. Connect your Slack account + target channel. Enable the workflow and let it run automatically. What It Does This workflow continuously monitors your WooCommerce store for failed orders without relying on webhooks. On every scheduled run, it fetches all orders marked as failed, processes them one by one, and checks Airtable using the order\_id to see whether the order has already been logged. If the order already exists, the workflow safely stops processing for that order and optionally sends an informational Slack message. If the order is new, the workflow formats the data, saves it into Airtable, generates a clean AI-written summary, and sends a Slack alert to the team. This approach ensures data accuracy and prevents duplicate records. Who’s It For WooCommerce store owners needing reliable failed-payment tracking Finance teams monitoring recovery opportunities Support teams requiring instant alerts Developers building reusable, idempotent workflows Agencies managing multiple WooCommerce stores Ops teams using Airtable for reporting and audits Requirements to Use This Workflow Active n8n instance (cloud or self-hosted) WooCommerce store with REST API access Airtable account with Base and Table Slack workspace with API access OpenAI API key (for AI-generated messages) Permission to write data to Airtable and Slack How It Works & How To Set Up Step 1: Configure the Scheduler Set how often the workflow runs in Check Failed Orders (Scheduler) (e.g., every 5 minutes, 15 minutes, or hourly). Step 2: Set Your WooCommerce Domain In Set WooCommerce Domain, enter your store domain: Plain textANTLR4BashCC#CSSCoffeeScriptCMakeDartDjangoDockerEJSErlangGitGoGraphQLGroovyHTMLJavaJavaScriptJSONJSXKotlinLaTeXLessLuaMakefileMarkdownMATLABMarkupObjective-CPerlPHPPowerShell.propertiesProtocol BuffersPythonRRubySass (Sass)Sass (Scss)SchemeSQLShellSwiftSVGTSXTypeScriptWebAssemblyYAMLXML yourstore.com This value is reused across the workflow. Step 3: Fetch Failed Orders In Fetch Failed Orders From WooCommerce, configure Basic Authentication using: Consumer Key Consumer Secret The workflow fetches: Plain textANTLR4BashCC#CSSCoffeeScriptCMakeDartDjangoDockerEJSErlangGitGoGraphQLGroovyHTMLJavaJavaScriptJSONJSXKotlinLaTeXLessLuaMakefileMarkdownMATLABMarkupObjective-CPerlPHPPowerShell.propertiesProtocol BuffersPythonRRubySass (Sass)Sass (Scss)SchemeSQLShellSwiftSVGTSXTypeScriptWebAssemblyYAMLXML https://{{wc_domain}}/wp-json/wc/v3/orders?status=failed Step 4: Loop & Duplicate Check Each failed order is processed individually using Loop Over Items. The workflow searches Airtable using Search Records to check whether the order\_id already exists. A Merge node ensures safe data handling, and the IF node decides whether the order is a duplicate or a new entry. Step 5: Format New Order Data The Format Order Data node normalizes WooCommerce data, maps failure reasons, builds admin and retry URLs, and prepares the data for storage. Step 6: Save to Airtable New failed orders are saved in Airtable using Save Failed Order to Airtable. Duplicate orders are skipped to prevent data duplication. Step 7: Generate & Send Slack Alerts For new failed orders, the workflow generates a concise AI-based summary and sends it to Slack. Duplicate orders can optionally trigger an informational Slack message. How To Customize Polling Frequency:** Change scheduler interval Duplicate Logic:** Modify Airtable search or IF condition Stored Fields:** Adjust Airtable field mappings Formatting Rules:* Edit JavaScript in Format Order Data* Slack Message Style:** Update AI prompt Optional Enhancements Retry-payment tracking with attempts count Customer notification via email or SMS Jira/Trello ticket creation Google Sheets or BI dashboard sync Multi-store WooCommerce support Example Use Cases Centralized failed-payment tracking in Airtable Instant Slack alerts for support and finance teams Clean reporting without duplicate records Faster issue resolution with AI summaries Scalable foundation for recovery automation Troubleshooting Guide | Issue | Possible Cause | Solution | | --------------------------- | ----------------------------------- | ------------------------------------------------------ | | No orders fetched | Wrong WooCommerce domain or API URL | Check Set WooCommerce Domain and HTTP Request URL | | 401 Unauthorized | Invalid API key/secret | Regenerate keys from WooCommerce → REST API | | Airtable record not created | Field mismatch | Confirm column names and types in Airtable | | Slack message empty | AI node prompt or path mismatch | Confirm output path: $json.output[0].content[0].text | | Workflow not running | Scheduler disabled | Ensure workflow is Active | | API timeout | Store too slow or blocked | Whitelist server IP or increase timeout in HTTP node | Need Help? If you need assistance customizing this workflow, adding new features or integrating more systems, feel free to reach out. The n8n automation team at WeblineIndia can help with: Advanced WooCommerce automations Multi-store workflows Airtable/Slack/OpenAI integrations Custom logic, validations and data pipelines And many such advanced automation solutions. We’re here to support you in scaling your automation journey.

> ⚠️ Notice: > This workflow uses the CustomJS JSON to TOON node from CustomJS, which requires a self-hosted n8n instance and a CustomJS API key. This workflow demonstrates how to automatically categorize invoices from Airtable using OpenAI, while significantly reducing token usage by converting structured data into TOON (Token-Optimized Object Notation) before sending it to the LLM. Instead of passing large, nested JSON payloads (clients, invoices, invoice items) directly to OpenAI, the workflow converts the data into TOON, lets the AI focus purely on semantic classification, and then converts the result back into clean JSON that can safely be written back to Airtable. The result is a reliable, cost-efficient, and production-ready invoice categorization pipeline. Why This Workflow? Categorizing invoices based on free-text invoice items is a perfect AI use case — but sending raw JSON to LLMs is: expensive slow error-prone (broken JSON, hallucinated fields) This workflow applies the TOON pattern, reducing token usage by 40–60%, while ensuring the AI only returns exactly the data you expect. The LLM never sees raw JSON syntax — only a compact, schema-preserving representation. What This Workflow Does Fetches Invoices, Invoice Items, and Clients from Airtable Aggregates invoice items per invoice Converts the structured data into TOON Uses OpenAI to assign exactly one category per invoice Converts the AI result back into JSON Writes the category back to Airtable All without manual intervention. Key Features AI-based Invoice Categorization** Automatically classify invoices (e.g. web_development, system_administration) TOON Token Optimization** Reduce OpenAI token usage by 40–60% Schema Safety** AI never breaks your JSON structure Deterministic Output** One category per invoice, enforced by prompt design Airtable-Native** Reads from and writes directly back to Airtable How It Works Manual Trigger Run the workflow on demand Load Data from Airtable Fetch ready invoices Resolve related clients Fetch and aggregate invoice items Prepare Structured Context Group client, invoice, and invoice items into a single object JSON → TOON Convert structured data into token-efficient TOON AI Categorization OpenAI receives TOON data Assigns exactly one category per invoice Returns only TOON (no JSON, no prose) TOON → JSON Convert AI output back into valid JSON Persist Result Update the invoice category field in Airtable

How it works The workflow detects incoming job-application emails, extracts resumes, and parses them for AI analysis. It evaluates each candidate against three open roles and assigns a fit score with structured reasoning. Low-scoring applicants are stored for review, while strong candidates move into an automated scheduling flow. The system checks availability on the next business day, books the slot, sends a confirmation email, and records all details in Airtable. Step-by-step Detect and collect job-application data Gmail Trigger1** – Monitors inbox for all new emails. Message a model2** – Classifies whether the email is a job application. If2** – Continues only when the AI result is YES. Get a message1** – Fetches the full message and attachments. Upload file1** – Uploads the resume to Google Drive. Extract from File1** – Converts the PDF resume into text. Analyze the resume and evaluate fit Available Positions1** – Defines the three open roles. Message a model3** – Produces recommended role, fit score, strengths, gaps, skills, and reasoning. If3** – Routes candidates based on fit_score ≥ 8. Create a record3** – Stores lower-scoring applicants in Airtable. Get Next Business Day1** – Calculates the schedule window for qualified candidates. Check availability on the next business day AI Agent1** – Orchestrates availability search using calendar nodes. Get Events1** – Retrieves events for the target day. Check Availability1** – Evaluates free 1-hour slots. OpenAI Chat Model2** – Reasoning engine for the agent. Structured Output Parser1** – Returns clean JSON with start_time and end_time. OpenAI Chat Model3** – Supports structured parsing. Schedule the interview and notify the candidate Create an event1** – Books the interview in Google Calendar. Send a message1** – Sends an HTML confirmation email to the candidate. Create a record2** – Saves shortlisted candidate and interview data in Airtable. Why use this? Removes manual screening by automating email intake and resume parsing. Ensures consistent AI-based role matching and scoring. Books interviews automatically using real calendar availability. Keeps all applicant and scheduling data organized in Airtable. Provides a fully hands-off, end-to-end hiring pipeline.

Overview This workflow automates the "speed-to-lead" process for insurance agencies. It instantly triggers an AI voice call when a new lead comes in, qualifies their needs via conversation, and automatically generates and emails a personalized insurance proposal (Blueprint) using GPT-4. Who’s it for -Insurance Brokers & Agencies who want to automate the initial outreach and qualification of inbound leads. -Applicable to any type of Insurance (Life, Health, Home, Auto or bundling ) -Sales Teams who want to filter out unqualified leads and receive detailed call summaries for qualified prospects. -Any business willing to have a 24/7 virtual assistant that want to qualify potential customers intent and draft proposals. How it works Lead Ingestion: The workflow starts when a potential client submits an n8n web form (Name, Email, Phone Number). CRM Logging: The lead is immediately created in Airtable . AI Voice Call: The workflow triggers Vapi.ai to call the lead immediately. The AI agent acts as a representative to gather requirements. Analysis & Logic: Once the call ends, Vapi sends the call analysis and transcript back to n8n via a webhook. The workflow checks the "Success Evaluation" and ensures a "Type of Insurance" was identified. Path A: Qualified Lead gets a an insurance blueprint: OpenAI (GPT-4) generates a professional "Insurance Blueprint" email based on the call transcript and client needs (type of insurance the client is seeking). Email Dispatch: The proposal is sent directly to the client via Gmail. CRM Update: The Airtable record is updated to "Qualify" with the call summary. Error Handling: If the email fails to send, a Slack alert is sent to the team with the proposal text for manual follow-up. Path B: Unqualified Lead Notification: The team is alerted via Slack with the reason for disqualification. CRM Update: The Airtable record is updated to "Unqualified." with the call summary. Requirements Vapi.ai Account: For the AI voice telephony (requires a configured Assistant and Phone Number). OpenAI Account: For GPT-4 or any LLM model of your choice analysis used for proposals writing. Make sure to have enough tokens. Airtable Account: For lead management. Gmail Account: To send the proposals. Slack Account: For internal team notifications. How to set up Configure External Services Airtable: Create a base with a table with a name of your choice. Ensure it has the following columns: Name (Single text), Email (Email), Phone number (Phone/Text), Status (Single Select: Qualify, Unqualified), Type of Insurance (Text), and Call summary (Long Text). Vapi: Create an Assistant in Vapi. Give the assistant a system prompt according to what you want it to say during the call. Ensure you enable the "Server URL" in the Vapi dashboard to point to the Production URL of the Post call Webhook node in this workflow. Configure Credentials in n8n Add credentials for Airtable, OpenAI, Gmail, and Slack. In the Vapi call node, use your credentials or add your Vapi Private API Key to the header (Authorization: Bearer <YOUR_KEY>). Update Node Parameters Airtable Nodes: Select your specific Base and Table in both the "Create a record" and "Update record" nodes. Vapi Call Node: Input your assistantId, phoneNumberId in the JSON body with the actual IDs from your Vapi dashboard and change the international dialing code. Slack Nodes: Select the channel where you want notifications sent. How to customize the workflow Change the Persona: Open the Prepare Blueprint (OpenAI) node. Edit the System Message to change the agent's name and Insurance or agency name, tone, or the formatting of the email proposal. Adjust Qualification Logic: Open the Is Qualified? (If) node. You can modify the data Collection by adding more fields to the Form Trigger (e.g., "State," "Age") and map them through to the Airtable nodes and the Vapi assistant prompt context. Switch Communication Channels: Replace the Slack and Gmail nodes with other nodes (e.g., Microsoft Teams, Outlook) depending on your tech stack preferences.

This n8n template automatically processes inbound form leads, researches their company via their website, and uses AI to write and send a highly personalized "speed to lead" email instantly. It also tracks subsequent appointment bookings to keep your CRM up to date. Use cases are focused on high velocity sales: Perfect for agency owners, founders, and sales teams who need to respond to new leads in seconds while maintaining a high quality, personal touch. Good to know At the time of writing, this template is optimized for GPT-4o to ensure the highest quality personalization. This template was originally designed using a Lovable form, but it works with any form builder (Typeform, Webflow, WordPress) that can send data via a webhook. How it works The workflow starts when a new lead submits your contact form via the Webhook node. It immediately checks your Airtable CRM to ensure the lead is new and not a duplicate. The system scrapes the provided website URL and uses custom code to clean the HTML data. AI analyzes the cleaned website data to generate a concise summary of the business. A second AI step uses this summary and the lead's goals to draft and send a personalized email via Gmail. The lead data and website summary are logged into your Airtable base. A parallel flow monitors your inbox for booking confirmations and updates the CRM automatically. How to use Create the necessary Base and Table in Airtable to store your leads. Connect your website form to the Webhook URL in the workflow. Update the OpenAI node prompts with your specific email signature and phone number. Run a test submission to ensure the website scraper is capturing data correctly. Requirements Airtable account OpenAI account (GPT-4o model recommended) Gmail account Customising this workflow You can easily adapt this for different communication channels. Try swapping the Gmail node for a Slack notification to alert your team of high value leads, or connect it to HubSpot instead of Airtable for enterprise CRM management.

AI Lead Enrichment & Notification System This n8n template automates the lead enrichment process for your business. Once a lead fills out a form, the workflow scrapes their website, provides a summary of their business, and logs everything into a CRM before notifying your team on Slack. Some use cases: "Speed-to-Lead" optimization, lead enrichment, automated prospect research. How it works Ingestion: A lead submits their details (Name, Email, Website) via a form. Intelligent scraping: The workflow scrapes the provided URL. AI Analysis: OpenAI's model (GPT-4o) analyzes the extracted data and determines whether there is enough info or if the workflow needs to scrape the "About Us" page. CRM Sync: The CRM (Airtable) is updated with the enriched data. Notification: An instant Slack notification is sent to the team channel. How to use the workflow Configure the form: Open the trigger form and input the required fields. Setup OpenAI: Ensure that your credentials are connected. Database mapping: Ensure your Airtable base has the following columns: Name, Website, AI Insight, Email, and Date. Slack setup: Specify the desired Slack channel for notifications. Test it out! Open the form, enter sample data (with a real website), and watch the system enrich the lead for you. Requirements OpenAI API Key** (For analyzing website content and generating summaries) Airtable** (For CRM and logging) Slack** (For team notifications)

AI Sales Analyst & Lead Router This n8n template handles the post-call process for your business. It uses the call recording to extract valuable data and handles the prospect based on their budget. Some use cases: Sales follow-ups, auto-qualifying leads based on budget, monetizing low-budget leads, and automatic data entry. How it works Ingestion: When a call recording is uploaded to a specific Google Drive folder, the workflow is triggered. Transcription: OpenAI's model transcribes the call recording. Analysis: The GPT-4o model analyzes the transcript and extracts crucial information. Lead classification: The extracted budget is checked against your defined threshold (e.g., $5,000). Hot leads (Budget > 5k): The workflow logs the data in Airtable (CRM), creates a high-priority task, and instantly alerts the team via a Slack channel. Warm leads (Budget < 5k): The workflow logs the data, creates a low-priority task, and emails the lead, offering a cheaper alternative. Logging: Every execution is logged in Airtable. How to use the workflow Configure Google Drive: Open the Trigger node and select the destination folder for the call recordings. Set your Threshold: Open the If node and set your desired budget (currently set to 5,000). Customize the email: Open the Gmail node in Phase 2B and modify the email according to your own preferences. Database mapping: Ensure that your Airtable base has the following columns: Client Name, Budget, Sentiment, Summary, Date, and Timeline. Test it out! Generate a sample audio file on ElevenLabs and upload it to your Google Drive folder. Requirements Google Drive** (For storing audio recordings) OpenAI API Key** (Access to OpenAI models) Airtable** (For CRM and System Logging) Trello** (For Task Management) Slack** (For Team Notifications) Gmail** (For sending automated emails)

This workflow automates the entire process of running a Print-on-Demand (POD) business by combining market trend analysis with autonomous AI design and quality control. It acts as a virtual product team that researches, designs, vets, and publishes new products to your store every week. Who is it for? This template is ideal for e-commerce entrepreneurs, content creators, and print-on-demand store owners who want to scale their merchandise inventory without spending hours on design and market research. What it does Market Research: Fetches real-time search data from Google Trends and customer preference data from Typeform. AI Design: Uses OpenAI (GPT-4o) to brainstorm t-shirt concepts based on the gathered trends, then generates high-quality vector-style images using Replicate (Flux/Stable Diffusion). Quality Control: A "Vision AI" agent analyzes the generated image, rates it on a scale of 1-10, and filters out any design scoring below 7. Dynamic Pricing & Publishing: Automatically calculates a premium price for higher-rated designs and publishes the product directly to your Printify store. Logging: Saves the product details to Airtable for your records. How to set up Configure Credentials: Open the "Workflow Configuration" node. Replace the placeholder values with your API keys for OpenAI, Replicate, Printify, and Typeform. Set Printify Details: In the "Workflow Configuration" node, add your Shop ID. In the "Publish to Printify" node, update the blueprint_id (the specific t-shirt model, e.g., Bella+Canvas 3001) and print_provider_id. Airtable Setup: Create a table with columns for Title, Description, Price, Quality Score, and Image URL, then map the IDs in the Airtable node. Requirements n8n: Cloud or Self-hosted instance. API Keys: OpenAI (with GPT-4o access), Replicate, Printify, Typeform, and Airtable. Printify Account: A connected store (e.g., Shopify, Etsy, or Pop-up). How to customize Prompt Engineering: Modify the "Chief Designer AI" system prompt to change the artistic style (e.g., from "vector" to "pixel art" or "vintage"). Pricing Logic: Adjust the JavaScript in the "Dynamic Pricing Calculator" to change your base margins or markup rules. Schedule: Change the "Weekly Schedule Trigger" to run daily or monthly depending on your volume needs.

How it works This template creates a fully automated "hands-off" pipeline for processing financial documents. It's perfect for small businesses, freelancers, or operations teams who want to stop manually entering invoice and receipt data. When you drop a new image/multiple images file into a specific Google Drive folder, this workflow automatically: Triggers and downloads the new file. Performs OCR on the file using a local AI model (Nanonets-OCR-s) to extract all the raw text. Cleans & Structures the raw text using a second local AI model (command-r7b). This step turns messy text into a clean, predictable JSON object. Saves the structured data (like InvoiceNumber, TotalAmount, IssueDate, etc.) to a new record in your Airtable base. Moves the original file to a "Done" or "Failed" folder to keep your inbox clean and organized. Requirements Google Drive Account:** For triggering the workflow and storing files. Airtable Account:** To store the final, structured data. Ollama (Local AI):** This template is designed to run locally for free. You must have Ollama running and pull two models from your terminal: ollama pull benhaotang/Nanonets-OCR-s:F16 ollama pull command-r7b:7b-12-2024-q8_0 How to set up Setup should take about 10-15 minutes. The workflow contains 7 sticky notes that will guide you step-by-step. Airtable: Use the link in the main sticky note ([1]) to duplicate the Airtable base to your own account. Ollama: Make sure you have pulled the two required models listed above. Credentials: You will need to add three credentials in n8n: Your Google Drive (OAuth2) credentials. Your Airtable (Personal Access Token) credentials. Your Ollama credentials. (To do this, create an "OpenAI API" credential, set the Base URL to your local server (e.g., http://localhost:11434/v1), and use ollama as the API Key). Follow the Notes: Click through the workflow and follow the numbered sticky notes ([1] to [6]) to connect your credentials and select your folders for each node. How to customize the workflow Use Cloud AI:** This template is flexible! You can easily swap the local Ollama models for a cloud provider (like OpenAI's GPT-4o or Anthropic's Claude 3). Just change the credentials and model name in the two AI nodes (OpenAI Chat Model and Data Cleaner). Add More Fields:** To extract more data (e.g., SupplierVATNumber), simply add the new field to the prompt in the Data Cleaner node and map it in the AirTable - Create a record1 node.

Analyze email performance and optimize campaigns with AI using SendGrid and Airtable This n8n template creates an automated feedback loop that pulls email metrics from SendGrid weekly, tracks performance in Airtable, analyzes trends across the last 4 weeks, and generates specific recommendations for your next campaign. The system learns what works and provides data-driven insights directly to your email creation process. Who's it for Email marketers and growth teams who want to continuously improve campaign performance without manual analysis. Perfect for businesses running regular email campaigns who need actionable insights based on real data rather than guesswork. Good to know After 4-6 weeks, expect 15-30% improvement in primary metrics Requires at least 2 weeks of historical data to generate meaningful analysis System improves over time as it learns from your audience Implementation time: ~1 hour total How it works Schedule trigger runs weekly (typically Monday mornings) Pulls previous week's email statistics from SendGrid (delivered, opens, clicks, rates) Updates the previous week's record in Airtable with actual performance data GPT-4 analyzes trends across the last 4 weeks, identifying patterns and opportunities Creates a new Airtable record for the upcoming week with specific recommendations: what to test, how to change it, expected outcome, and confidence level Your email creation workflow pulls these recommendations when generating new campaigns After sending, the actual email content is saved back to Airtable to close the loop How to set up Create Airtable base: Make a table called "Email Campaign Performance" with fields for week_ending, delivered, unique_opens, unique_clicks, open_rate, ctr, decision, test_variable, test_hypothesis, confidence_level, test_directive, implementation_instruction, subject_line_used, email_body, icp, use_case, baseline_performance, success_metric, target_improvement Configure SendGrid: Add API key to the "SendGrid Data Pull" node and test connection Set up Airtable credentials: Add Personal Access Token and select your base/table in all Airtable nodes Add OpenAI credentials: Configure GPT-4 API key in the "Previous Week Analysis" node Test with sample data: Manually add 2-3 weeks of data to Airtable or run if you have historical data Schedule weekly runs: Set workflow to trigger every Monday at 9 AM (or after your weekly campaign sends) Integrate with email creation: Add an Airtable search node to your email workflow to retrieve current recommendations, and an update node to save what was sent Requirements SendGrid account with API access (or similar ESP with statistics API) Airtable account with Personal Access Token OpenAI API access (GPT-4) Customizing this workflow Use different email platform**: Replace SendGrid node with Mailchimp, Brevo, or any ESP that provides statistics API—adjust field mappings accordingly Add more metrics**: Extend Airtable fields to track bounce rate, unsubscribe rate, spam complaints, or revenue attribution Change analysis frequency**: Adjust schedule trigger for bi-weekly or monthly analysis instead of weekly Swap AI models**: Replace GPT-4 with Claude or Gemini in the analysis node Multi-campaign tracking**: Duplicate the workflow for different campaign types (newsletters, promotions, onboarding) with separate Airtable tables

🚀 Enrich CRM Leads with LinkedIn Company Data Using AI Who's it for Sales teams, marketers, and business development professionals who need to automatically enrich their CRM records with detailed company information from LinkedIn profiles. Perfect for anyone doing B2B outreach who wants to personalize their messaging at scale. What it does This workflow transforms bare-bones lead records into rich, personalized prospect profiles by: Automatically scraping LinkedIn company profiles Using AI (GPT-4) to extract key business intelligence Generating 15+ email-ready personalization variables Updating your CRM with structured, actionable data The workflow pulls company overviews, products/services, funding information, recent posts, and converts everything into natural-language variables that can be dropped directly into your outreach templates. How it works Trigger: Workflow starts when a new lead is added to Airtable (or on schedule) Fetch: Retrieves the lead record containing the LinkedIn company URL Scrape: Pulls the raw HTML from the company's LinkedIn profile Clean: Strips HTML tags and formats content for AI processing Analyze: GPT-4 extracts structured company intelligence (overview, products, market presence, recent posts) Transform: Converts analysis into 15+ email-ready variables with natural phrasing Update: Writes enriched data back to your CRM Setup Requirements Airtable account** (free tier works fine) OpenAI API key** (GPT-4o-mini recommended for cost-effectiveness) LinkedIn company URLs** stored in your CRM 5 minutes** for initial configuration How to set up Configure Airtable Connection Replace YOUR_AIRTABLE_BASE_ID with your base ID Replace YOUR_TABLE_ID with your leads table ID Ensure your table has a "LinkedIn Organization URL" field Add your Airtable API credentials Add OpenAI Credentials Click on both OpenAI nodes Add your OpenAI API key GPT-4o-mini is recommended (cost-effective and fast) Set Up Trigger Add a trigger node (Schedule, Webhook, or Airtable trigger) Configure to run when new leads are added or on a daily schedule Test the Workflow Add a test lead with a LinkedIn company URL Execute

Who’s it for This template is perfect for TikTok creators, content marketers, and social media teams who want to turn viral comments into engaging short-form videos without manually scripting, recording, or editing. If you want to keep up with trends and consistently publish high-quality avatar videos, this workflow automates the entire process from comment selection to enhanced final video. What it does The workflow takes TikTok video URLs and their top comments from a Data Table, extracts the transcript using Dumpling AI, and uses GPT-4 to write a natural and engaging TikTok script inspired by the comment. It then generates a full AI avatar video through Captions.ai, enhances it with subtitles and B-roll using Submagic, and finally saves all video details into Airtable for tracking. Here’s what happens step by step: Pulls TikTok videos and their top comments from a Data Table Sends video URLs to Dumpling AI to retrieve transcripts Feeds both transcript and comment into GPT-4 to generate a conversational TikTok script Cleans and formats the script using JavaScript Sends the script to Captions.ai to produce an AI avatar video Checks video status and retries if needed Enhances the final video with Submagic for captions and effects Receives the enhanced video via webhook and logs details into Airtable How it works Schedule Trigger: Runs automatically at set intervals to start the workflow Data Table: Retrieves TikTok video URLs and associated comments Dumpling AI: Extracts transcripts from the video URLs GPT-4: Generates a compelling TikTok script based on the comment JavaScript Node: Cleans up script formatting for a smooth avatar generation Captions.ai: Creates an AI avatar video from the cleaned script Wait & Check: Monitors video creation status and retries if necessary Submagic: Enhances the video with captions, zooms, and B-roll effects Webhook & Airtable: Receives final video data and saves URL and ID for future use Requirements ✅ Dumpling AI API key stored as HTTP header credentials ✅ OpenAI GPT-4 credentials ✅ Captions.ai API credentials ✅ Submagic API credentials ✅ Airtable base with fields for Video URL and Caption Video ID ✅ A properly structured Data Table containing TikTok Keywords or video URLs How to customize Adjust the GPT-4 system prompt to shape the tone, style, or format of the TikTok script Change the avatar or creator settings in Captions.ai to match your brand personality Modify Submagic settings to control subtitle styling or B-roll effects Integrate approval steps before final video generation if needed Extend the workflow to auto-publish videos to TikTok or store them in cloud drives > This workflow lets you transform TikTok comments into engaging AI avatar videos with captions and edits, completely on autopilot. It’s a powerful way to scale content output and stay ahead of trends without manual scripting or filming.

Advanced AI Lead Enrichment & Cold Email Personalization with n8n, Airtable, Apify, and LLMs Automated B2B Lead Nurturing: Hyper-Personalization for High-Converting Cold Email Campaigns This powerful n8n automation workflow is designed to execute advanced B2B lead enrichment and hyper-personalization for cold email outreach. By orchestrating a complex chain of data scraping, AI analysis (via LLMs/GPT-4.1), and CRM synchronization (using Airtable), this workflow ensures every lead receives a highly tailored and relevant outreach message, maximizing conversion rates and minimizing manual effort. Workflow Execution & Key Features Airtable Trigger & Lead Qualification: The workflow is triggered by an Airtable webhook, pulling a new lead record (including name, email, and company URLs). Email Validation* is performed using NeverBounce* to filter out invalid contacts. Initial Lead Filtering screens for key demographic criteria (e.g., US: Yes or No? and target Headcount: >5, <30?). Only qualified B2B leads proceed, ensuring optimal resource allocation. Deep Web & Social Scraping (Apify Integration): LinkedIn Company Scraper* and a LinkedIn Profile Scraper (via Apify*) extract raw data from the lead's company and personal profiles. Company Homepage Scraper** pulls the main website content for analysis. Scrape Personal LinkedIn Posts** node retrieves recent activity for the ultimate personalization hook. AI-Powered Data Synthesis & Variable Determination: Multiple OpenAI (GPT-4.1-mini/4.1) nodes analyze and structure the raw, cleaned text (Remove HTML nodes ensure clean inputs). Determine Valuable URLs** uses an LLM to smartly categorize and select key company pages (e.g., ==/about==, ==/solutions==, ==/case-studies==) for deeper scraping. Analyze Company/Mission, Analyze Offerings & Positioning, Analyze Process & Differentiation, and **Analyze Proof of Success nodes create factual, structured business summaries for the ultimate ICP research. Determine Variables* nodes create pre-written, personalized cold email variables* (==company_specialty==, ==ICPofLead==, ==PainPointLeadSolves==, etc.) for different outreach strategies. LinkedIn Post Personalization: An LLM (Craft Opening Line - Posts) analyzes recent LinkedIn activity to generate a hyper-specific, conversation-starting opener (e.g., "Saw your LinkedIn post about..."). Conditional logic (Posts Available?) determines whether to use the post-based opener or fall back to the standard, company-based personalization. CRM Update & Campaign Launch (Instantly.ai): Finalized, enriched lead data and the crafted personalization variables are synchronized back to the Airtable CRM for record-keeping and lead status updates (Update Lead W/ Enrichment). The lead is then seamlessly pushed to the Instantly.ai outbound platform, injecting the AI-generated custom variables directly into the cold email sequence for mass deployment. This blueprint automates the tedious, high-effort task of prospect research and personalization, providing a scalable lead generation solution that increases both outreach quality and sales velocity. Stop sending generic emails—start leveraging AI automation today.