Generate AI viral videos with NanoBanana & VEO3, shared on socials via Blotato
Generate AI viral videos with NanoBanana & VEO3, shared on socials via Blotato Who is this for? This workflow is designed for content creators, marketers, and entrepreneurs who want to automate their video production and social media publishing process. If you regularly post promotional or viral-style content on platforms like TikTok, YouTube Shorts, Instagram Reels, LinkedIn, and more, this template will save you hours of manual work. --- What problem is this workflow solving? / Use case Creating viral short-form videos is often time-consuming: You need to generate visuals, write scripts, edit videos, and then manually upload them to multiple platforms. Staying consistent across TikTok, YouTube Shorts, Instagram Reels, LinkedIn, Twitter/X, and others requires constant effort. This workflow solves the problem by automating the entire pipeline from idea → video creation → multi-platform publishing. --- What this workflow does Collects an idea and image from Telegram. Enhances visuals with NanoBanana for user-generated content style. Generates a complete video script with AI (OpenAI + structured prompts). Creates the final video with VEO3 using your custom prompt and visuals. Rewrites captions with GPT to be short, catchy, and optimized for social platforms. Saves metadata in Google Sheets for tracking and management. Auto-uploads the video to all major platforms via Blotato (TikTok, YouTube, Instagram, LinkedIn, Threads, Pinterest, X/Twitter, Bluesky, Facebook). Notifies you on Telegram with a preview link once publishing is complete. --- Setup Connect your accounts: Google Sheets (for video tracking) Telegram (to receive and send media) Blotato (for multi-platform publishing) OpenAI API (for captions, prompts, and image analysis) VEO3 API (for video rendering) Fal.ai (for NanoBanana image editing) Google Drive (to store processed images) Set your credentials in the respective nodes. Adjust the Google Sheet IDs to match your own sheet structure. Insert your Telegram bot token in the Set: Bot Token (Placeholder) node. --- How to customize this workflow to your needs Platforms: Disable or enable only the Blotato social accounts you want to post to. Video style: Adjust the master prompt schema in the Set Master Prompt node to fine-tune tone, camera style, or video format. Captions: Modify the GPT prompt in the Rewrite Caption with GPT-4o node to control length and tone. Notifications: Customize the Telegram nodes to notify team members, not just yourself. Scheduling: Add a Cron trigger if you want automatic posting at specific times. --- ✨ With this workflow, you go from idea → AI-enhanced video → instant multi-platform publishing in just minutes, with almost no manual work. 📄 Documentation: Notion Guide --- Need help customizing? Contact me for consulting and support : Linkedin / Youtube
By Dr. FirasAI-powered lead generation with Apollo, GPT-4, and Telegram to database
AI-Powered Lead Generation with Apollo, GPT-4, and Telegram to Database Overview This intelligent lead generation workflow transforms voice commands or text input into verified prospect lists through automated Apollo.io scraping. The system processes natural language requests, extracts search parameters using AI, and delivers clean, verified contact data directly to your database. Key Features 🎤 Voice & Text Input Processing Voice Recognition: Converts audio messages to text using OpenAI's transcription API Natural Language Processing: AI agent interprets requests and extracts search criteria Flexible Input: Supports both voice commands and text messages 🔍 Smart Lead Scraping Apollo.io Integration: Automated scraping using official Apollo.io API Dynamic URL Generation: Builds search URLs based on extracted parameters Intelligent Parsing: Processes location, industry, and job title criteria ✅ Email Verification & Filtering Verified Emails Only: Filters results to include only verified email addresses Duplicate Prevention: Compares against existing database to avoid duplicates Data Quality Control: Ensures high-quality prospect data 📊 Automated Data Management Database Integration: Automatic storage in PostgreSQL/Supabase Structured Data: Organizes contacts with complete profile information Real-time Updates: Instant database updates with new prospects How It Works Input Processing: Receive voice message or text command AI Analysis: Extract search parameters (location, industry, job titles) URL Construction: Build Apollo.io search URL with extracted criteria Data Scraping: Retrieve prospect data via Apollo.io API Email Verification: Filter for verified email addresses only Duplicate Check: Compare against existing database records Data Storage: Save new prospects to database Confirmation: Send success notification with count of new leads Supported Search Parameters Location: City, state, country combinations Industry: Business sectors and verticals Job Titles: Executive roles, departments, seniority levels Company Size: Organization scale and employee count Data Fields Extracted Contact Information First Name & Last Name Email Address (verified only) LinkedIn Profile URL Phone Number (when available) Professional Details Current Job Title Company Name Industry Seniority Level Employment History Location Data City & State Country Full Location String Company Information Website URL Business Industry Organization Details Technical Architecture Core Components n8n Workflow Engine: Orchestrates the entire process OpenAI Integration: Powers voice transcription and AI analysis Apollo.io API: Source for prospect data PostgreSQL/Supabase: Database storage and management API Integrations OpenAI Whisper API for voice transcription OpenAI GPT for natural language processing Apollo.io API for lead data retrieval Supabase API for database operations Use Cases Sales Teams Quickly build prospect lists for outreach campaigns Target specific industries or job roles Maintain clean, verified contact databases Marketing Professionals Generate targeted lead lists for campaigns Research prospects in specific markets Build comprehensive contact databases Business Development Identify potential partners or clients Research competitive landscapes Generate contact lists for networking Recruitment Find candidates in specific locations Target particular job roles or industries Build talent pipeline databases Benefits ⚡ Speed & Efficiency Voice commands for instant lead generation Automated processing eliminates manual work Batch processing for large prospect lists 🎯 Precision Targeting AI-powered parameter extraction Flexible search criteria combinations Industry and role-specific filtering 📈 Data Quality Verified email addresses only Duplicate prevention Structured, consistent data format 🔄 Automation End-to-end automated workflow Real-time database updates Instant confirmation notifications Setup Requirements Prerequisites n8n workflow platform OpenAI API access Apollo.io API credentials PostgreSQL or Supabase database Messaging platform integration Configuration Steps Import workflow into n8n Configure API credentials Set up database connections Customize search parameters Test with sample voice/text input Customization Options Search Parameters Modify location formats Add custom industry categories Adjust job title variations Set result limits Data Processing Customize field mappings Add data validation rules Implement additional filters Configure output formats Integration Options Connect to CRM systems Add email marketing tools Integrate with sales platforms Export to various formats Success Metrics Processing Speed: Voice-to-database in under 30 seconds Data Accuracy: 95%+ verified email addresses Automation Level: 100% hands-free operation Scalability: Process 500+ leads per request --- Transform your lead generation process with intelligent automation that understands natural language and delivers verified prospects directly to your database.
By PaulYoutube outlier detector (find trending content based on your competitors)
Video explanation This n8n workflow helps you identify trending videos within your niche by detecting outlier videos that significantly outperform a channel's average views. It automates the process of monitoring competitor channels, saving time and streamlining content research. Included in the Workflow Automated Competitor Video Tracking Monitors videos from specified competitor channels, fetching data directly from the YouTube API. Outlier Detection Based on Channel Averages Compares each video’s performance against the channel’s historical average to identify significant spikes in viewership. Historical Video Data Management Stores video statistics in a PostgreSQL database, allowing the workflow to only fetch new videos and optimize API usage. Short Video Filtering Automatically removes short videos based on duration thresholds. Flexible Video Retrieval Fetches up to 3 months of historical data on the first run and only new videos on subsequent runs. PostgreSQL Database Integration Includes SQL queries for database setup, video insertion, and performance analysis. Configurable Outlier Threshold Focuses on videos published within the last two weeks with view counts at least twice the channel's average. Data Output for Analysis Outputs best-performing videos along with their engagement metrics, making it easier to identify trending topics. Requirements n8n installed on your machine or server A valid YouTube Data API key Access to a PostgreSQL database This workflow is intended for educational and research purposes, helping content creators gain insights into what topics resonate with audiences without manual daily monitoring.
By Leonardo GrigorioGenerate food recipes from Gmail & form requests with Ollama & Llama 3.2
This n8n template demonstrates how to create an intelligent food recipe assistant that accepts requests via Gmail and web forms, processes them using AI chat models (Ollama and Llama 3.2), and delivers personalized recipes back to users. The system combines multiple input methods with advanced AI processing to provide customized cooking instructions and ingredient lists. Good to know The system accepts recipe requests through both Gmail and web form submissions AI models understand dietary restrictions, cuisine preferences, and cooking skill levels Recipe responses include formatted ingredients, step-by-step instructions, and cooking tips All requests are processed automatically without manual intervention How it works Gmail Recipe Request Workflow Gmail triggers activate when users send emails with recipe requests to the designated email address The system extracts recipe requirements, dietary preferences, and cooking constraints from email content User queries are processed through the Ollama Recipe Generator for intelligent recipe creation AI-generated recipes are formatted with proper ingredients, instructions, and cooking times Formatted recipes are sent back to users via Gmail with a professional presentation Web Form Recipe Request Workflow Web form submissions trigger when users fill out structured recipe request forms Form data includes cuisine type, dietary restrictions, available ingredients, and cooking time preferences The Llama 3.2 Chef Model processes structured requests for optimized recipe generation Recipes are formatted with clear instructions, ingredient measurements, and cooking techniques Users receive formatted recipes via email with additional cooking tips and variations How to use Import the workflow into your n8n instance and configure Gmail integration for recipe requests Set up the web form with fields for cuisine preferences, dietary restrictions, and cooking skill level Configure Ollama and Llama 3.2 AI models with appropriate recipe generation prompts Test both Gmail and web form inputs with sample recipe requests Customize email templates to match your brand and include additional cooking resources The system scales automatically to handle multiple simultaneous recipe requests Requirements Gmail account for email-based recipe requests and responses Ollama installation with Recipe Generator model Llama 3.2 Chef Model access for advanced recipe processing n8n instance with Gmail and AI model integrations Customising this workflow Recipe automation can be adapted for different cuisines, dietary needs, and cooking skill levels Try popular use-cases such as meal planning assistance, ingredient substitution suggestions, or nutritional information inclusion The workflow can be extended to include recipe image generation, shopping list creation, and cooking video recommendations
By Oneclick AI SquadLinkedIn lead generation: Auto DM system with comment triggers using Unipile & NocoDB
Short Description This LinkedIn automation workflow monitors post comments for specific trigger words and automatically sends direct messages with lead magnets to engaged users. The system checks connection status, handles non-connected users with connection requests, and prevents duplicate outreach by tracking all interactions in a database. Key Features Comment Monitoring: Scans LinkedIn post comments for customizable trigger words Connection Status Check: Determines if users are 1st-degree connections Automated DMs: Sends personalized messages with lead magnet links to connected users Connection Requests: Asks non-connected users to connect via comment replies Duplicate Prevention: Tracks interactions in NocoDB to avoid repeat messages Message Rotation: Uses different comment reply variations for authenticity Batch Processing: Handles multiple comments with built-in delays Who This Workflow Is For Content creators looking to convert post engagement into leads Coaches and consultants sharing valuable LinkedIn content Anyone wanting to automate lead capture from LinkedIn posts How It Works Setup: Configure post ID, trigger word, and lead magnet link via form Comment Extraction: Retrieves all comments from the specified post using Unipile Trigger Detection: Filters comments containing the specified trigger word Connection Check: Determines if commenters are 1st-degree connections Smart Routing: Connected users receive DMs, others get connection requests Database Logging: Records all interactions to prevent duplicates Setup Requirements Required Credentials Unipile API Key: For LinkedIn API access NocoDB API Token: For database tracking Database Structure Table: leads linkedin_id: LinkedIn user ID name: User's full name headline: LinkedIn headline url: Profile URL date: Interaction date posts_id: Post reference connection_status: Network distance dm_status: Interaction type (sent/connection request) Customization Options Message Templates: Modify DM and connection request messages Trigger Words: Change the words that activate the workflow Timing: Adjust delays between messages (8-12 seconds default) Reply Variations: Add more comment reply options for authenticity Installation Instructions Import the workflow into your n8n instance Set up NocoDB database with required table structure Configure Unipile and NocoDB credentials Set environment variables for Unipile root URL and LinkedIn account ID Test with a sample post before full use
By Alexandra SpalatoAutomate job applications with AI resume tailoring using GPT-4o, LinkedIn & Gmail
Overview Stop applying manually. This workflow acts as your personal AI recruiter, automating the end-to-end process of finding high-quality jobs, tailoring your resume, and preparing personalized outreach emails to decision-makers. What this workflow does Scrapes Real-Time Jobs: Uses Apify to pull live job listings from LinkedIn based on your specific keywords (e.g., "AI Automation"). Smart Filtering: Uses GPT-4o-mini to analyze job descriptions against your skills and automatically discards roles that aren't a good fit. Hyper-Personalized Resume: Uses GPT-4o to rewrite your "Master Resume" specifically for the target job description. Document Generation: Creates a new Google Doc with the tailored resume and automatically sets sharing permissions. Decision Maker Enrichment: Uses Anymail Finder to locate the verified email address of the Company CEO or Hiring Manager. Cold Email Draft: Generates a personalized pitch in Gmail (Drafts folder) with the link to your custom resume attached. Setup Requirements To run this workflow, you will need to set up credentials in n8n for the following services. Please ensure you use n8n credentials and do not hardcode API keys into the HTTP nodes: Google Drive & Docs: To read your master resume and create new application files. Apify Account: To run the LinkedIn Job Scraper actor. OpenAI API Key: For logic (GPT-4o-mini) and writing (GPT-4o). Anymail Finder API: To find contact email addresses. Gmail: To create the draft emails. How to use Upload Resume: Paste your "Master Resume" text into the first Google Docs node or connect your existing file. Configure Credentials: Add your API keys in the n8n credentials section for all services listed above. Set Search Criteria: Update the JSON body in the Apify node with your desired LinkedIn job search URL. Run: Execute the workflow and watch your drafts folder fill up with ready-to-send applications.
By WebsenseproControl Discord bot with natural language via MCP server
What it is- I wanted to create a simple, easy-to-use, MCP server for your Discord bot(s). How to set up- Literally all you do is select your bot auth (or crease a new Discord Bot auth if you havn't entered your key in n8n before) and that's IT! How to use it- You can now ask your bot to do things via any MCP client, including from within N8N workflows! Note: If you need an example, you can check out my simple quickstart Discord MCP Server that uses 4o to send messages to channels on your server and users who are members of the server the bot is in. Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community
By David AshbyBulk delete all YouTube playlists from your channel
🧑💼 Who is this for? This workflow is for any YouTube user who wants to bulk delete all playlists from their own channel — whether to start fresh, clean up old content, or prepare the account for a new purpose. It’s useful for: Creators reorganizing their channel People transferring content to another account Anyone who wants to avoid deleting playlists manually one by one 🧠 What problem is this workflow solving? YouTube does not offer a built-in way to delete multiple playlists at once. If you have dozens or hundreds of playlists, removing them manually is extremely time-consuming. This workflow automates the entire deletion process in seconds, saving you hours of repetitive effort. ⚙️ What this workflow does Connects to your YouTube account Fetches all playlists you’ve created (excluding system playlists) Deletes them one by one automatically > ⚠️ This action is irreversible. Once a playlist is deleted, it cannot be recovered. Use with caution. 🛠️ Setup 🔐 Create a YouTube OAuth2 credential in n8n for your channel. 🧭 Assign the credential to both YouTube nodes. ✅ Click “Test workflow” to execute. > 🟨 By default, this workflow deletes everything. If you want to be more selective, see the customization tips below. 🧩 How to customize this workflow to your needs ✅ Add a confirmation flag Insert a Set node with a custom field like confirm_delete = true, and follow it with an IF node to prevent accidental execution. ✂️ Delete only some playlists Add a Filter node after fetching playlists — you can match by title, ID, or keyword (e.g. only delete playlists containing “old”). 🛑 Add a pause before deletion Insert a Wait or NoOp node to give you a moment to cancel before it runs. 🔁 Adapt to scheduled cleanups Use a Cron trigger if you want to periodically clear temporary playlists.
By Lucía Maio BriosoSend automated appointment reminders via SMS with Twilio webhook
How It Works The workflow is an automated appointment reminder system built on n8n. Here is a step-by-step breakdown of its process: Reminder Webhook This node acts as the entry point for the workflow. It's a unique URL that waits for data to be sent to it from an external application, such as a booking or scheduling platform. When a new appointment is created in that system, it sends a JSON payload to this webhook. Extract Appointment Data This is a Code node that processes the incoming data. It's a critical step that: Extracts the customer's name, phone number, appointment time, and service from the webhook's JSON payload. Includes validation to ensure a phone number is present, throwing an error if it's missing. Formats the raw appointment time into a human-readable string for the SMS message. Send SMS Reminder This node uses your Twilio credentials to send an SMS message. It dynamically constructs the message using the data extracted in the previous step. The message is personalized with the customer's name and includes the formatted appointment details. --- Setup Instructions Import the Workflow Copy the JSON code from the Canvas and import it into your n8n instance. Connect Your Twilio Account Click on the "Send SMS Reminder" node. In the "Credentials" section, you will need to either select your existing Twilio account or add new credentials by providing your Account SID and Auth Token from your Twilio console. Find the Webhook URL Click on the "Reminder Webhook" node. The unique URL for this workflow will be displayed. Copy this URL. Configure Your Booking System Go to your booking or scheduling platform (e.g., Calendly, Acuity). In the settings or integrations section, find where you can add a new webhook. Paste the URL you copied from n8n here. You'll need to map the data fields from your booking system (like customer name, phone, etc.) to match the expected format shown in the comments of the "Extract Appointment Data" node. --- Once these steps are complete, your workflow will be ready to automatically send SMS reminders whenever a new appointment is created.
By David OlusolaCreate RAG vector database from Google Drive documents using Gemini & Supabase
How it works This workflow automates the process of converting Google Drive documents into searchable vector embeddings for AI-powered applications: • Takes a Google Drive folder URL as input • Initializes a Supabase vector database with pgvector extension • Fetches all files from the specified Drive folder • Downloads and converts each file to plain text • Generates 768-dimensional embeddings using Google Gemini • Stores documents with embeddings in Supabase for semantic search Built for the Study Agent workflow to power document-based Q&A, but also works perfectly for any RAG system, AI chatbot, knowledge base, or semantic search application that needs to query document collections. Set up steps Prerequisites: • Google Drive OAuth2 credentials • Supabase account with Postgres connection details • Google Gemini API key (free tier available) Setup time: ~10 minutes Steps: Add your Google Drive OAuth2 credentials to the Google Drive nodes Configure Supabase Postgres credentials in the SQL node Add Supabase API credentials to the Vector Store node Add Google Gemini API key to the Embeddings node Update the input with your Drive folder URL Execute the workflow Note: The SQL query will drop any existing "documents" table, so backup data if needed. Detailed node-by-node instructions are in the sticky notes within the workflow. Works with: Study Agent (main use case), custom AI agents, chatbots, documentation search, customer support bots, or any RAG application.
By Mantaka MahirGenerate meta & TikTok ad copy with OpenAI and Slack approval workflow
Who's it for Marketing teams, copywriters, and agencies who need to quickly generate and iterate on ad copies for Meta and TikTok campaigns. Perfect for brands that want AI-powered copy generation with human review and approval built into the workflow. What it does This workflow automates the ad copy creation process by: Collecting brand and product information through a form Using AI to generate tailored ad copies based on brand type (Fashion or Problem-Solution) Sending copies to Slack for team review and approval Handling revision requests with feedback incorporation Limiting revisions to 3 rounds to maintain efficiency How to set up Configure your OpenAI credentials in the OpenAI nodes Set up Slack integration and select your review channel in all Slack nodes Customize the AI prompts in the OpenAI nodes to match your brand voice Test the form to ensure file uploads and data collection work properly Activate the workflow when ready Requirements OpenAI API access (GPT-3.5 or GPT-4) Slack workspace with appropriate channel permissions Self-hosted n8n instance (for file upload functionality) How to customize Adjust the AI prompts in OpenAI nodes to match your specific industry or brand guidelines Modify the revision limit in the "Edit Fields: Revision Counter Max 3" node Add additional brand types in the form dropdown and corresponding AI nodes Customize Slack messages to match your team's communication style
By Chris RudyTranscribe & analyze Telegram voice messages with AssemblyAI & GPT-4.1 to Gmail
Telegram Voice → AI Summary & Sentiment Analysis via Gmail This n8n template demonstrates how to capture Telegram voice messages, transcribe them into text using AssemblyAI, analyze the transcript with AI for summary and sentiment insights, and finally deliver a structured email report via Gmail. Use cases Automating meeting or lecture voice note transcriptions. Gathering student feedback or training session insights from voice messages. Quickly summarizing Telegram-delivered audio inputs into structured reports. Reducing manual effort in capturing sentiment and key action items from conversations. How it works A voice message is sent to a connected Telegram Bot. The workflow fetches the file and uploads it to AssemblyAI. AssemblyAI generates a transcript from the audio. The transcript is analyzed by OpenAI to extract: Executive summary (120–180 words) Sentiment label and score Key points Action items (if any) Notable quotes Topics The formatted analysis is sent as an email report using Gmail. The workflow ends with a clean summary email containing actionable insights. How to use Import this workflow into your n8n instance. Set up and connect the required credentials: Telegram Bot API token AssemblyAI API key OpenAI API key Gmail OAuth2 account Replace placeholders (e.g., <<YOUREMAIL ID>> and <<YOURASSEMBLYAIAPIKEY>>) with your actual values. Start the workflow. Whenever a voice message is received on the Telegram Bot, the workflow will process it end-to-end and deliver a polished email report. Requirements Telegram Bot account (API token) AssemblyAI account with API key OpenAI account with API key Gmail OAuth2 credentials configured in n8n Active n8n instance Customising this workflow You can customize the email formatting, sentiment thresholds, or extend the workflow to save transcripts into Google Drive, Airtable, or any other connected apps. Additionally, you can trigger the same workflow from multiple input sources (e.g., local audio files, Google Drive links, or Telegram).
By Sridevi Edupuganti