Airtable and HTTP Request integration

📘 Workflow Documentation – Stock Market Daily Digest 👋 Introduction Wake up to a clean, analyst-style stock digest in your inbox—top gainers/losers, a readable performance table, 3–5 insights, and upcoming events—no spreadsheets, no manual scraping, no copy-paste. This article explains, step by step, how to build a robust, daily, end-to-end automation that collects market data (Bright Data), waits until scraping is done, aggregates results, asks an AI model (OpenAI) to draft a styled HTML email, logs everything to Airtable, and finally sends the report via Gmail. You’ll find a friendly but technical tour of every single node, so you can rebuild or adapt the same pipeline with confidence. 🎯 Who is this workflow for? Investors & traders** who want a quick, readable daily summary. Finance/Product teams** building data-driven alerts/digests. Consultants & agencies** sending recurring client updates. Automation builders** prototyping finance ops quickly. 🧰 Tools you’ll need Bright Data** — dataset triggers & snapshots for reliable web data. OpenAI (GPT)** — to generate a professional HTML digest. Airtable** — store daily rows for history, filters, dashboards. Example Airtable Table: Daily Stocks | Ticker | Company | Price | Change % | Sentiment | Date | |--------|--------------------------|---------|----------|-----------|---------------------| | AAPL | Apple Inc. | 225.80 | +1.4% | 🟢 Positive | 2025-09-18 09:00 | | MSFT | Microsoft Corporation | 415.20 | -0.7% | 🔴 Negative | 2025-09-18 09:00 | | NVDA | NVIDIA Corporation | 124.55 | +2.1% | 🟢 Positive | 2025-09-18 09:00 | | TSLA | Tesla Inc. | 260.00 | -3.0% | 🔴 Negative | 2025-09-18 09:00 | | META | Meta Platforms Inc. | 310.45 | +0.5% | 🟡 Neutral | 2025-09-18 09:00 | Gmail** — deliver the final HTML email to stakeholders. n8n** — the automation engine that orchestrates every step. > Keep API keys in n8n Credentials (never hard-code secrets). 🗺️ Architecture at a glance Schedule fires daily Seed list of tickers Split into one item per stock Prepare keyword for scraping Launch Bright Data job Poll progress with a wait-loop Fetch snapshot data Aggregate for the AI Generate HTML summary (GPT) Save rows to Airtable Send email via Gmail ⚙️ Step-by-step — Every node explained ⏰ Daily Run Trigger (Schedule Trigger) Purpose Start the automation at a precise time each day so nobody needs to push a button. Parameters (English) Trigger Type**: Time Interval or Cron Every X**: 1 Day (or your preferred cadence) Timezone**: UTC (or your own) Start Time**: optional (e.g., 09:00) 📝 Set Stock List (Set Node – SAMPLE DATA) Purpose Define the universe of stocks to monitor. This acts as the seed data for scraping. Parameters Values to Set**: Fixed JSON (array of objects) Keep Only Set**: true Fields per item**: ticker, name, market_cap (you may add sector, isin, etc.) 🔀 Split Stocks (Split Out) Purpose Turn the array into individual items so each ticker is processed independently (scraping, polling, results). Parameters Operation**: Split Out Items Field to Split**: the array defined in the previous Set node 🏷 Prepare Stock Keyword (Set Node) Purpose Create a keyword field (typically equal to ticker) for Bright Data discovery. Parameters Values to Set**: Add Field Field Name**: keyword Value**: use an expression referencing the current item’s ticker (e.g., {{ $json.ticker }} ) 🕸 Bright Data Scraper (HTTP Request) Purpose Trigger the Bright Data dataset to start collecting information for the keyword. Returns a snapshot_id to poll later. Parameters Method**: POST Endpoint**: https://api.brightdata.com/datasets/v1/trigger Authentication**: Authorization: Bearer <token> (header) Body Fields**: dataset_id: your Bright Data dataset ID discover_by: usually keyword keyword: the value prepared above > Add a retry/backoff policy on 429/5xx in node options. 🔄 Check Scraper Progress (HTTP Request) Purpose Poll Bright Data to see whether the snapshot is running or ready. Parameters Method**: GET Endpoint**: https://api.brightdata.com/datasets/v1/snapshots/{snapshot_id} Authentication**: Authorization: Bearer <token> Expected Output**: a status field (running, ready) ⏳ Wait for Data (Wait Node) Purpose Pause between progress checks to avoid rate limits and give Bright Data time to finish. Parameters Mode**: Wait a fixed amount of time Time**: e.g., 30 seconds (tune to your dataset size) 🔀 Scraper Status Switch (Switch Node) Purpose Route logic based on the polled status. Parameters Value to Check**: status Rules**: Equals running → go to Wait for Data (then re-check) Equals ready → proceed to Fetch Scraper Results > Loop pattern: Check → Wait → Check, until ready. 📥 Fetch Scraper Results (HTTP Request) Purpose Download the completed snapshot data once Bright Data marks it ready. Parameters Method**: GET Endpoint**: https://api.brightdata.com/datasets/v1/snapshots/{snapshot_id}/data Authentication**: Authorization: Bearer <token> Query**: format=json Output**: array of rows per ticker (price, change %, any fields your dataset yields) > Normalize fields with a Set/Code node if needed. 📊 Aggregate Stock Data (Aggregate Node) Purpose Combine all individual items into one consolidated object so the AI can analyze the entire market snapshot. Parameters Mode**: Aggregate (merge to a single item) Fields to Include**: ticker, name, price, change, sentiment (plus any extra fields captured) Output**: one JSON item containing an array/map of the day’s stocks 🤖 Generate Daily Summary (AI Node – OpenAI) Purpose Ask the model to convert raw data into a styled HTML email: headline, top movers, table, insights, and (optional) upcoming events. Parameters Model**: gpt-4.1 Input**: the aggregated JSON from the previous node Prompt guidelines**: Output HTML only with inline styles (email-safe) Include a table (Ticker, Company, % Change with ↑/↓ & color, Market Cap, Sentiment icon) Highlight top 2 gainers & 2 losers with short reasoning if present Provide 3–5 insights (sector rotation, volatility, outliers) Add upcoming events when available (earnings, launches, macro) Footer: “Generated automatically by your AI-powered stock monitor” Output field**: confirm the exact property that contains the HTML (e.g., output, message, text) 🗂 Save to Airtable (Airtable – Create Record) Purpose Log each item (or the roll-up) to Airtable for history, filtering, and dashboards. Parameters Operation**: Create Record Base ID**: from your Airtable URL Table**: e.g., Daily Stocks Field Mapping**: Ticker ← {{ $json.ticker }} Company ← {{ $json.name }} Price ← {{ $json.price }} Change % ← {{ $json.change }} Sentiment ← {{ $json.sentiment }} Date ← {{ $now.toISO() }} > Use a Single-Select for Sentiment (🟢 / 🟡 / 🔴) to build clean Airtable views. 📧 Send Report via Gmail (Gmail Node) Purpose Deliver the AI-generated HTML digest to your recipients. Parameters Operation**: Send Email Send To**: one or more recipients (e.g., [email protected]) Subject**: Daily Stock Market Digest – {{ $now.format("yyyy-MM-dd") }} Message (HTML)**: reference the AI node’s HTML property (e.g., {{ $('Generate Daily Summary').first().json.output }} ) Options: set **Append Attribution to false (keep the email clean) > Test in Gmail, Outlook, and mobile to validate inline CSS. 🧪 Error handling & reliability tips Backoff on Bright Data* — If scraping many tickers, increase Wait* or batch requests. Guard against empty results** — If a snapshot returns 0 rows, branch to a fallback email (“No data today”). AI guardrails** — Enforce “HTML-only” and skip missing sections gracefully. Airtable normalization** — Strip %, cast numbers to float before insert. Observability* — Add a final Slack/Email On Fail* node with run ID and error message. 🧩 Customization ideas Sector deep-dives**: add sector fields and a second AI paragraph on sector rotation. CSV attachment**: generate & attach a CSV for power users. Multiple lists**: run parallel branches for Tech, Healthcare, or regions. Other asset classes**: Crypto, ETFs, Indices, FX. Audience targeting**: different “To” lists and slightly different prompts per audience. ✅ Why this workflow is powerful Hands-off** — the report simply shows up every day. Analyst-grade** — clean HTML, top movers, tidy table, actionable insights. Auditable** — rows archived in Airtable for history and dashboards. Composable** — swap scrapers, LLMs, storage, or email service. Scalable** — start with 10 tickers, grow to many lists using the same loop. For advanced no-code & AI projects, see 0vni – Agence automatisation.

💥 Clone Video Ads Factory using NanoBanana, Kling and Publish with Blotato 📄 Documentation: Notion Guide Who is this for? This workflow is built for marketers, growth hackers, agencies, content creators, and automation builders who want to industrialize video ad production. Perfect for anyone running paid ads, social media campaigns, UGC-style content, dropshipping creatives, AI ad testing, or scalable content factories. What problem is this workflow solving? / Use case Creating high-performing video ads is: Slow Manual Expensive Hard to scale Hard to test in volume This workflow solves: ❌ Manual editing ❌ Manual prompt writing ❌ Manual scene creation ❌ Manual video assembly ❌ Manual audio integration ❌ Manual publishing It turns one input video + prompt into a fully automated ad production pipeline. What this workflow does This automation system acts as a full AI video ads factory: Step-by-step pipeline: Video Analysis Breaks down the source video into cinematic scenes Extracts structure, rhythm, composition, pacing, and visual logic Prompt Engineering Generates structured prompts for: Images Videos Music Captions Global script Scene structure Image Generation Uses NanoBanana to generate consistent AI images per scene Keeps visual identity across scenes Video Generation Uses Kling to generate cinematic video clips Scene-based video creation Video Merging Automatically merges all generated scenes into one final video Music Generation Generates a full song from prompt (AI music model) Audio + Video Merge Merges generated music with the final video Publishing Automatically publishes content using Blotato Creates posts and media assets ➡️ Result: Fully automated AI video ad production system Setup Required accounts: Airtable fal.ai AtlasCloud** Blotato** Initial configuration: Create Airtable base Add required fields: Original Video Avatar Image Product Image Status Prompts Scenes Music File Final Video Add API keys in the Setup nodes: AtlasCloud fal.ai Airtable Blotato Expected outcome You get a fully automated AI content factory that can: Clone ad styles Scale ad production Test creatives at scale Generate UGC-style ads Build content farms Automate marketing pipelines Create AI ad studios Run continuous ad experiments Typical use cases AI UGC ad factories Dropshipping ad automation SaaS promo videos Influencer content cloning Brand video scaling Marketing automation Ad testing labs Growth hacking pipelines AI content studios 👋 Need help or want to customize this? 📩 Contact: LinkedIn 📺 YouTube: @DRFIRASS 🚀 Workshops: Mes Ateliers n8n Need help customizing? Contact me for consulting and support : Linkedin / Youtube / 🚀 Mes Ateliers n8n

Automate your cold calling process with AI-powered conversation handling, smart scheduling, and comprehensive call tracking How it works This comprehensive cold calling system automates your entire outbound calling workflow in 4 high-level steps: Automated Dialing - System automatically calls prospects from your Airtable database at scheduled intervals AI Conversation Handling - Advanced AI assistant conducts natural conversations, handles objections, and books appointments Smart Call Processing - Real-time call analysis determines outcomes (answered, voicemail, busy) and updates prospect status Intelligent Follow-up - Automatically schedules callbacks, creates calendar appointments, and maintains detailed call records Key Features Automated Prospect Management** - Pulls contacts from Airtable and manages call status AI-Powered Conversations** - Uses VAPI.ai for natural, human-like phone interactions Research Integration** - AI can research prospects using Wikipedia, Hacker News, and web search Calendar Integration** - Automatically books meetings in Google Calendar Call Analytics** - Tracks costs, duration, transcripts, and outcomes Smart Routing** - Different workflows for successful calls vs. callbacks Set up steps Total setup time: ~30 minutes Prerequisites Airtable account with prospect database VAPI.ai account for AI calling Google Calendar (for appointment booking) OpenAI API key SerpAPI key (for web research) Quick Setup (5 steps) Import workflows - Import all 4 workflow files into your n8n instance Configure Airtable - Connect your Airtable base with prospect data (Name, Mobile, Status columns) Set up VAPI.ai - Configure AI assistant and phone number in VAPI dashboard Connect integrations - Add credentials for Google Calendar, OpenAI, and SerpAPI Test & Launch - Run a test call and activate the scheduler Database Structure Your Airtable should include these tables: Data** - Main prospect list (Name, Mobile, Status) Recordings** - Call logs and transcripts Call Later** - Scheduled callbacks Detailed configuration notes are included within each workflow as sticky notes

Auto-Generate Long Videos with AI, ElevenLabs,PIAPI,Shotstack/Creatomate & Post to Youtube Overview This n8n automation workflow automates the creation, scripting, production, and posting of YouTube videos. It leverages AI (OpenAI), image generation (PIAPI), video rendering (Shotstack), and platform integrations (Airtable, Google Sheets, YouTube) to streamline the process. Target Audience Content creators, video producers, and YouTubers** seeking to automate video content creation. Digital marketing teams** managing video campaigns for travel or history niches. Users familiar with n8n, Airtable, Google Sheets, YouTube, and API integrations**. Problem Solved Manually managing YouTube video production, from ideation to posting, is time-consuming and prone to errors. This workflow addresses: Content Sourcing**: Generates video ideas using AI based on "domain of choice". Content Formatting**: Automatically creates detailed scripts and scene structures. Visual Production**: Produces high-quality images and renders videos with minimal manual input. Multi-Platform Integration**: Publishes to YouTube with status tracking in Airtable and Google Sheets. Status Tracking**: Monitors progress (Generated, Scripted, Produced, Published) across platforms. Prerequisites Before setting up, ensure you have: An n8n instance (self-hosted or cloud) API credentials for: OpenAI (for idea generation) PIAPI.ai (for image and video generation) ElevenLabs (for audio generation) Shotstack (for video rendering) Creatomate (for video rendering) Airtable & Google Sheets and Drive (for storage and tracking) Gmail (for notifications) YouTube API (for posting to YouTube) How the Automation Works (Step by Step) Trigger (Schedule Trigger) Initiates the workflow daily Connects to "Generate Idea" Generate Idea Uses OpenAI to create a unique 4-minute video idea with a title, description, keywords, scene structure, and intrigue note Checks Airtable "Ideas" table via searchAirtable to avoid duplicates Connects to "Parse Ideas" Parse Ideas Extracts title, description, and notes from the OpenAI output using JavaScript Connects to "Add Ideas" Add Ideas Stores the initial idea in Google Sheets "Ideas" sheet with fields like "Idea", "Description", and "Progress" (set to "Generated") Connects to "Store in Airtable" Store in Airtable Saves the idea to Airtable "Ideas" table with mapped fields and typecast enabled Connects to "Generate Script" Generate Script Creates a 500-600 word script with 8-10 scenes using OpenAI, based on the latest "Generated" idea Uses Structured Output Parser to format output Connects to "Parse Script Output" Parse Script Output Formats the script into readable text and JSON, extracting scenes and closing question Connects to "Store Script" Store Script Saves the script to Google Sheets "Production" sheet with "Script", "Scenes", and "Status" (set to "Scripted") Connects to "Store Script in Airtable" Store Script in Airtable Saves the script to Airtable "Production" table with mapped fields and typecast enabled Connects to "Updated Idea to Scripted" Updated Idea to Scripted Updates the idea status to "Scripted" in Google Sheets "Ideas" sheet Connects to "Update Status Ideas Table" Update Status Ideas Table Updates the idea status to "Scripted" in Airtable "Ideas" table, matching by "Idea ID" Connects to "Extract Scenes" Extract Scenes Parses scene data from Airtable "Production" table for image generation Connects to "Text-to-Image" Text-to-Image Generates images for each scene using PIAPI Connects to "Wait for 4 Min" Wait for 4 Min Waits 3 minutes to allow image generation to complete Connects to "Get Images" Trigger (Schedule Trigger1) Initiates the posting process daily Connects to "Search for Latest Ready Video" Search for Latest Ready Video Searches Airtable "Production" table for the latest video with "Status" = "Ready" Connects to "If Ready?" If Ready? Checks if a video is ready (condition: Status contains Ready) If true, connects to "Download Video" and "Update Production Table" Download Video Downloads the video file using the VideoURL from Airtable Connects to "Post YouTube" Post YouTube Uploads the video to YouTube with title and description, using YouTube OAuth2 Update Production Table Updates the "Production" sheet in Google Sheets, setting "Status" to "Published" and matching by "Production ID" Additional Nodes and Processes OpenAI Chat Model**: Powers "Generate Idea" and "Generate Script" with GPT Structured Output Parser**: Ensures proper JSON output for scripts Get Images**: Retrieves generated images Extract Narration**: Prepares narration for voice generation Voice Generation**: Generates voiceovers Generate Music Prompt**: Creates music prompts using OpenAI Text-to-Music**: Generates music Build Shotstack Timeline**: Constructs video timeline ShotStack Render Video**: Renders the final video Poll Rendered Videos**: Checks video rendering status Final Video**: Updates Airtable "Production" with final video details Final Video Update**: Updates Google Sheets "Production" with video URL Music Urls**: Adds music URLs to the process Setup Requirements Before starting, ensure you have the following 1 n8n Instance A self-hosted or cloud-based n8n instance to run the workflow 2 API Credentials OpenAI: API key Airtable: Personal Access Token (e.g, "Airtable Personal Access Token Google Sheets: OAuth2 credentials PIAPI: HTTP Header Auth key YouTube: OAuth2 credentials 3 Airtable Configuration Base: "Youtube Videos" Tables: "Ideas" "Production" Share with the Airtable token 4 Google Sheets Configuration Document: "Youtube Videos" Sheets: "Ideas" "Production" Share with the Google Sheets credential email Shotstack Configuration (Assumed) API key and endpoint for video rendering (not specified in JSON) Setup Instructions Import the Workflow Import the provided JSON file into your n8n instance Configure Credentials Add OpenAI, Airtable, Google Sheets, PIAPI, and YouTube credentials in n8n’s credential manager Set Up Airtable Create or update the "Ideas" and "Production" tables with the specified fields Ensure proper permissions with the Airtable token Configure Google Sheets Create or update the "Ideas" and "Production" sheets with the specified columns Share the document with the Google Sheets credential email Schedule Triggers Set "Schedule Trigger" to trigger Test the Workflow Run manually to verify each node’s functionality Check Airtable, Google Sheets, and YouTube for updates Ensure PIAPI image generation completes (wait 4 minutes) Monitor and Adjust Monitor API rate limits (e.g, PIAPI, YouTube) Adjust wait times if image or video generation delays occur Verify connections for unlinked nodes Benefits Efficiency**: Automates the entire process from idea to posting Scalability**: Handles daily video production Quality**: Ensures cinematic scripts and visuals Tracking**: Provides detailed progress monitoring Notes Rate Limits**: Be aware of PIAPI (150,000 units per task) and YouTube API limits Timing**: Adjust wait nodes (e.g, "Wait for 4 Min") based on API response times Conclusion and Suggestions to Improve the Automation Conclusion This workflow streamlines YouTube video production, making it ideal for busy content creators, video producers, and marketing teams. Customize it by adding more platforms, adjusting wait delays for image/video generation, or enhancing notifications for status updates. Share your feedback in the n8n community to help others benefit from this automation. Suggestions to Improve Customization**: Adjust prompts, timings, and API parameters based on your needs Expand "Text-to-Music**" with multiple music styles or integrate a royalty-free music API for variety. Improve Video Rendering**: Optimize "Build Shotstack Timeline" and "ShotStack Render Video" with predefined templates to reduce rendering time. Add Analytics Tracking**: Include a node to fetch YouTube Analytics post-upload for performance monitoring. Error Handling**: Add error-catching nodes (e.g., "If" nodes) to retry failed image or video generations. Notification System**: Incorporate email or Slack notifications for key milestones (e.g., script completion, video upload).

📝 POSTIZ MEDIA UPLOAD WORKFLOW ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 PURPOSE: Automated media upload pipeline that downloads videos and images from Google Drive and uploads them to Postiz storage for social media posting. 🔄 WORKFLOW PROCESS: Webhook triggers the workflow Fetch media metadata from Airtable Download video + image from Google Drive Upload both files to Postiz storage Save Postiz file paths back to Airtable 🔧 TECHNICAL DETAILS: • API: Postiz /upload endpoint (multipart-form-data) • Storage: Converts Google Drive files → Postiz URLs • Integration: Updates Airtable with Postiz paths • Required: All media must be uploaded before posting 📱 SOCIAL MEDIA POSTING WORKFLOW ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 PURPOSE: Automated multi-platform social media posting using Postiz API. Distributes content across Instagram, Twitter/X (2 accounts), LinkedIn, and Facebook with platform-specific content cleaning and formatting. 🔄 COMPLETE WORKFLOW PROCESS: 📊 Fetch social media content from Airtable database 🔗 Get integration IDs for all connected social platforms 🔀 Route each platform to appropriate content processor 🧹 Clean content to prevent JSON formatting errors 📱 Post to respective social media platforms simultaneously 📋 PLATFORM COVERAGE: • 📸 Instagram (Visual content + captions) • 🐦 Twitter/X Main Account (Text + images) • 🐦 Twitter/X Alt Account (Duplicate posting) • 💼 LinkedIn (Professional content) • 📘 Facebook (Meta ecosystem posting) ⚠️ CRITICAL CONTENT CLEANING: • Removes line breaks (\n), carriage returns (\r), tabs (\t) • Replaces multiple spaces with single spaces • Prevents 'JSON parameter needs to be valid JSON' errors • ESSENTIAL: Without cleaning, all API calls fail! 🔧 TECHNICAL SPECIFICATIONS: • API: Postiz /posts endpoint (POST) • Authentication: HTTP Header Auth • Content-Type: application/json • Posting Type: Immediate ('now') + 1 minute delay • Media: References pre-uploaded Postiz image paths • Rate Limit: 30 requests/hour (API beta limitation) 🔗 DATA SOURCES: • Content: Airtable • Media: Pre-uploaded via separate media upload workflow • Fields: instagram_caption, linkedin_post, twitter single, faceboook • Images: References 'postiz image' field paths ⚡ EXECUTION FLOW: Airtable → Integrations → Platform Router → Content Cleaners → Social Publishers 🚨 TROUBLESHOOTING: • JSON Errors: Check content cleaning nodes • 500 Errors: Verify integration IDs and account connections • Missing Media: Ensure media upload workflow ran first • Rate Limits: Space out executions (30/hour limit) 🔄 DEPENDENCIES: • Requires: Media upload workflow (for image/video paths) • Connects to: Analytics and monitoring workflows • Updates: Airtable with posting status and URLs ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ CRITICAL NOTES: • Cannot use external URLs in Postiz posts • Files must be uploaded to google drive first - id referenced in airtable • Enables reference tracking for all platforms 📊 DATA FLOW: Google Drive → Download → Postiz Upload → Airtable Update 🔗 CONNECTS TO: Main social media posting workflows that reference these uploaded file paths for Instagram, Twitter, LinkedIn, Facebook, and YouTube posting. 🎬 VIDEO POSTING WORKFLOW ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 PURPOSE: Automated video content distribution across Instagram, Facebook, and YouTube using Postiz API. Specialized workflow for video content with platform-specific processing and cleaning. 🔄 WORKFLOW EXECUTION: 📊 Fetch video content from Airtable database (recuoYjg4icStHsMK) 🔗 Get integration IDs for video-enabled platforms 🔀 Route platforms to appropriate video processors 🧹 Clean content for Instagram & Facebook (YouTube bypassed) 📹 Publish to video platforms simultaneously 📹 PLATFORM COVERAGE: • 📱 Instagram: Video posts & Reels (✅ Working) • 📘 Facebook: Video content (⚠️ Test mode) • 🎬 YouTube: Long-form videos (🚨 Broken) ⚡ EXECUTION FLOW: Airtable → Integrations → Video Router → [3 Parallel Paths] ├── Instagram: Cleaner → Publisher ├── Facebook: Cleaner → Publisher └── YouTube: [Direct] → Publisher 🗄️ DATA SOURCE: • Base: Netkreatives.com • Table: Youtube tool • Video Field: 'postiz video' • Content Fields: instagram_caption, faceboook 🔧 TECHNICAL SPECS: • Method: POST • Auth: HTTP Header (Postiz credentials) • Timing: Immediate posting (+1 minute delay) • Media: Pre-uploaded video paths • Content-Type: application/json

This workflow automates multi-channel AI-driven sales engagement for lead qualification, service information delivery, and consultation booking. It integrates WhatsApp, Facebook Messenger, Instagram DM, and an n8n chat interface with a backend CRM (Airtable), a knowledge base (Supabase), and conversational AI (OpenAI), all orchestrated by n8n. Tools & Services Used Messaging Platforms: WhatsApp, Facebook Messenger, Instagram DM, n8n Built-in Chat AI Core & Processing: OpenAI (GPT-4o for main agent logic, Whisper for audio transcription) CRM & Data Management: Airtable (for initial WhatsApp lead lookup, lead form submissions, and as the backend for the crmAgent sub-workflow operations) Knowledge Base: Supabase (Vector Store for technical_and_sales_knowledge tool) Chat Memory: PostgreSQL (for the main AI Agent's conversation history) Orchestration & Automation: n8n (Self-hosted, utilizing Langchain community nodes) Calendar Service: Integrated via the calendarAgent sub-workflow CRM Service: Integrated via the crmAgent sub-workflow (interacting with Airtable) Workflow Overview This automation performs the following steps: Trigger: A new interaction is initiated through one of the following channels: A new message is received via the WhatsApp Trigger. A new message is received via the Facebook Trigger (Webhook). A new message is received via the Instagram Trigger (Webhook). A new message is received via the n8n Chat Trigger. Alternatively, a new lead is submitted via the Airtable Form Submitted Webhook. Channel-Specific Ingestion & Pre-processing: For WhatsApp: The system attempts to find an existing lead in Airtable using the sender's phone number. Incoming messages are routed by the Handle Message Types switch: Text messages are passed to the Edit Fields - chat1 node to prepare input for the AI Agent, including any found lead information. Audio messages are processed: the WhatsApp Business Cloud node gets the media URL, the HTTP Request node downloads the audio, OpenAI transcribes it to text, and Edit Fields - chat2 prepares this transcribed text and lead information for the AI Agent. Unsupported message types trigger the Reply To User1 node to send a notification that the message type cannot be processed. For Facebook Messenger: The system responds to webhook verification (Respond to Webhook - facebook get) and acknowledges new messages (Respond to Webhook - facebook post). The If is not echo - facebook node filters out messages sent by the page. The Sales Agent Demo - typing_on node sends a typing indicator. The Edit Fields - facebook node prepares the message text, sender ID, and Facebook-specific context for the AI Agent. For Instagram DM: The system responds to webhook verification (Respond to Webhook - instagram get) and acknowledges new messages (Respond to Webhook - instagram post). The If is not echo - instagram node filters out messages sent by the business account. The Edit Fields - instagram node prepares the message text, sender ID, and Instagram-specific context for the AI Agent. For n8n Chat: The Edit Fields - chat node prepares the user's input and session information for the AI Agent. Input Aggregation for AI Agent: Processed data from all active messaging channels (WhatsApp text/audio, Facebook, Instagram, n8n Chat) is funneled through the No Operation, do nothing node to the main AI Agent. AI Sales Conversation & Tool Utilization: The AI Agent (using OpenAI Chat Model - GPT-4o, and Postgres Chat Memory) engages the user according to its system prompt, aiming to qualify them for Paint Protection Film (PPF), Ceramic Coating, or Window Tint. The AI Agent uses the technical_and_sales_knowledge tool (which queries the Demo Supabase vector store via Embeddings OpenAI and OpenAI Chat Model1) to provide service details and answer questions. The AI Agent uses the crmAgent tool (a sub-workflow) to log contact details (Name, Email, service interest) and update opportunity statuses in Airtable. The AI Agent uses the calendarAgent tool (a sub-workflow) to book consultation appointments once preferred dates/times are provided. This occurs after contact details are logged in the CRM. Response Delivery: The AI Agent's final textual response is passed to the Switch node. The Switch node routes the response to the appropriate node for delivery on the original channel: Reply To User for WhatsApp. Facebook Graph API - Sales Agent Demo for Facebook Messenger. Instagram Graph API - smb.sales.agent.demo for Instagram DM. Output - chat for the n8n Chat interface. Airtable Form Submission Processing (Separate Branch): When the Airtable Form Submitted webhook receives data, the Airtable node fetches the full record. The Create Contact node creates a new contact in the Airtable 'Contacts' table. The Edit Fields - form node prepares data for a notification. The WhatsApp Business Cloud2 node sends a templated WhatsApp message to the lead, confirming their form submission.

Who is this for? This workflow is ideal for sales teams, marketers, and virtual assistants who manage outbound campaigns and want to improve their cold outreach personalization. It helps automate the research and writing process for each lead, saving time while improving quality. What problem is this workflow solving? Cold outreach often lacks personalization because manually reviewing each lead's website takes time. This workflow eliminates that bottleneck by using AI to auto-generate personalized icebreakers, summaries, and outreach emails based on a lead’s website—without human research. What this workflow does This n8n workflow runs on a schedule and pulls leads from Airtable who don't yet have an "Ice breaker" field filled out. For each lead, it does the following: Trigger: Scheduled daily via the Run Daily to Process New Leads node. Search Airtable: Finds leads in Airtable where the Ice breaker field is empty using the Search Cold Leads Without Icebreaker node. Split in Batches: Iterates through each lead one by one using Loop Through Each Lead. Rate Limiting: Waits briefly before each request using Wait Before Making Request to avoid rate limits. Scrape Website: Sends each lead’s website to Dumpling AI's /scrape endpoint via the Scrape Lead Website with Dumpling AI HTTP request. Generate AI Copy: Sends the scraped content to GPT-4o using the Generate Icebreaker, Summary & Email (GPT-4o) node. It asks the LLM to create: A short personalized icebreaker A 2–3 line website summary A short email body for cold outreach Save Results: Updates the original Airtable record with the generated content using the Save AI Output Back to Airtable node. Sticky Note: Provides an overview of the workflow and usage instructions for future editors or collaborators. This loop continues for all leads found, updating Airtable with fresh AI-generated outreach content. Integration Requirements Airtable (Personal Access Token) Dumpling AI API Key (Header Auth) OpenAI (GPT-4o)

Scheduled Trigger: Every X day at Y pm, the workflow is automatically triggered. Fetch User Data: The workflow retrieves all user records from the "WhatsApp Engagement Database" in Airtable. Each record contains the user’s WhatsApp ID, current points, and the number of raffle vouchers. Personalized Message Preparation: For each user, a personalized WhatsApp message is prepared. The message includes: The user’s current point total The number of raffle vouchers they have for the week Encouragement to keep engaging for more chances to win Information about the weekly raffle and available prizes Send WhatsApp Message: The workflow sends this personalized message to each user via the Whapi API, using their WhatsApp ID. Result: Every active user receives a weekly update about their engagement status, raffle tickets, and a motivational message to encourage further participation. This helps boost engagement and keeps users informed about their progress and chances in the weekly raffle.

Find LinkedIn Professionals with Google Search and Airtable Who is this for? This workflow is perfect for sales professionals, recruiters, business development teams, and marketers who need to build targeted prospect lists from LinkedIn. Whether you're looking for specific job titles, industry professionals, or experts in particular locations, this template automates the tedious process of manual LinkedIn searching. Follow me for more What problem is this workflow solving? Finding qualified prospects on LinkedIn manually is time-consuming and inefficient. Traditional methods involve: Manually searching LinkedIn with limited search capabilities Copy-pasting profile information one by one Struggling with LinkedIn's search limitations and restrictions Difficulty organizing and tracking prospect data No systematic way to avoid duplicate contacts This workflow solves these challenges by leveraging Google's powerful search capabilities to find LinkedIn profiles at scale, automatically extracting key information, and organizing everything in a structured database. What this workflow does The workflow performs intelligent LinkedIn prospect discovery through these key steps: Keyword-Based Search: Uses Google Custom Search API to find LinkedIn profiles matching your specific criteria (job titles, industries, locations) Smart Data Extraction: Automatically parses profile titles, descriptions, URLs, and search snippets from Google results Structured Storage: Saves all prospect data to Airtable with proper field mapping and automatic deduplication Pagination Handling: Automatically processes multiple pages of search results to maximize prospect discovery Rate Limiting: Includes built-in delays to respect API limits and ensure reliable operation Key features: Deduplication**: Prevents storing duplicate LinkedIn profiles Batch Processing**: Handles large prospect lists efficiently Customizable Search**: Easily modify keywords to target different professional segments Clean Data Output**: Structured data ready for outreach campaigns Setup Prerequisites You'll need accounts with the following services: Google Cloud Console** (for Custom Search API) Airtable** (free tier works) n8n** (cloud or self-hosted) Step 1: Google Custom Search Setup Go to Google Cloud Console Create a new project or select existing one Enable the Custom Search API Create credentials (API Key) Set up a Custom Search Engine at Google CSE Configure it to search the entire web Copy your Search Engine ID (cx parameter) Bonus: Youtube Set-up Guide Step 2: Airtable Base Setup Create a new Airtable base with a table named "LinkedIn Prospects" containing these fields: Title (Single line text) - LinkedIn profile headline linkedin_url (URL) - Direct link to LinkedIn profile Search (Single line text) - Original search terms used Description (Long text) - Profile description/summary Snippet (Long text) - Google search result snippet Step 3: n8n Credentials Configuration Set up these credentials in n8n: Google Custom Search API: Type: HTTP Query Auth Name: Google Query Auth Query Parameter Name: key Value: Your Google API key Airtable: Type: Airtable Personal Access Token Token: Your Airtable personal access token Configure the base and table IDs in the Airtable node Step 4: Workflow Configuration Import this workflow template Update the "⚙️ CUSTOMIZE YOUR SEARCH KEYWORDS HERE" node with your target keywords Configure the Airtable node with your base and table information Test the workflow with a small keyword set first How to customize this workflow to your needs Targeting Different Industries Modify the search keywords in the yellow configuration node: // For technology professionals "Software Engineer React" "Product Manager SaaS" "Data Scientist Machine Learning" // For sales professionals "Account Executive Enterprise" "Sales Director B2B" "Business Development Manager" // For marketing professionals "Digital Marketing Manager" "Content Marketing Specialist" "Growth Marketing Lead" Geographic Targeting Add location keywords to narrow your search: "Marketing Manager London" "Sales Director New York" "Software Engineer Berlin" Company Size Targeting Include company type indicators: "CFO Startup" "VP Engineering Fortune 500" "Marketing Director SMB" Adjusting Search Volume Modify the Maxresults parameter in the "Configure Search Settings" node: Set to 10 for quick tests Set to 50-100 for comprehensive searches Maximum recommended: 100 per search to respect API limits Industry-Specific Customization For Recruiters: Target specific job titles and seniority levels Add skills-based keywords ("Python Developer", "React Specialist") Include experience indicators ("Senior", "Lead", "Principal") For Sales Teams: Focus on decision-maker titles ("Director", "VP", "C-Level") Target specific company sizes or industries Include location-based searches for territory management For Marketers: Search for industry influencers and thought leaders Target specific professional communities Look for content creators and industry experts Advanced Filtering Add conditional logic after the search results to filter prospects based on: Profile description keywords Title patterns Company information (when available in snippets) Integration Extensions Connect additional tools to enhance your prospect research: Email finder tools** (Hunter.io, Apollo) for contact discovery CRM integration** (HubSpot, Salesforce) for automatic lead creation Enrichment services** (Clearbit, ZoomInfo) for additional prospect data Slack/Teams notifications** for real-time prospect alerts Data Quality Improvements Enhance the workflow with additional processing: Duplicate detection** across multiple search terms Profile validation** to ensure active LinkedIn profiles Keyword scoring** to rank prospect relevance Export formatting** for specific CRM requirements This template provides a solid foundation that can be adapted for virtually any B2B prospect research need, making it an essential tool for modern sales and marketing teams.

Overview This n8n workflow template automates the entire process of publishing Instagram Reels from content stored in Google Sheets and Google Drive. It's designed for content creators, social media managers, and businesses who maintain a content calendar in spreadsheets and need automated publishing with AI-generated captions. Workflow Steps Trigger Phase Schedule Trigger**: Runs every 12 hours (configurable) Google Sheets Trigger**: Alternatively triggers when new rows are added Retrieves the next unposted video from the spreadsheet (where POSTED = FALSE) Content Preparation Downloads video from Google Drive using file ID from spreadsheet Processes video with FFmpeg to add custom text overlays: Title text overlay Numbering overlay Sales hook text Sends processed video using SSH Caption & Metadata Generation Extracts video filename and metadata Uses AI Agent (DeepSeek) to generate engaging Instagram captions: 2-4 engaging sentences 3-5 relevant hashtags Clear call-to-action Under 150 characters total Stores caption and metadata in Airtable for record-keeping Instagram Publishing Creates Facebook/Instagram media container with video URL and caption Waits and polls for video processing completion Publishes the Reel when ready Updates Google Sheet to mark content as posted (POSTED = TRUE) Cleanup Removes temporary video files from disk

This n8n template is a complete, two-part social media engine: it automates competitor/inspiration research, uses AI to recreate viral formats for your niche, and handles multi-platform distribution with auto-generated visuals. Instead of staring at a blank page, this workflow scrapes top-performing content, breaks down the psychological hooks, rewrites it for your specific audience, and drafts a custom text graphic. Once you approve the draft, n8n handles the heavy lifting of posting it everywhere. You curate and approve. n8n researches, writes, designs, and publishes. How it works Part 1: Research & Recreating A scheduled trigger runs daily to pull a target username from your Airtable database. Apify scrapes the latest tweets from that user, filtering out replies and links, and sorts them by the highest view count. An AI Analysis Agent (Gemini) breaks down the top post's structure and creates a reusable template. An AI Writing Agent (GPT) uses that template to write a fresh, original post tailored to your niche. A Caption Agent (GPT) writes an engaging, long-form caption with hooks and hashtags. The draft is saved into Airtable for your review. Part 2: Auto-Posting & Repurposing When you change a draft's status to "Approved" in Airtable, the second flow triggers. An AI Image generator creates a sleek text-graphic based on your short post. The image is uploaded to ImgBB to generate a public URL. The pure text version is pushed directly to X (Twitter) and Threads (via authenticated HTTP requests). The generated image and long-form caption are published to LinkedIn, Facebook, and Instagram. Finally, the Airtable record is marked as "Posted." How to use Set up an Airtable base with your target usernames and a table for content drafts. Update the AI Agent system prompts (Writing and Caption) to match your specific target audience, expertise, and tone. Connect all your platform credentials in n8n (ensure you use the credential manager for the HTTP nodes, like HTTP Header Auth for Threads and Query Auth for ImgBB—no hardcoded API keys!). Let the schedule scrape and draft content for you. Simply mark a draft as "Approved" in Airtable when you want it to go live. What you get Automated viral content research and curation AI-driven structural analysis and rewriting Auto-generated text-graphics for visual platforms Hands-free publishing to 5 platforms (X, Threads, IG, FB, LinkedIn) A centralized content approval system Requirements Airtable account Apify account (Twitter Scraper actor) OpenAI & Google Gemini API credentials ImgBB account X (Twitter), Threads, LinkedIn, Facebook, and Instagram accounts Need help tweaking the AI agents for your specific funnel? Ask in the n8n Forum or shoot me a DM on LinkedIn Happy automating 🚀

Introduction Automates Singapore COE price tracking with AI forecasts and buy/wait recommendations. Weekly scraping collects LTA data, enriches with economic indicators, predicts 6-month trends, and alerts users via Telegram/email—helping car buyers and fleet managers make data-driven purchase decisions while avoiding manual tracking. How it Works Weekly trigger scrapes LTA COE → validates → stores in Google Sheets → calculates indicators → AI forecasts trends → multi-scenario analysis → generates buy/wait signals → sends actionable alerts. Setup Steps Add OpenAI/NVIDIA API credentials in n8n Authenticate Google Sheets and create spreadsheet Configure Telegram bot or Gmail SMTP Set weekly trigger (Thursday 9AM SGT post-bidding) Adjust alert thresholds in conditional nodes Workflow Schedule Trigger → Scrape COE → Validate → Store Sheets → Fetch Historical → Calculate Indicators → AI Prediction → Merge Economics → Multi-Scenario Analysis → Compare Conditions → Generate Dashboard → Send Alerts Workflow Steps Scraping: Fetch LTA COE results with retry logic Validation: Check completeness, flag anomalies Storage: Append timestamped records to Sheets Enrichment: Calculate moving averages, volatility, seasonality AI Analysis: Forecast next 6 months with confidence intervals Decision Engine: Output buy/wait/monitor recommendation Reporting: Create dashboard and send alerts via Telegram/email Prerequisites OpenAI/NVIDIA API key, Google Sheets access, Telegram bot token or Gmail, basic COE category understanding Use Cases First-time buyers timing purchases, fleet operators coordinating bulk acquisitions Customization Add SMS alerts via Twilio, integrate loan calculators for total cost analysis Benefits Saves 5+ hours monthly, captures 10–18% price dips, provides predictive insights (potential $10K–$25K savings)

Who is this for? Creators, designers, and developers exploring AI-powered image generation. Automation enthusiasts who want to integrate image creation into n8n workflows. Telegram bot builders looking to add visual AI capabilities. Marketers or freelancers automating creative content workflows. What problem is this workflow solving? Creating AI images usually requires multiple tools and manual setup. This workflow removes the complexity by: Connecting Nano Banana (AI image model) directly to n8n. Allowing image generation via Telegram chatbot. Providing a no-code setup that is fully automated and scalable. What this workflow does This workflow demonstrates how to generate AI images using Nano Banana and n8n, with an integrated Telegram chatbot interface. The process includes: Connecting Gemini Nano Banana to n8n. Automating image generation requests triggered from Telegram. Returning AI-generated images back to the user. Allowing customization of prompts and styles dynamically. By the end, you’ll have a fully functional automation to generate and send AI-created images through Telegram — no coding required. Setup Create accounts: Sign up on n8n.io and ensure you have Telegram Bot API access. Connect your Nano Banana or Gemini API endpoint. Set up your Telegram Bot: Use BotFather to create a new bot and get the token. Add the “Telegram Trigger” node in n8n. Configure Nano Banana connection: Add an HTTP Request node for Nano Banana API. Insert your API key and prompt parameters. Handle responses: Parse the AI-generated image output. Send the image file back to the Telegram user. Test and Deploy: Run a sample image prompt. Verify that Telegram returns the correct generated image. How to customize this workflow to your needs Modify prompts or styles to fit different artistic use cases. Add conditional logic for image size, aspect ratio, or filters. Integrate with Google Drive or Notion for image storage. Schedule automatic image generation for campaigns or content creation. Expand with OpenAI or Stability AI for hybrid workflows. Notes Nano Banana API may have rate limits depending on usage. Ensure your Telegram bot has permission to send files and images. You can host this workflow on n8n Cloud or self-hosted setups. Want A Video Tutorial on How to Setup This Automation:  https://youtu.be/0s6ZdU1fjc4

Introduction Automate candidate evaluation from CV submission to interview booking. Perfect for HR teams and recruiters. How It Works Webhook receives CVs, extracts Airtable data, AI assesses qualifications, filters candidates, sends emails, schedules Google Calendar interviews, and updates records. Workflow Template Webhook → Airtable (Get Data) → AI Extract CV → AI Assessment → Filter Qualified → Generate Email → Send Email → Filter Interview Candidates → Schedule Calendar → Update Airtable → Slack Notification → Respond Workflow Steps Receive & Store: Webhook receives CVs, saves to Airtable. Fetch & Download: Gets job criteria, downloads CVs. AI Assessment: Parses skills, scores candidates. Filter & Email: Routes qualified, sends messages. Schedule & Update: Books interviews, updates Airtable. Notify: Alerts via Slack, confirms status. Setup Instructions Webhook & Airtable: Set URL, create tables, add credentials. AI Configuration: Add OpenAI key, define schema, customize scoring. Communication: Connect Gmail, Calendar, and Slack. Prerequisites Airtable account OpenAI API key Gmail and Google Calendar Slack workspace (optional) Customization Multi-stage scheduling ATS integration (Greenhouse, Lever) Benefits Reduces screening time by 90% Ensures uniform evaluation Cuts time-to-hire by 60%

Who is this for This workflow is designed for content creators, digital marketers, bloggers, and businesses who need to produce high-quality, SEO-optimized blog posts and newsletters at scale. Perfect for marketing teams, content agencies, solopreneurs, and anyone looking to automate their content creation process while maintaining professional quality. What it does This multi-agent AI system generates complete, research-backed blog posts and newsletters automatically. Four specialized AI agents work in sequence: the Research Agent gathers facts and sources, the Outline Agent structures the content, the Writer Agent creates engaging Medium-style prose, and the Editor Agent polishes and optimizes for search engines. The workflow automatically routes content to either blog format (with DALL-E generated featured images) or newsletter format based on your input, then saves everything to Airtable or Google Sheets for easy management. Requirements OpenRouter API key (for Grok AI model) Google Gemini API key OpenAI API key (for DALL-E image generation) Airtable account Google Sheets account (for newsletters) Telegram bot token (optional, for notifications) How to set up Import the workflow into your n8n instance Add your API credentials to each language model node (OpenRouter, Google Gemini, OpenAI) Configure your Airtable base ID and table ID in the "Save Blog to Airtable" node Set your Google Sheets document ID in the "Save Newsletter to Google Sheets" node (Optional) Add your Telegram bot token and chat ID for notifications Test the workflow by submitting the form with a sample topic How to customize the workflow You can easily adapt this workflow to your specific needs. Replace the AI models with your preferred providers (Claude, GPT-4, Llama, etc.) by swapping the language model nodes. Modify the agent prompts to change writing style, tone, or target audience. Add additional agents for fact-checking, plagiarism detection, or brand voice alignment. Connect the output directly to publishing platforms like WordPress, Medium, Webflow, or email marketing services like Mailchimp. Adjust the image generation parameters to match your brand aesthetic, or skip image generation entirely if not needed.

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.

Who is it for Customer service or support teams who want to use their Zendesk articles in other tools. Content/Knowledge managers consolidating or migrating knowledge bases. Ops/automation specialists who want Markdown versions of articles (could be adapted to Notion, Google Sheets, or any Markdown-friendly system). How to get started Download the template and install it on your instance Set Zendesk and Airtable credentials Modify the Zendesk base_url and Airtable's table and base Run the workflow once manually to get your existing articles Finally, modify the Schedule Trigger (by default it runs every 30 days) and activate the workflow Prerequisites Airtable base** set up using this template. It includes the fields Title, Content, URL and Article ID. Zendesk account** with API access (read permissions for help center articles) Zendesk API credentials** (see instructions below) Airtable API credentials** (see instructions below) Getting Your Credentials Airtable: Sign up or log in to Airtable. Go to your account settings and generate a Personal Access Token (recommended scopes: data.records:read, data.records:write). In n8n, create new Airtable credentials using this token. Zendesk: Log in to your Zendesk dashboard. Go to Admin Center > Apps and Integrations > Zendesk API. Enable “Token Access,” and create an API token. In n8n, add Zendesk credentials with your Zendesk domain, email, and the API token. How it works Triggers Manual:* For first setup, use the Manual Trigger to fetch all* existing articles. Scheduled:* Automatically runs every N days to fetch only new or updated* articles since the last run. Fetch Articles from Zendesk Calls the Zendesk Help Center API, using pagination to handle large volumes. Extract and Prepare Data Splits out each article, then collects fields: id, url, title, and body. Converts the article body from HTML to Markdown (for portability and easier reuse). Upsert Into Airtable Inserts new articles, or updates existing ones (using Article ID as the unique key). Fields stored: Title, Content (Markdown), URL, Article ID. Airtable Template Use this Airtable template as your starting point. Make sure the table has columns: Title, Content, URL, Article ID. You can add more depending on your needs. Example Use Cases Migrating Zendesk articles to another knowledge base. Building an internal knowledge hub in Airtable or Notion. Creating Markdown backups for compliance or versioning. Service If you need help implementing the template or modifying it, just reach out 💌

Receive Webhook Notification The workflow starts when a webhook receives a POST request from Whapi, notifying that a new participant has joined a WhatsApp group. Filter the Event The workflow checks two conditions: The event is for the correct WhatsApp group (matching the specific group ID). The action type is "add" (meaning a user was added to the group). Send Welcome Message If both conditions are met, the workflow sends a personalized welcome message to the new participant via Whapi. The message explains the group rules and how the user can earn points and participate in weekly raffles. Create Airtable Record After sending the welcome message, the workflow creates a new record in the Airtable database for the new participant. The record includes: The participant’s WhatsApp ID An initial engagement count of 100 points The date of the last interaction (set to today) Result Every new group member is automatically welcomed and registered in your engagement database with starter points, ready to participate in your group’s activities and rewards. This workflow ensures new users are greeted, informed, and instantly included in your engagement tracking system.

This workflow allows you to scrape website content, clean the HTML, extract structured information using GPT-5-mini, and store the results along with SEO keywords into Airtable. Ideal for building keyword lists and organizing web content for SEO research. Setup Instructions Prerequisites n8n Community or Cloud instance Airtable account with a base and table ready OpenAI API Key with access to GPT-5-mini Airtable Structure Ensure your Airtable table has the following fields: | Field Name | Type | Notes | | ------------ | ------- | ------------------------------- | | Website Name | String | Name or URL of the website | | Data | String | Cleaned website text | | Keyword | String | Extracted SEO keyword list | | Status | Options | Values: Todo, In progress, Done | Node Setup ✅ Form Trigger: Collects website URL from the user. ✅ HTTP Request: Fetches the website content. ✅ HTML Cleaner (Code Node): Strips out styles, tags, and whitespace to get clean text. ✅ Topic Extractor (AI Agent + GPT-5-mini): Extracts topic-wise information from the cleaned website content. ✅ Text Cleaner (Code Node): Removes unwanted symbols like ### and **. ✅ Keyword Extractor (AI Agent + GPT-5-mini): Generates a list of 90 important SEO keywords. ✅ Airtable Upsert: Stores the cleaned data, keywords, and status in Airtable. Key Features ✅ Automatic website content scraping ✅ Clean HTML and extract plain text ✅ Use GPT-5-mini for topic-wise information extraction ✅ Generate 90-keyword SEO lists ✅ Store and manage data in Airtable Use Cases SEO Keyword Research Competitor Website Content Analysis Structured Website Data Collection Additional Workflow Recommendations ✅ Rename Nodes for Clarity | Current Name | Suggested Name | | ------------ | ------------------------------- | | Website Name | Website URL Input Form | | HTTP Request | Fetch Website Content | | Code | HTML to Plain Text Cleaner | | Split Out1 | Clean Text Splitter | | AI Agent1 | Topic Extractor (GPT-5-mini) | | Code1 | Text Cleanup Formatter | | Split Out2 | Final Text Splitter | | AI Agent | Keyword Extractor (GPT-5-mini) | | Airtable | Airtable Data Upsert | | Wait1 | Delay Before Merge | | Merge | Combine Data for Airtable |

You Don’t Need More Tools. You Just Need the Right Leads. Why spend $1,000s on lead gen when your perfect leads are already waiting in Apollo? You’ve already filtered the ideal prospects. You know who they are, where they work, and what they do. Now imagine turning that list into enriched, ready-to-contact leads—without paying pricey Apollo's recurring subscription (spoiler: you will pay only 0.60$ per 500 leads). From Filter to Outreach-Ready in Seconds With the Lead Generation System, you just drop your Apollo search URL. The workflow does the rest: ✅ Scrapes all matching contacts from your Apollo filter ✅ Enriches and organizes the data (names, roles, emails, LinkedIns, companies, etc.) ✅ Delivers the final lead list to Airtable—or your CRM of choice No more manual exports. No CSV mess. No VA needed. Just qualified leads, cleaned and ready to go. Perfect For Founders doing DIY outbound Growth marketers scaling cold email Agencies running lead-gen for clients Anyone tired of paying too much for messy, outdated lists Setup Guide I built a step-by-step guide to setup this workflow in 5 to 10 minutes, available here: https://notanothermarketer.gitbook.io/home/templates/lead-generation This template is free. Enjoy!

For Who? Content Creators Youtube Automation Marketing Team How it works? 1 - Retrieve Base Image, Image Description and Situation from Airtable 2 - Generate Image Prompt 3 - Generate Image via Fal AI 4 - Verify if Image is generated 5 - Upload Image on Airtable 📺 YouTube Video Tutorial: SETUP Setup Input : The first part of the workflow can be replaced with anything else. You need as input a Prompt and the Base Image URL (publicly available). Setup Output : In this Workflow, the output is storing the image on Airtable but you can replace that with anything else but basically you have two options : Store the Generated Image somewhere : Keep everything like this and replace the last Airtable node with the Third Party you want to use. Use the Image directly in n8n : In HTTP Request "Generate Image" switch sync_mode to "true", remove all the following nodes and add "Extract form File" node (convert to Base64 String) APIs : For the following third-party integrations, replace ==[YOUR_API_TOKEN]== with your API Token or connect your account via Client ID / Secret to your n8n instance: Fal AI (FLUX KONTEXT MAX) : https://fal.ai/models/fal-ai/flux-pro/kontext/max/api#schema-input Airtable : https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.airtable/?utm_source=n8n_app&utm_medium=node_settings_modal-credential_link&utm_campaign=n8n-nodes-base.airtable

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.

🧠 What It Does This n8n workflow collects leads from Google Maps, scrapes their websites via direct HTTP requests, and extracts valid email addresses — all while mimicking real user behavior to improve scraping reliability. It rotates User-Agent headers, introduces randomized delays, and refines URLs by removing only query parameters and fragments to preserve valid page paths (like social media links). The workflow blends Apify actors, raw HTTP requests, HTML-to-Markdown conversion, and smart email extraction to deliver clean, actionable lead data — ready to be sent to Airtable, Google Sheets, or any CRM. Perfect for lean, scalable B2B lead generation using n8n’s native logic and no external scrapers. 💡Why this workflow Modest lead scrapers rely on heavy tools or APIs like Firecrawl. This workflow: Uses lightweight HTTP requests (with randomized user-agents) to scrape websites. Adds natural wait times to avoid rate limits and IP bans. Avoid full-page crawlers, yet still pulls emails effectively. Works great for freelancers, marketers, or teams targeting niche B2B leads. Designed for stealth and resilience. 👤 Who it’s for Lead generation freelancers or consultants. B2B marketers looking to extract real contact info. Small businesses doing targeted outreach. Developers who want a fast, low-footprint scraper. Anyone who wants email + website leads from Google Maps. ⚙️ How It Works 📥 Form Submission (Lead Input) A Form Trigger collects: Keyword Location No. of Leads (defaults to 10) This makes the workflow dynamic and user-friendly — ready for multiple use cases and teams. 📊 Scrape Business Info (via Apify) Apify’s Google Maps Actor searches for matching businesses. The Dataset Node fetches all relevant business details. A Set Node parses key fields like name, phone, website, and category. A Limit Node ensures the workflow only processes the desired number of leads. 🔁 First Loop – Visit & Scrape Website Each business website is processed in a loop. A Code Node cleans the website URL by removing only query parameters/fragments — keeping full paths like /contact. A HTTP Request Node fetches the raw HTML of the site: Uses randomized User-Agent headers (5 variants) to mimic real devices and browsers. This makes requests appear more human and reduces the risk of detection or blocking. HTML is converted to Markdown using the Markdown Node, making it easier to scan for text patterns. A Wait Node introduces a random delay between 2-7 seconds: Helps avoid triggering rate limits, Reduces likelihood of being flagged as a bot. A Merge Node combines scraped markdown + lead info for use in the second loop. 🔁 Second Loop – Extract Emails In this second loop, the markdown data is processed. A Code Node applies regex to extract the first valid email address. If no email is found, "N/A" is returned. A brief 1 second Wait Node simulates realistic browsing time. Another Merge Node attaches the email result to the original lead data. ✅ Filter, Clean & Store A Filter Node removes all entries with "N/A" or invalid email results. A Set Node ensures only required fields (like website, email, and company name) are passed forward. The clean leads are saved to Airtable (or optionally, Google Sheets) using an upsert-style insert to avoid duplicates. 🛡️ Anti-Flagging Design This workflow is optimized for stealth: No scraping tools or headless browsers (like Puppeteer or Firecrawl). Direct HTTP requests with rotating User-Agents. Randomized wait intervals (2-7s). Only non-intrusive parsing — no automation footprints. 🛠 How to Set It Up Open n8n (Cloud or Self-Hosted). Install Apify node search Apify and click on Install. Do this before importing your file. Import the provided .json file into your n8n editor. Set up the required credentials: 🔑 Apify API Key** (used for Google Maps scraping) 🔑 Airtable API Key** (or connect Google Sheets instead) Recommended Prepare your Airtable base or Google Sheet with fields like: Email, Website, Phone, Company Name. Review the Set node if you'd like to collect more fields from Apify (e.g., Ratings, Categories, etc.). 🔁 Customization Tips The Apify scraper returns rich business data. By default, this workflow collects name, phone, and website — but you can add more in the "Grab Desired Fields" node. Need safer scraping at scale? Swap the HTTP Request for Firecrawl’s Single URL scraper (or any headless service like Browserless, Oxylabs, Bright Date, or ScrapingBee) — they handle rendering and IP rotation. Want to extract from internal pages (like /contact or /about)? Use Firecrawl’s async crawl mode — just note it takes longer. For speed and efficiency, this built-in HTTP + Markdown setup is usually the fastest way to grab emails.

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

AI Image Generation Workflow for Social Media Content Overview This n8n workflow automates the creation of photorealistic AI-generated images for social media content. The workflow uses RunComfy (ComfyUI cloud service) combined with Airtable for data management to create high-quality images based on custom prompts and LoRa models. Key Features Automated Image Generation: Creates photorealistic images using Flux Realism model and custom LoRa models Airtable Integration: Centrally manages content requests, model information, and image status Cloud-based Processing: Utilizes RunComfy servers for powerful GPU processing without local hardware requirements Status Tracking: Monitors generation process and automatically updates database entries Telegram Notifications: Sends success notifications after image completion Technical Workflow Server Initialization: Starts RunComfy server with configured specifications Data Retrieval: Fetches content requests from Airtable database Image Generation: Sends prompts to ComfyUI with Flux Realism + LoRa models Status Monitoring: Checks generation progress in 30-second intervals Download: Downloads completed images Database Update: Updates Airtable with image links and status Server Cleanup: Deletes RunComfy server for cost optimization Prerequisites RunComfy Membership** with API access Airtable Account** with configured database Telegram Bot** for notifications Flux Realism Workflow** in RunComfy library Uploaded LoRa Models** in RunComfy Airtable Schema The database must contain these fields: topic: Content description pose_1: Detailed image prompt LoRa Name Flux: LoRa model name Model: Character name pose_1_drive_fotolink: Link to generated image Bilder erstellt: Generation status Configuration Options Image Resolution: Default 832x1216px (adjustable in ComfyUI parameters) Generation Parameters: 35 steps, Euler sampler, Guidance 2.0 Server Size: "Large" for optimal performance (adjustable based on requirements) Time Intervals: 30s status checks, 50s server initialization This workflow is ideal for content creators who need regular, high-quality, character-consistent images for social media campaigns.

Search LinkedIn companies and add them to Airtable CRM Who is this for? This template is ideal for sales teams, business development professionals, and marketers looking to build a robust prospect database without manual LinkedIn research. Perfect for agencies, consultants, and B2B companies targeting specific business profiles. What problem does this workflow solve? Manually researching companies on LinkedIn and adding them to your CRM is time-consuming and error-prone. This automation eliminates the tedious process of finding, qualifying, and importing prospects into your database. What this workflow does This workflow automatically searches for companies on LinkedIn based on your criteria (keywords, size, location), retrieves detailed information about each company, filters them based on quality indicators (follower count and website availability), and adds new companies to your Airtable CRM while preventing duplicates. Setup Create a Ghost Genius API account and get your API key Configure HTTP Request nodes with Header Auth credentials (Name: "Authorization", Value: "Bearer your_api_key") Create an Airtable base named "CRM" with columns: name, website, LinkedIn, id, etc. Set up your Airtable credentials following n8n documentation Add your company search selection criteria to the “Set Variables” node. How to customize this workflow Modify search parameters in the "Set Variables" node to target different industries, locations, or company sizes Adjust the follower count threshold in the "Filter Valid Companies" node based on your qualification criteria Customize the Airtable fields mapping in the "Add Company to CRM" node to match your database structure Add notification nodes (Slack, Email) to alert you when new companies are added

Video Guide I prepared a detailed guide that shows the whole process of building an AI tool to analyze Instagram Reels using n8n. Youtube Link Who is this for? This workflow is ideal for social media analysts, digital marketers, and content creators who want to leverage data-driven insights from their Instagram Reels. It's particularly useful for those looking to automate the analysis of video performance to inform strategy and content creation. What problem does this workflow solve? Analyzing video performance on Instagram can be tedious and time-consuming, requiring multiple steps and data extraction. This workflow automates the process of fetching, analyzing, and recording insights from Instagram Reels, making it simpler for users to track engagement metrics without manual intervention. What this workflow does This workflow integrates several services to analyze Instagram Reels, allowing users to: Automatically fetch recent Reels from specified creators. Analyze the most-watched videos for insights. Store and manage data in Airtable for easy access and reporting. Initial Trigger: The process begins with a manual trigger that can later be modified for scheduled automation. Data Retrieval: It connects to Airtable to fetch a list of creators and their respective Instagram Reels. Video Analysis: It handles the fetching, downloading, and uploading of videos for analysis using an external service, simplifying performance tracking through a structured query process. Record Management: It saves relevant metrics and insights into Airtable, ensuring that users can access and organize their video analytics effectively. Setup Create accounts: Set up Airtable, Edify, n8n, and Gemini accounts. Prepare triggers and modules: Replace credentials in each node accordingly. Configure data flow: Ensure modules are set to fetch and analyze the correct data fields as outlined in the guide. Test the workflow: Run the scenario manually to confirm that data is fetched and analyzed correctly.

Who is this for This workflow is built for real estate investors, wholesalers, and skip tracers who need to find contact details -- phone numbers, emails, and addresses -- for property owners at scale. It automates the entire lookup process using the ScraperCity People Finder API and stores clean results in Airtable for follow-up. How it works A manual trigger starts the workflow. A configuration node lets you define the list of property owner names (or phones/emails) to look up. The workflow submits a skip trace job to the ScraperCity People Finder API, which returns a runId for async tracking. An async polling loop checks the job status every 60 seconds until the result is marked SUCCEEDED. Once complete, the workflow downloads the results CSV and parses each contact record using a code node. Duplicate records are removed, and each unique contact is synced into an Airtable base as a new row with name, phone, email, and address fields. How to set up Create a ScraperCity API credential in n8n (HTTP Header Auth, header name Authorization, value Bearer YOUR_KEY). Update the Configure Search Inputs node with your target names, phones, or emails. Connect your Airtable credential and set your Base ID and Table name in the Sync Contacts to Airtable node. Requirements ScraperCity account with People Finder access (scrapercity.com) Airtable account with a base set up to receive contact data How to customize the workflow Change max_results in Configure Search Inputs to return more contacts per person. Swap the Airtable node for a Google Sheets node if preferred. Add a filter node after parsing to keep only records that have a verified phone number.

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.

Airtable Hierarchical Record Fetcher Description This n8n workflow retrieves an Airtable record along with its related child records in a hierarchical structure. It can fetch up to 3 levels of linked records and assembles them into a comprehensive JSON object, making it ideal for complex data relationships and nested record structures. Features Multi-level Record Fetching**: Retrieves parent record, linked child records (level 2), and optionally grandchild records (level 3) API Call Optimization**: Uses Airtable's filterByFormula to minimize API calls by fetching multiple related records in single requests Selective Level 3 Fetching**: Only fetches level 3 records for specified linked fields to optimize performance Rich Text Processing**: Converts Airtable's pseudo-markdown rich text fields to HTML format Hierarchical JSON Output**: Organizes all data in a structured, nested JSON format Flexible Configuration**: Customizable depth and field selection per execution Input Parameters The workflow accepts a JSON array with the following structure: [ { "base_id": "appN8nPMGoLNuzUbY", "table_id": "tblLVOwpYIe0fGQ52", "record_id": "reczMh1Pp5l94HdYf", "level_3": [ "fldRaFra1rLta66cD", "fld3FxCaYk8AVaEHt" ], "to_html": true } ] Parameter Details | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | base_id | string | Yes | Airtable base identifier | | table_id | string | Yes | Airtable table identifier for the main record | | record_id | string | Yes | Airtable record identifier to fetch | | level_3 | array | No | Array of field IDs from level 2 records for which to fetch level 3 children | | to_html | boolean | No | Convert rich text fields from pseudo-markdown to HTML (default: false). This requires marked npm package. | Output Structure The workflow returns a hierarchical JSON object with the following structure: { "id": "recXXXXXXX", "field_1": ..., "field_2": ..., "level2_child": [ { "id": "recXXXXXXX", "field_a": ..., "field_b": ..., "level3_child": [ { "id": "recXXXXXXX", "field_y": ..., "field_z": ..., }, ... ] }, ... ] } `

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

Startup Funding Research Automation with Claude, Perplexity AI, and Airtable How it works This intelligent workflow automatically discovers and analyzes recently funded startups by: Monitoring multiple news sources (TechCrunch and VentureBeat) for funding announcements Using AI to extract key funding details (company name, amount raised, investors) Conducting automated deep research on each company through perplexity deep research or jina deep search. Organizing all findings into a structured Airtable database for easy access and analysis Set up steps (10-15 minutes) Connect your news feed sources (TechCrunch and VentureBeat). Could be extended. These were easy to scrape and this data can be expensive. Set up your AI service credentials (Claude and Perplexity or jina which has generous free tier) Connect your Airtable account and create a base with appropriate fields (can be imported from my base) or see structure below. Airtable Base Structure Funding Round Base | Field Name | Data Type | Description | |------------|-----------|-------------| | website_url | String | URL of the company website | | company_name | String | Name of the company | | funding_round | String | The funding stage or round (e.g., Series A, Seed, etc.) | | funding_amount | Number | The amount of funding received | | lead_investor | String | The primary investor leading the funding round | | market | String | The market or industry sector the company operates in | | participating_investors | String | List of other investors participating in the funding round | | press_release_url | String | URL to the press release about the funding | | evaluation | Number | The company's valuation | Structure Company Deep Research Base | Field Name | Data Type | Description | |------------|-----------|-------------| | website_url | String | URL of the company website | | company_name | String | Name of the company | | funding_round | String | The funding stage or round (e.g., Series A, Seed, etc.) | | funding_amount | Number | The amount of funding received | | currency | String | Currency of the funding amount | | announcement_date | String | Date when the funding was announced | | lead_investor | String | The primary investor leading the funding round | | participating_investors | String | List of other investors participating in the funding round | | industry | String | The industry sectors the company operates in | | company_description | String | Description of the company's business | | hq_location | String | Company headquarters location | | founding_year | Number | Year the company was founded | | founder_names | String | Names of the company founders | | ceo_name | String | Name of the company CEO | | employee_count | Number | Number of employees at the company | | total_funding | Number | Total funding amount received to date | | total_funding_currency | String | Currency of total funding | | funding_purpose | String | Purpose or use of the funding | | business_model | String | Company's business model | | valuation | Object | Company valuation information | | previous_rounds | Object | Information about previous funding rounds | | source_urls | String | Source URLs for the funding information | | original_report | String | Original report text about the funding | | market | String | The market the company operates in | | press_release_url | String | URL to the press release about the funding | | evaluation | Number | The company's valuation | Notes I found that by using perplexity via open router, we lose access to the sources, as they are not stored in the same location as the report itself so I opted to use perplexity API via HTTP node. For using perplexity and or jina you have to configure header auth as described in Header Auth - n8n Docs What you can learn How to scrape data using sitemaps How to extract strucutred data from unstructured text How to execute parts of the workflow as subworkflow How to use deep research in a practical scenario How to define more complex JSON schemas

Video Guide I prepared a detailed guide that shows the entire process of building an AI agent that integrates with Airtable data in n8n. This template covers everything from data preparation to advanced configurations. Youtube Link Who is this for? This workflow is designed for developers, data analysts, and business owners who want to create an AI-powered conversational agent integrated with Airtable datasets. It is particularly useful for users looking to enhance data interaction through chat interfaces. What problem does this workflow solve? Engaging with data stored in Airtable often requires manual navigation and time-consuming searches. This workflow allows users to interact conversationally with their datasets, retrieving essential information quickly while minimizing the need for complex queries. What this workflow does This workflow enables an AI agent to facilitate chat interactions over Airtable data. The agent can: Retrieve order records, product details, and other relevant data. Execute mathematical functions to analyze data such as calculating averages and totals. Optionally generate maps for geographic data visualization. Dynamic Data Retrieval: The agent uses user prompts to dynamically query the dataset. Memory Management: It retains context during conversations, allowing users to engage in a more natural dialogue. Search and Filter Capabilities: Users can perform tailored searches with specific parameters or filters to refine their results. Set up steps Separate workflows: Create additional workflow and move there Workflow 2. Replace credentials: Replace connections and credentials in all nodes. Start chat: Ask questions and don't forget to mention required base name.

> 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.

Video Guide I prepared a detailed guide that showed the whole process of integrating the Binance API and storing data in Airtable to manage funding statements associated with tokens in a wallet. Youtube Link Who is this for? This workflow is ideal for developers, financial analysts, and cryptocurrency enthusiasts who want to automate the process of managing funding statements and token prices. It’s particularly useful for those who need a systematic approach to track and report funding fees associated with tokens in their wallets. What problem does this workflow solve? Managing funding statements and token prices across multiple platforms can be cumbersome and error-prone. This workflow automates the process, allowing users to seamlessly fetch funding fees from Binance and record them alongside token prices in Airtable, minimizing manual data entry and potential discrepancies. What this workflow does This workflow integrates the Binance API with an Airtable database, facilitating the storage and management of funding statements linked to tokens in a wallet. The agent can: Fetch funding fees and current positions from Binance. Aggregate data to create structured funding statements. Insert records into Airtable, ensuring proper linkage between funding data and tokens. API Authentication: The workflow establishes authentication with the Binance API using a Crypto Node to handle API keys and signatures, ensuring secure and verified requests. Data Collection: It retrieves necessary data, including funding fees and current positions with properly formatted API requests to ensure seamless communication with Binance. Airtable Integration: The workflow inserts aggregated funding statements and token data into the corresponding Airtable records, managing token existence checks to avoid duplicate entries. Setup Set Up Airtable Database: Create an Airtable base with tables for Funding Statements and Tokens. Generate Binance API Key: Log in and create an API key with appropriate permissions. Set Up Authentication in N8N: Utilize a Crypto Node for Binance API authentication. Configure API Request to Binance: Set request method and headers for communication with the Binance API. Fetch Funding Fees and Current Positions: Retrieve funding data and current positions efficiently. Aggregate and Create Statements: Aggregate data to create detailed funding statements. Insert Data into Airtable: Input the structured data into Airtable and manage token records. Using Get Price Node: Implement a Get Price Node to maintain current token price tracking without additional setup.

For Who? Content Creators Youtube Automation Marketing Team How it works? 1 - Every week, retrieve the keywords you want to track 2 - Thanks to Apify, scrape videos from YouTube Search related to these keywords, filtered by relevance 3 - Wait until the dataset is completed 4 - Get the information contained in the dataset 5 - For each video, clean and summarize the script 6 - Upload everything to your Airtable database 📺 YouTube Video Tutorial: Setup (~5min) Scheduled Trigger: Select the frequency you want. If you change it, update the data accordingly in the "Create Videos Dataset" HTTP Request node in Body ➡️ JSON ➡️ dateFilter. Setup Keywords: Enter keywords related to the niche you want. If you change the number of keywords, update the data accordingly in the "Create Videos Dataset" HTTP Request node in Body ➡️ JSON ➡️ searchQueries. Create Videos Dataset: Refer to the Apify documentation for more: https://docs.apify.com/api/v2/getting-started APIs: For all HTTP Request nodes in the URL field, replace [YOUR_API_TOKEN] with your API token. 👨‍💻 More Workflows : https://n8n.io/creators/nasser/

Submission Overview for Voiceflow Demo Workflow View the YouTube video for this workflow here. Who is this for? This workflow is ideal for businesses and developers using Voiceflow to power AI voice chatbots. It benefits teams that want to enhance chatbot functionality through integrations with platforms like Zendesk, Google Calendar, and Airtable. What problem is this workflow solving? The workflow addresses the need for seamless integration of chatbot interactions with backend systems. It automates customer service tasks such as ticket creation, meeting scheduling, and data reporting, reducing manual effort and enhancing efficiency. What does this workflow do? Customer Lookup:** Checks the database for existing customers and returns relevant details or a "NOT_FOUND" status. Zendesk Ticket Creation:** Automates the creation of support tickets for customer issues. Meeting Scheduling:** Integrates with Google Calendar to provide availability and schedule meetings. Transcript Reporting:** Aggregates interaction data and sends it to Airtable for analysis by the product team. Setup Configure your Voiceflow chatbot to connect to this workflow via a webhook. Set up the required integrations: Zendesk API: For ticket creation. Google Calendar API: For scheduling. Airtable API: For storing transcripts. Customize the workflow's nodes to match your use case, such as database fields or API endpoints. Deploy the workflow on your n8n instance and test the integrations. How to customize this workflow to your needs Adjust database queries to match your customer data schema. Modify the Zendesk ticket payload to include additional fields or custom formats. Update Google Calendar configurations for different scheduling requirements. Add or remove Airtable fields based on the product team's analysis needs. This template adheres to n8n’s submission guidelines, ensuring clarity, relevance, and broad applicability for users in customer service, product development, and automation.

Video Guide I prepared a comprehensive guide detailing how to create a Smart Agent that automates meeting task management by analyzing transcripts, generating tasks in Airtable, and scheduling follow-ups when necessary. Youtube Link Who is this for? This workflow is ideal for project managers, team leaders, and business owners looking to enhance productivity during meetings. It is particularly helpful for those who need to convert discussions into actionable items swiftly and effectively. What problem does this workflow solve? Managing action items from meetings can often lead to missed tasks and poor follow-up. This automation alleviates that issue by automatically generating tasks from meeting transcripts, keeping everyone informed about their responsibilities and streamlining communication. What this workflow does The workflow leverages n8n to create a Smart Agent that listens for completed meeting transcripts, processes them using AI, and generates tasks in Airtable. Key functionalities include: Capturing completed meeting events through webhooks. Extracting relevant meeting details such as transcripts and participants using API calls. Generating structured tasks from meeting discussions and sending notifications to clients. Webhook Integration: Listens for meeting completion events to trigger subsequent actions. API Requests for Data: Pulls necessary details like transcripts and participant information from Fireflies. Task and Notification Generation: Automatically creates tasks in Airtable and notifies clients of their responsibilities. Setup N8N Workflow Configure the Webhook: Set up a webhook to capture meeting completion events and integrate it with Fireflies. Retrieve Meeting Content: Use GraphQL API requests to extract meeting details and transcripts, ensuring appropriate authentication through Bearer tokens. AI Processing Setup: Define system messages for AI tasks and configure connections to the AI chat model (e.g., OpenAI's GPT) to process transcripts. Task Creation Logic: Create structured tasks based on AI output, ensuring necessary details are captured and records are created in Airtable. Client Notifications: Use an email node to notify clients about their tasks, ensuring communications are client-specific. Scheduling Follow-Up Calls: Set up Google Calendar events if follow-up meetings are required, populating details from the original meeting context.

Who Is This For? This workflow is designed for marketers, content creators, agencies, and solo founders who want to publish long‑form posts with visuals on autopilot using n8n and AI agents. ​ Whether you run a blog, SaaS, personal brand, newsletter, or client accounts, this tool helps you keep a consistent content pipeline without manually writing every article, creating images, and posting to each platform one by one. ​ ​ 💪🏼 While the template is wired around classic blog + social media distribution, the underlying logic is universal. You can easily adapt it to any niche by editing prompts, swapping models, and re‑wiring nodes. You can plug in any LLM you like, from ChatGPT to Claude, Gemini, Mistral, DeepSeek, OpenRouter, or even local models through Ollama. ​ What Problem Is This Workflow Solving? 🤯 Most teams waste hours on the same repetitive loop: research a topic, gather links, write a blog post, craft social captions, generate visuals, upload everything to multiple platforms, and archive assets. ​ ​ 💎 This workflow solves that by automating the full content chain—from research and blog‑post generation to image creation, publishing across channels, and logging everything in your content database—so your feeds stay active while you focus on strategy, not busywork. ​ What This Workflow Does ✨ Generates in‑depth blog posts tailored to your topic and target audience, enriched with fresh references from the web via Tavily/SerpAPI search tools. ​ ✨ Creates an image prompt and title from the article, generates the visual with OpenAI Images (gpt-image-1), and converts it into a ready‑to‑use image file. ​ ✨ Automatically publishes content to your connected platforms (WordPress for blog posts, Telegram, X/Twitter, Facebook, LinkedIn) while saving images to Google Drive and logging each publication in Google Sheets for tracking. ​ How It Works? Surprisingly simple ☺️ The workflow is triggered by another n8n workflow or by one of several triggers (Facebook, RSS, Google Sheets, Airtable, Postgres) that pass in the blogTopic, targetAudience, and Telegram chatID. ​ ​ The Blog Post Agent (LLM with access to Tavily/SerpAPI) researches the topic, writes a structured article for the specified audience, and sends its output to the Image Prompt Agent, which turns the content into a visual prompt and title. ​ 🎯 The end result: you provide a topic, run the workflow, and receive a complete blog post, matching image, and ready‑made social posts shipped directly to your channels and archives—no manual copy‑paste. ​ How to Customize This Workflow to Your Needs 🎨 Switch AI models and fine‑tune prompts so the agent can handle your exact formats: tutorials, case studies, listicles, product updates, thought‑leadership pieces, or campaign landing posts. 🔍 Refine research sources inside Tavily/SerpAPI to prioritize the domains, blogs, and docs your audience trusts, keeping posts accurate and up to date. ⏰ Adjust posting cadence and schedules to align with peak engagement for your audience, mixing automated slots with manual “launch” runs for special announcements. 📱 Expand or trim channels as needed: keep just WordPress + LinkedIn, add Telegram as a content feed, or plug the workflow into additional automations like email campaigns or RSS feeds. 📊 Use Google Sheets as your content hub to store ideas, angles, CTAs, references, and performance notes so you can double‑down on topics and formats that perform best. 🎬 Swap images for video by replacing the image generation node with video tools (for example, Runway‑style APIs) if your strategy is video‑first while keeping the same prompt pipeline. 💾 Build a reusable prompt library in Sheets, Notion, or Airtable so you can rotate proven prompt patterns each month and keep quality high without reinventing the wheel. 🤖 The system will continuously generate blog posts, visuals, and social updates and publish them across your selected platforms while archiving everything in Drive and Sheets—keeping your brand visible, consistent, and professional with minimal ongoing effort.

This n8n template from Intuz provides a complete and automated solution for transforming a static product image and a creative idea into a dynamic, AI-generated video ad. Using Google's state-of-the-art Veo 3 model, this workflow manages the entire creative process from concept to a final, downloadable video file. Who's this workflow for? E-commerce Brands & Marketers Advertising Agencies Social Media Content Creators Product Managers How it works Submit a Creative Brief: The workflow starts when a user submits a creative idea via a simple web form (e.g., "A Pepsi can exploding into a vibrant disco party"). Upload a Product Image: The user is then prompted to upload a corresponding image (e.g., a high-quality photo of the Pepsi can). Log the Project in Airtable: The idea and the uploaded image are saved to an Airtable base, which acts as the central tracking system for all video generation projects. AI Creative Analysis: Google Gemini analyzes both the user's text prompt and the uploaded image. It acts as an "AI Creative Director," generating a detailed video brief that reinterprets the static image according to the user's creative vision. Generate Video with Veo 3: The detailed creative brief is sent to Google's Veo 3 AI video generation model. The workflow initiates a long-running task to create the video. Retrieve the Final Video: After a brief waiting period, the workflow polls the Veo 3 API to retrieve the finished video, converts it into a binary file, and makes it available for download directly from the n8n execution log. Key Requirements to Use This Template n8n Instance & Required Nodes: An active n8n account (Cloud or self-hosted). This workflow uses the official n8n LangChain integration (@n8n/n8n-nodes-langchain). If you are using a self-hosted version of n8n, please ensure this package is installed. Google Cloud Account: A Google Cloud Project with the Vertex AI API enabled. You must have access to both the Gemini and Veo 3 models within your project. You will need a Gemini API Key and a Google OAuth2 Credential configured for the Vertex AI scope. Airtable Account: An Airtable base with a table set up to track the video projects. It should have columns for Image Prompt, Image (Attachment), Video (Attachment/URL), and Status. Setup Instructions Airtable Configuration (Crucial): In the Create a record, Get a record, and Update record nodes, connect your Airtable credentials and update the Base ID and Table ID to match your setup. In the Uploading Image in Airtable (HTTP Request) node, you must edit the URL and the "Authorization" header to include your Base ID, Table ID, and Personal Access Token. Google AI Configuration (Gemini & Veo): In the Analyze image (Google Gemini) node, select your Gemini API credentials. In both the Generate Video Veo 3 and Get the the Video (HTTP Request) nodes: You must replace [Project ID] and [Location] in the URLs with your own Google Cloud Project ID and region (e.g., us-central1). Select your Google OAuth2 credentials for authentication. Customize Video Parameters (Optional): In the Parse Request (Code) node, you can modify the JavaScript code to change video generation settings like aspectRatio, durationSeconds, and resolution. Execute the Workflow: Activate the workflow. Open the Form URL from the Prompt your Idea node to start the process. Sample Videos Connect with us Website: https://www.intuz.com/n8n-workflow-automation-templates Email: [email protected] LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Workflow Automation Click here- Get Started