Workflow Templates

💥 Automate multi-format design creation in Abyssale and publish via Blotato 📄 Documentation: Notion Guide This workflow automates the creation of multi-format social media visuals using Abyssale and publishes them directly to social platforms via Blotato. It includes AI-based product image generation, background removal, dynamic design customization, and multi-channel distribution. Who is this for? Marketers and growth teams managing multiple social platforms E-commerce brands launching product campaigns Agencies producing multi-format creatives at scale Automation builders who want end-to-end design + publishing in one workflow What problem is this workflow solving? / Use case Creating platform-specific visuals manually is time-consuming. Each social network requires different dimensions and formats. Design → Export → Resize → Upload → Publish quickly becomes repetitive and inefficient. This workflow solves that by: Generating a clean product image (PNG with transparent background) Injecting it automatically into an Abyssale design template Generating all required social media formats Publishing each format to the correct platform automatically What this workflow does Generate product image (AI) Creates a high-quality product image Ensures single product rendering unless otherwise requested Removes background and outputs transparent PNG Customize design in Abyssale Loads selected template Builds editable form dynamically Allows image and text updates Generates multiple formats (Facebook, Instagram, LinkedIn, etc.) Dispatch by format Uses a Switch node to route each format Each format is sent to a dedicated Blotato node Publish to social platforms Facebook post Facebook feed Instagram post Instagram story LinkedIn feed Twitter/X post Pinterest pins Tiktok post Each format is automatically matched with its corresponding publishing node. Setup Credentials required Abyssale API credentials Blotato API credentials AtlasCloud API (NanoBanana) + Background remover API Configure template Select your Abyssale template ID Ensure all required formats are enabled in the template Set publishing destinations Connect Blotato accounts to your social platforms Map each format to the correct channel Optional Adjust polling timing for image generation Modify default caption input How to customize this workflow to your needs Replace the AI image generation model Modify the prompt rules (e.g., product style, realism, lighting) Add or remove social platforms Change the Abyssale template Add approval step before publishing Add scheduling instead of instant publishing Insert analytics tracking after posting You can also extend it by: Adding email notifications Storing generated images in cloud storage Logging posts in a database Creating A/B variations automatically This workflow enables a fully automated pipeline from product idea to published multi-platform campaign with minimal manual work. 🎥 Watch This Tutorial 👋 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

Create & Publish AI Videos from Telegram Chat with VEED and Blotato Overview This n8n workflow creates a conversational AI video agent accessible through Telegram. Users chat with a bot to request AI-generated talking-head videos using VEED's MCP tools, then optionally publish to 9 social media platforms via Blotato with a single approval tap. Output: AI-generated talking-head videos delivered in Telegram and published to TikTok, YouTube, Instagram, LinkedIn, Facebook, X, Threads, Bluesky, and Pinterest. What It Does User Message (Telegram) → AI Agent → VEED MCP tools create video → Response sent via Telegram ↕ Memory ↓ (if video URL detected) Approval prompt (Approve/Reject) ↓ Approved Upload to Blotato → Publish to 9 platforms in parallel ↓ Merge results → Summary sent via Telegram Flow Breakdown | Step | Component | What Happens | |------|-----------|--------------| | 1. Message Received | 📩 Telegram Trigger | User sends a text message to the bot | | 2. AI Processing | 🤖 AI Video Agent (gpt-5-nano) | Interprets request, decides which VEED tools to use | | 3. Context Retention | 💾 Conversation Memory | Maintains conversation history per chat (20-message window) | | 4. Video Creation | 🎬 VEED MCP Tools | Lists characters/voices, confirms details, creates video via VEED Fabric | | 5. Response Delivery | 📤 Send Agent Response | Sends agent text back to user in Telegram | | 6. URL Extraction | 📋 Extract Video URL | Detects the VIDEO_READY: marker in agent output | | 7. Approval Prompt | 📩 Publish to Social Media? | Telegram sendAndWait with Approve/Reject buttons (24h timeout) | | 8. Upload | 📤 Upload Video to Blotato | Uploads video file to Blotato CDN, returns hosted URL | | 9. Publish | TikTok, YouTube, Instagram, LinkedIn, Facebook, X, Threads, Bluesky, Pinterest | All 9 platform nodes post in parallel using the Blotato URL | | 10. Summary | 📤 Send Publish Summary | Confirms publication back to user in Telegram | Required Connections n8n Credentials | Node | Credential Type | Where to Get | |------|-----------------|--------------| | 📩 Telegram Trigger | Telegram Bot API | Create bot via @BotFather in Telegram | | 🧠 OpenAI Chat Model | OpenAI API Key | https://platform.openai.com/api-keys | | 🎬 VEED MCP Tools | MCP OAuth2 | Your VEED OAuth2 client credentials | | 📤 Send Agent Response | Telegram Bot API | Same bot token as trigger | | 📩 Publish to Social Media? | Telegram Bot API | Same bot token as trigger | | 📤 Upload Video to Blotato | Blotato API | https://my.blotato.com/settings → API | | TikTok / YouTube / Instagram / ... | Blotato API | Same Blotato credential as upload | Community Node Required Install @blotato/n8n-nodes-blotato via Settings → Community Nodes → Install in n8n. Configuration Options AI Agent System Prompt The AI Agent's behavior is defined by its system prompt. Edit the 🤖 AI Video Agent node to customize: You are a friendly AI video creation assistant powered by VEED. You help users create professional talking-head videos with AI avatars through Telegram. Video Creation Flow: Understand their need - Ask what video they want Choose a character - Show available AI avatars Choose a voice - Ask preferred language/locale Confirm details - Summarize before creating Create the video - Generate with confirmed parameters Track progress - Poll generation status Deliver result - Share the video URL with VIDEO_READY: marker Agent Configuration | Field | Default | Description | |-------|---------|-------------| | Model | gpt-5-nano | OpenAI model used for reasoning | | Max Iterations | 15 | Maximum tool-calling rounds per message | | Memory Window | 20 messages | How many past messages the agent remembers | | Session Key | {{ $json.message.chat.id }} | Isolates memory per Telegram chat | Available VEED MCP Tools | Tool | Required Parameters | Description | |------|---------------------|-------------| | list_workspaces | — | Show available workspaces | | list_characters | — (optional: gender) | Browse AI avatar characters | | list_voices | locale (e.g. "en") | Browse voices (optional: gender filter) | | confirm_fabric_video | script, voiceId, characterId | Preview video details before creating | | create_fabric_video | script, voiceId, characterId | Create a talking-head video (optional: aspectRatio) | | get_generation_status | jobId | Check video generation progress | | get_credit_balance | — | Check remaining VEED credits | Blotato Platform Configuration Each platform node needs its accountId configured (select from dropdown after connecting Blotato credentials): | Platform | Extra Configuration | |----------|-------------------| | TikTok | — | | YouTube | Title, privacy status (private by default), notify subscribers | | Instagram | — | | LinkedIn | — | | Facebook | Page ID (select from dropdown) | | Twitter / X | — | | Threads | — | | Bluesky | — | | Pinterest | Board ID | Disable any platform node you don't use. Caption Configuration Edit the ⚙️ Set Caption node to customize what gets posted: caption: defaults to first 200 characters of the agent's response video_url: automatically extracted from the VIDEO_READY: marker Conversation Examples | User Says | Agent Does | |-----------|-----------| | "Hi, what can you do?" | Introduces itself and explains video creation capabilities | | "Create a video about AI trends" | Asks about character/voice preferences, then guides through creation flow | | "Show me available characters" | Calls list_characters, formats results for easy selection | | "Use a female English voice" | Calls list_voices with locale "en" and gender filter, shows options | | "Yes, create it!" | Calls create_fabric_video, then immediately checks get_generation_status | | "Is my video ready?" | Calls get_generation_status with the last jobId from memory | | Taps "Approve" | Video uploads to Blotato, publishes to all 9 platforms, summary sent | | Taps "Reject" | "No problem! Your video won't be published to social media." | Output Per Video Generated | Asset | Format | Delivered Via | |-------|--------|---------------| | Video URL | VEED hosted MP4 link | Telegram message | | Approval prompt | Approve/Reject buttons | Telegram sendAndWait | | Social media posts | Video + caption | TikTok, YouTube, Instagram, LinkedIn, Facebook, X, Threads, Bluesky, Pinterest | | Publish summary | Text confirmation | Telegram message | Estimated Costs Per Video | Service | Usage | Approximate Cost | |---------|-------|------------------| | OpenAI gpt-5-nano | 1-3K tokens per conversation turn | $0.005-0.02 | | VEED Fabric | 1 video render (8 credits/sec) | $0.10-0.20 | | Blotato | Media upload + 9 platform posts | Included in paid plan | | Telegram Bot API | Messages | Free | | Total | | ~$0.10-0.25 per video | > Costs vary based on conversation length, video duration, and current API pricing. Setup Checklist Step 1: Import Workflow [ ] Import create-and-publish-ai-videos-from-telegram-chat-with-veed-and-blotato.json into n8n Step 2: Install Blotato Community Node [ ] Go to Settings → Community Nodes → Install [ ] Enter @blotato/n8n-nodes-blotato and install Step 3: Create Telegram Bot [ ] Open Telegram and message @BotFather [ ] Send /newbot and follow the prompts to create your bot [ ] Copy the bot token provided by BotFather Step 4: Configure n8n Credentials [ ] Click on 📩 Telegram Trigger node → Add Telegram Bot credential with your token [ ] Click on 🧠 OpenAI Chat Model node → Add OpenAI API Key credential [ ] Click on 🎬 VEED MCP Tools node → Add MCP OAuth2 credential with your VEED OAuth2 client credentials [ ] Click on 📤 Send Agent Response node → Select the same Telegram Bot credential [ ] Click on 📩 Publish to Social Media? node → Select the same Telegram Bot credential [ ] Click on 📤 Upload Video to Blotato node → Add Blotato API credential (from blotato.com settings) Step 5: Configure Blotato Platforms [ ] Open each platform node (TikTok, YouTube, Instagram, etc.) [ ] Select your connected account from the accountId dropdown [ ] For YouTube: set title and privacy preferences [ ] For Facebook: select your Page from the dropdown [ ] For Pinterest: set Board ID [ ] Disable any platform nodes you don't need Step 6: Activate & Test [ ] Activate the workflow by clicking Publish and toggling it active [ ] Send a test message to your bot in Telegram (e.g., "Hi, what can you do?") [ ] Verify the bot responds with its capabilities [ ] Create a video and test the full flow including the approval prompt [ ] Approve publishing and verify posts appear on your social accounts Limitations & Notes Technical Limitations Telegram activation**: The workflow must be published and active — simply executing it is not enough for the Telegram trigger to receive messages. Memory window**: Only the last 20 messages are retained per conversation. Older context is lost. VEED processing**: Video generation takes 1-5 minutes. The agent reports status but the user must wait. Concurrent users**: Multiple users are supported — each Telegram chat gets independent conversation memory keyed by chat.id. Approval timeout**: The publish prompt expires after 24 hours if not answered. VIDEO_READY marker**: The agent must include VIDEO_READY: <url> in its response for the publishing flow to trigger. This is enforced via the system prompt. Blotato paid plan**: API access requires a paid Blotato subscription. Content Considerations The AI agent autonomously decides which VEED tools to use based on the user's request Users can request specific characters, voices, and scripts through natural conversation The agent cannot edit or modify videos after creation Video output depends on available VEED characters and voices Each second of generated video costs approximately 8 VEED credits Published captions default to the first 200 characters of the agent's response — edit the ⚙️ Set Caption node to customize Best Practices Set bot commands: Use @BotFather's /setcommands to add help commands for your users Test with simple requests first: Start with "list available characters" before attempting full video creation Monitor token usage: Longer conversations consume more OpenAI tokens per turn Customize the system prompt: Tailor the agent's persona, default locale, and guidelines to your use case Disable unused platforms: Disable platform nodes you haven't connected to avoid errors YouTube defaults to private: Videos are published as private by default — change in the YouTube node if needed Troubleshooting | Issue | Solution | |-------|----------| | Bot not responding | Ensure workflow is published and active, not just executed manually | | "Unauthorized" from Telegram | Verify bot token is correct in n8n Telegram credential | | VEED MCP connection failed | Re-authorize the VEED OAuth2 credential in n8n | | Agent doesn't use VEED tools | Verify 🎬 VEED MCP Tools node is connected to the AI Agent node | | Memory not working across messages | Confirm session key expression {{ $('📩 Telegram Trigger').item.json.message.chat.id }} is correct | | Video generation timeout | VEED processing can take up to 5 minutes — agent should poll get_generation_status | | "Model not found" error | Verify OpenAI API key has access to gpt-5-nano model | | No approval prompt after video | Check the agent includes VIDEO_READY: marker — verify system prompt is intact | | Blotato upload fails | Verify Blotato API credential is valid and plan is active | | Platform publish fails | Ensure accountId is configured in the failing platform node | | "Can't parse entities" error | The Send Agent Response node should have no parse_mode set (plain text) | | Blotato node not found | Install @blotato/n8n-nodes-blotato via Settings → Community Nodes | Version History | Version | Date | Changes | |---------|------|---------| | 1.0 | Mar 2026 | Initial release with Telegram bot, AI Agent, VEED MCP integration, conversation memory | | 2.0 | Apr 2026 | Added Blotato multiplatform publishing (9 platforms), Telegram approval flow, video URL extraction, caption configuration | Credits Built with: n8n** - Workflow automation OpenAI** - AI agent reasoning (gpt-5-nano) VEED** - AI video generation (via MCP) Blotato** - Multiplatform social media publishing Telegram** - Chat interface & approval flow LangChain** - Agent framework and memory

🚀 Create Pro-Level Social Media Carousels & Auto-Publish with Blotato By @nocodehack Who is this for? This workflow is built for e-commerce brands, social media managers, marketing agencies, dropshippers, content creators, and automation builders who need to produce professional carousel posts at scale. Perfect for anyone running product marketing, brand campaigns, multi-platform social media, affiliate content, or any business that publishes carousel posts regularly and wants to eliminate design costs entirely. What problem is this workflow solving? / Use case Creating professional carousel posts is: Slow** — designing even one carousel takes 30-60 minutes manually Expensive** — Fiverr/Upwork designers charge $50-100 per carousel Inconsistent** — AI-generated slides never visually match each other Unscalable** — managing multiple brands multiplies every problem Tedious** — exporting, uploading, scheduling, and publishing is repetitive busywork This workflow solves: ❌ Manual carousel design (Canva, Photoshop, Figma) ❌ Paying designers per post ❌ AI images that look obviously AI-generated ❌ Visually inconsistent slides that don't match ❌ Manual copywriting for captions and hashtags ❌ Manual uploading and publishing to each platform ❌ Managing multiple brands with different visual identities It turns one Google Sheet row into a fully designed, published carousel — across Instagram, Facebook, and X — for approximately 5 cents. What this workflow does This automation system acts as a complete AI-powered carousel design studio and publishing pipeline. Step-by-step pipeline: Step 1 — Data Pipeline (Google Sheet) Runs on a schedule (configurable interval) Pulls the next unprocessed row from Google Sheets Each row = one carousel (one brand, one product, one post) Marks the row as "Processing" to prevent duplicate execution Checks if product description and images are provided — if missing, auto-scrapes from the product URL using Jina.ai (free, no account needed) Merges all data into one clean payload for the AI Step 2 — AI Creative Direction (Claude) Sends all product data (description, images as base64, brand logo, creative specifications) to Claude via the Anthropic API Claude acts as an executive creative director — not just generating content, but building a complete visual identity first: Color palette (2-3 hex colors) Typography style and hierarchy Lighting direction and mood Signature design element Background texture concept Then generates for each slide: headline, body copy, layout approach, and a detailed 80+ word image prompt A 2000-word system prompt with banned elements list eliminates the generic AI look (no waves, no scattered leaves, no flat backgrounds, no Canva-style templates) Every image prompt ends with a negative prompt / AVOID block — same concept as Stable Diffusion negative prompts, applied to Gemini Output is structured JSON via a parser — no freeform text that could break the pipeline Also generates the Instagram caption and hashtags Step 3 — Image Generation with Visual Consistency Loop This is the core innovation of the workflow** Slides are generated sequentially, NOT in parallel — this is critical For slide 1: Gemini generates the image from the prompt + product reference images For slide 2+: The workflow fetches all previously generated slides, converts them to base64, and attaches them as reference images alongside the current prompt The text prompt explicitly instructs: "Match the exact typography, color palette, and lighting from the attached previous slides" This creates a double enforcement system — visual reference + written instruction Result: every slide in the carousel shares the same visual identity without using templates or presets Images are generated via NanoBanana Pro (Gemini image generation API) Each generated slide is uploaded to Blotato media storage and saved to a global memory array for the next iteration Uses $getWorkflowStaticData('global') to persist slide URLs across loop iterations Step 4 — Publishing & Status Update Collects all uploaded slide URLs in correct order Reads the "Socials" field from the Google Sheet (comma-separated: instagram, facebook, x) Routes to the correct platform via a Switch node Publishes via Blotato API — supports immediate posting or scheduled posting (ISO 8601 format) One row can publish to all three platforms simultaneously Updates the Google Sheet row: Status → "Published" + direct Post URL If anything breaks: Status → "Failed" with error details ➡️ Result: One Google Sheet row in, one fully designed and published multi-platform carousel out. 5 cents. 5 minutes. Setup Required accounts & API keys: Google Sheets** — read/write access to your content spreadsheet Anthropic** — Claude API key (creative direction + copywriting) Google AI / Gemini** — API key for image generation via NanoBanana Pro ($300 free credit per new Gmail) Blotato** — API key for media upload + multi-platform publishing Jina.ai** — free web scraping, no account required (10M tokens free) Google Sheet structure: Column Description Brand Logo URL Direct link to your brand logo — placed on every slide automatically Product URL Link to product page — used for auto-scraping if description/images are empty Product Description Optional — write it yourself for best results, or leave blank to auto-scrape Product Images URL Direct links to product photos (comma-separated for multiple) Specification Creative direction hint (e.g. "dark cinematic luxury" or "bright playful minimal") — leave empty for AI to decide Post Date YYYY-MM-DD format — workflow only picks up rows matching today's date Post Hour now for immediate publish, or 14:00 / 2pm for scheduled Socials Comma-separated platforms: instagram, facebook, x Status Leave empty — auto-filled: Processing → Published / Failed Post URL Leave empty — auto-filled with direct link to live post Configuration steps: Import the workflow JSON into n8n Add all required API credentials in n8n's credential manager Create your Google Sheet using the template provided (link in resources) Set your Blotato profile IDs in each publishing node (one per platform) Map platform outputs in the Switch node Verify the Gemini image generation endpoint in the NanoBanana Pro node Test with one row before activating production mode Recommended hosting: n8n is free and open source but needs a server. A VPS with at least 2GB RAM handles image generation and multiple API calls without issues. The workflow runs 24/7 on schedule. How to customize Change AI model:** Swap Claude for GPT-4o or Gemini in the LLM Chain node — the structured output parser works with any model Change slide count:** Edit the system prompt and user prompt (currently locked to 3 slides) Change visual style:** Edit the creative direction in the system prompt — modify banned elements, change composition approaches, adjust the quality standard Add platforms:** Add new outputs to the Switch node + new Blotato publish nodes (Blotato supports TikTok, LinkedIn, Pinterest, Threads, YouTube, Bluesky) Add approval step:** Insert a Wait node before publishing to manually review before posting Change image hosting:** Swap Blotato Upload for Cloudinary or any S3-compatible storage Change scraper:** Swap Jina.ai for any other web scraping tool Adjust scheduling:** Modify the Schedule Trigger interval and use the Post Hour column for per-post timing Multi-brand setup:** Each row can have a different brand logo and creative specification — the AI generates a fresh visual identity per row Cost breakdown per carousel (approx.) Component Cost Claude (creative direction + copy, ~8K tokens) ~$0.02 Gemini (3 slide images via NanoBanana Pro) ~$0.03 Jina.ai (web scraping) Free Blotato (publishing) Per plan Total per carousel ~$0.05 Compare: Fiverr/Upwork designers charge $50-100 per carousel post. This workflow does it for 5 cents. Gemini offers $300 free credit per new Gmail account — enough for thousands of carousels before spending anything. Expected outcome You get a fully automated carousel production system that can: Generate agency-quality carousel designs from a spreadsheet Maintain visual consistency across all slides without templates Handle multiple brands with completely different visual identities Publish to Instagram, Facebook, and X simultaneously Schedule content weeks in advance Scale from 1 carousel/day to dozens without additional effort Eliminate design costs almost entirely Typical use cases E-commerce product marketing (daily product carousels) Brand awareness campaigns across multiple platforms Affiliate marketing content at scale Social media agency client deliverables Dropshipping product promotion Multi-brand social media management Content calendar automation A/B testing different creative directions for the same product Watch the full step-by-step walkthrough. 🎥 Video Tutorial 👋 Need help or want to customize? 📩 Contact: LinkedIn 📺 YouTube: @nocodehack 🌐 Resources & Downloads: nocodehack.io

Community Contest Tracker (FB Comments) → Sentiment Analysis → Telegram Winner Alerts + Airtable Proof This workflow automatically monitors a Facebook post, extracts comments, enforces a "past winner" blocklist, analyzes sentiment using AI to find positive entries, randomly selects a winner, stores them in Airtable and announces the result via Telegram. This workflow runs every night to manage your daily community giveaways. It fetches fresh comments from a specific Facebook post and cross-references users against a list of previous winners stored in Airtable to ensure fairness. It uses OpenAI to filter for genuinely positive sentiment (removing spam), selects a random winner, saves the record and sends a celebratory announcement to your Telegram channel. You receive: Daily automated comment collection** Fairness enforcement (Blocklist for past winners)** AI-powered sentiment filtering (Positive vibes only)** Automated winner selection & notification** Ideal for community managers and brand owners who want to run fair, high-engagement contests without manually reading hundreds of comments or tracking past winners in spreadsheets. Quick Start – Implementation Steps Add your Facebook Graph API Credentials in the HTTP Request node. Connect and configure your Airtable base (Winners Table). Add your OpenAI API Key for sentiment analysis. Connect your Telegram Bot credentials and set the Chat ID. Update the Post ID in the "Get FB Comments" node. Activate the workflow — daily contest automation begins instantly. What It Does This workflow automates the entire lifecycle of a social media contest: Daily Trigger: Runs automatically at 9:00 PM every day. Data Ingestion: Fetches the latest comments from Facebook and the full list of past winners from Airtable simultaneously. Pre-Processing: Creates a blocklist of users who won in the last 30 days. Filters out spam, short comments (e.g., single emojis) and blocklisted users. AI Analysis: Uses GPT-4o-mini to analyze the text of eligible comments. Filters specifically for "Positive" sentiment. Selection: Randomly picks one winner from the pool of positive comments. Storage: Saves the winner's Name, Facebook ID and Comment to Airtable. Notification: Sends a "Winner Announcement" to your public Telegram channel. If any errors occur (e.g., DB save fail), logs them to Supabase and alerts the Admin. This ensures your contests are fair, spam-free and consistently managed with zero manual effort. Who’s It For This workflow is ideal for: Social Media Managers Community Moderators Digital Marketing Agencies Brand Owners running daily giveaways Influencers managing high-volume comment sections Customer Experience teams rewarding positive feedback To run this workflow, you will need n8n instance** (cloud or self-hosted) Facebook Developer App** (Graph API Access Token) Airtable Base** + Personal Access Token OpenAI API Key** (or compatible LLM) Telegram Bot Token** Supabase Project** (Optional, for error logging) How It Works Daily Trigger – The schedule node initiates the process. Fetch Data – Comments are pulled from FB; Winners pulled from Airtable. Code Filter – JavaScript node removes past winners and low-quality spam. Sentiment Analysis – AI determines if the comment is Positive, Neutral or Negative. Pick Winner – A randomized logic block selects one "Positive" user. Record Keeping – The winner is officially logged in your database. Broadcast – The winner is announced to the community via Telegram. Setup Steps Import the provided n8n JSON file. Open Get FB Comments node → Add credentials and paste your specific Post ID. Open Get Past Winners node → Link to your Airtable "Winners" table. Open OpenAI Chat Model node → Add your API Key. Open Create a record (Airtable) → Map the fields: Name Facebook ID Date Open Send a text message (Telegram) → Add your Chat ID (e.g., @mychannel). Activate the workflow — done! How To Customize Nodes Customize Filtering Logic Modify the Pre-Filter (Blocklist) Code node: Change the minimum character length (default is 2). Adjust the "Blocklist" duration (e.g., allow users to win again after 7 days instead of 30). Customize AI Criteria Modify the Sentiment Analysis or OpenAI prompt: Look for "Creative" or "Humorous" comments instead of just "Positive". Filter for specific keywords related to your brand. Customize Notifications Replace Telegram with: Slack** (for internal team updates). Discord** (for gaming communities). Email** (SMTP/Gmail) to notify the marketing team. Customize Storage Replace Airtable with: Google Sheets Notion PostgreSQL / MySQL Add-Ons (Optional Enhancements) You can extend this workflow to: Auto-Reply:** Use the Facebook API to reply to the winner's comment automatically ("Congrats! DM us to claim."). Image Generation:** Use OpenAI DALL-E or Bannerbear to generate a "Winner Certificate" image. Cross-Posting:** Automatically post the winner's name to Twitter/X or LinkedIn. Sentiment Report:** Create a weekly summary of overall community sentiment (Positive vs Negative ratio). Prize Tiering:** Assign different prizes based on the quality of the comment. Use Case Examples 1. Daily Product Giveaways Reward one user every day who comments why they love your product. 2. Feedback Drives Encourage users to leave constructive feedback and reward the most helpful positive comment. 3. Community Engagement Keep your group active by automating "Best Comment of the Day" rewards. 4. Brand Loyalty Programs Track "Super Fans" by counting how many times they participate (even if they don't win). Troubleshooting Guide | Issue | Possible Cause | Solution | | :--- | :--- | :--- | | No comments found | Invalid Post ID or Token | Check Facebook Graph API token and Post ID. | | No winner selected | No positive comments | AI found no "Positive" sentiment. Check prompt or input data. | | Airtable Error | Field Mismatch | Ensure column names in Airtable match exactly (Name, Facebook ID). | | Telegram Error | Bot Permissions | Ensure the Bot is an Admin in the channel. | | Workflow Stuck | API Rate Limit | Check OpenAI or Facebook API usage limits. | Need Help? If you need help customizing or extending this workflow, adding multi-platform support (Instagram/YouTube), integrating complex prize logic or setting up advanced dashboards, feel free to hire n8n automation developers at WeblineIndia. We are happy to assist you with advanced automation solutions.

💡 What this workflow does Type #Audit https://clientsite.com in Slack. Walk away. Get a professional PDF report and a structured Excel fix sheet delivered to Google Drive and posted back in your Slack thread — fully automated, zero manual work. Built for SEO agencies and freelancers who deliver technical audits at scale. 👇 Check out the deliverables: 📄 View Sample PDF Report 📊 View Sample Excel Fix Sheet 📦 What You Get 20–50 page PDF report:** Includes a health score, Core Web Vitals, broken links, On-Page SEO, issue cards with fix explanations, a priority action plan, and an SEO glossary. Excel fix sheet:** 18 tabs (one per issue type), containing every URL and exact fix instructions — ready to hand off to a developer. Cloud Storage:** Both files are saved to your Google Drive /SEO Audits folder automatically. Slack Delivery:** Links to the generated files are posted directly back into your original Slack thread. ⚙️ How It Works A Slack message containing #Audit and a URL triggers the workflow. A POST request starts the crawl via your self-hosted Screaming Frog CLI API (built with Python + FastAPI, exposed publicly through a Cloudflare Tunnel — no static IP needed). The workflow polls the API every 2 minutes until the status is done, timeout, or failed. The crawl ZIP is downloaded and decompressed, triggering two simultaneous branches: Branch A (Executive Report): SEO Audit Parser → PageSpeed Insights → PSI Parser → Report Builder → HTML to PDF → Google Drive. Branch B (Developer Sheet): Full Data Parser → Tab Builder → Excel File Builder → Google Drive. Both Google Drive links are merged, logged to a Google Sheet, and posted back into the Slack thread. 🛠️ Key Technical Features Streaming CSV Parser:** Easily handles large crawl files up to 500MB without causing timeouts or memory crashes. Smart File Optimization:** Auto-skips massive all_inlinks.csv and all_anchor_text.csv files (reduces the unzipped payload from 450MB to 15MB). Advanced 403 Error Logic:** Splits 403 errors into three actionable categories: Your own site blocking the crawler (WAF/Cloudflare) Known bot-blocked platforms (Twitter, Wikipedia) Unknown external links requiring a manual check Archive Page Filtering:** Removes tags, pagination, feeds, and search pages from all issue counts so your data isn't skewed. Dynamic Health Score (0–100):** Algorithmically weighted by critical vs. warning issues. Universal CMS Support:** Works flawlessly with WordPress, Blogger, Shopify, and any other crawlable CMS. 📋 What You Need | Requirement | Notes | | :--- | :--- | | Screaming Frog SEO Spider | Licensed version (£199/year) required | | SF CLI API (Python/FastAPI) | Not included in this template — Contact creator below | | Cloudflare Tunnel | Free — exposes your local API publicly | | Google PageSpeed API Key | Free from Google Cloud Console | | PDF Conversion Service | Workflow is pre-configured for pdfendpoint.com | | Google Drive & Sheets | OAuth2 credentials for file storage and audit logging | | Slack | OAuth2 credentials for the trigger and delivery | | n8n (Self-Hosted) | Recommended for long execution times | ⚠️ Required n8n Environment Variables To ensure the workflow can process large sites without timing out, add these to your n8n .env file: N8N_DEFAULT_BINARY_DATA_MODE=filesystem EXECUTIONS_TIMEOUT=7200 N8N_RUNNERS_TASK_TIMEOUT=7200 NODE_OPTIONS=--max-old-space-size=8192 🚀 Quick Setup API Setup: Deploy the SF CLI API on your Windows machine/server and expose it via Cloudflare Tunnel. Link the Crawler: Update the Start Crawl node URL and Bearer token with your tunnel URL and API secret. PageSpeed Insights: Replace the PSI API key in the Page Speed Insights HTTP node with your own. Cloud Storage: Set your Google Drive Folder ID in both upload nodes, and your Google Sheets Spreadsheet ID in the Append row node. Branding: In the Report Builder code node, update the AGENCY config object (around line 125) with your name, email, and tagline. In the Input Cleaner node, set the watermark value to your agency's name. 📞 Support & Custom API Access Note: The custom Python/FastAPI backend required to orchestrate Screaming Frog is not included in this JSON template. If you want to set up the complete system, please reach out: 📧 Email:salmanmehboob1947@gmail.com 🔗 LinkedIn: Salman Mehboob

Automated Podcast Generation with n8n, OpenAI & Buzzsprout This workflow automatically turns any audio file uploaded to Google Drive into a complete podcast episode. It handles transcription, content generation, blog drafting, social copy creation, thumbnail generation, Airtable record updates, Buzzsprout publishing and finally notifies your team via Slack. It is a full “audio-to-published-podcast” automation that requires no manual editing. ⚡ Quick Start: 10-Step Fast Implementation Connect Google Drive, OpenAI, Airtable, Slack & Buzzsprout credentials. Upload an audio file to the Drive folder. Workflow triggers automatically. Audio → Text transcription via OpenAI Whisper. AI converts transcript into title, show notes, tags, publish date, etc. AI generates social content & blog article. AI generates YouTube thumbnail (URL saved). Data saved to Airtable. Episode uploaded to Buzzsprout. Slack receives final “Episode Published” notification. What It Does This workflow automates the complete lifecycle of podcast publishing. Once an audio file is placed inside a Google Drive folder, the system takes over: it transcribes the audio, generates structured metadata, creates rich content including a blog post and multiple social media captions and produces a YouTube-ready thumbnail. Generated content is saved into Airtable, ensuring you always have a centralized database of episode metadata. The workflow then uploads the processed audio file to Buzzsprout, creating a ready-to-publish podcast entry. Finally, it sends a Slack notification summarizing the episode details. This workflow eliminates hours of manual podcast editing, writing and uploading — providing a fast, reliable and repeatable content automation pipeline. Who’s It For Podcasters who want to automate production and publishing Marketing teams managing multiple content channels Creators who want to repurpose audio into blogs & social content Agencies or studios producing podcasts for clients Anyone wanting a hands-free “record → upload → publish” podcast system Airtable Table Structure (Required Fields) To run this workflow successfully, you must create one Airtable table that stores all generated podcast episode data. Below is the exact list of fields (with correct Airtable field types) that the workflow expects. | Field Name | Airtable Field Type | Purpose | | -------------------------- | ------------------- | --------------------------------------------------------- | | episode_title | Single line text | Title generated from the audio transcript | | record_Id | Auto number | Automatically generated unique internal record identifier | | episode_description | Long text | Description of the episode (AI-generated) | | show_notes | Long text | Detailed show notes generated from transcript | | suggested_publish_date | Single line text | Publish date suggested by AI | | blog_draft_markdown | Long text | SEO-optimized full blog draft | | linkedin_post | Long text | LinkedIn long-form post | | instagram_caption | Long text | Instagram caption + hashtags | | twitter_thread | Long text | Thread text (converted from array → single string) | | tiktok_script | Long text | Short TikTok/Shorts script | | youtube_thumbnail_url | URL | Thumbnail image URL generated by OpenAI | | buzzsprout_episode_id | Number | Episode ID returned from Buzzsprout | | audio_url | Single line text | Buzzsprout final audio file URL | | published_at | Single line text | Actual published datetime returned by Buzzsprout | | guid | Single line text | Unique GUID assigned by Buzzsprout | Notes for Users Setting Up the Table Do not use array fields — arrays are converted into strings before saving. record_Id is Airtable auto-number will generate it and it used for update record. published_at, audio_url, guid and buzzsprout_episode_id are populated after Buzzsprout upload. youtube_thumbnail_url is populated after the AI Image Generation node. Requirements To use this workflow, you need: n8n** self-hosted or cloud Google Drive account** (folder monitored for new audio uploads) OpenAI API Key** (Whisper + GPT + Image Generation) Airtable Base & API Key** Buzzsprout Podcast ID & API Token** Slack App / Bot Token** Audio file in MP3/WAV/M4A format How It Works & Setup Steps Step 1 — Google Drive Trigger Monitors a specific folder. When an audio file is uploaded, the workflow starts. Step 2 — Transcribe Audio with OpenAI Uses Whisper model to convert speech → text. Returned transcript is cleaned and extracted. Step 3 — Extract Episode Metadata Title Description Show notes Episode tags Suggested publish date All parsed and structured via OpenAI. Step 4 — Generate Social Media Content LinkedIn article post Twitter/X thread Instagram caption TikTok short script Step 5 — Generate Blog Draft Full SEO-optimized Markdown article created by OpenAI. Step 6 — Create YouTube Thumbnail OpenAI Image API 1280×720 thumbnail URL stored in Airtable. Step 7 — Save Everything to Airtable One single table Stores episode title, description, tags, blog draft, social content, thumbnail URL, and transcript. Step 8 — Upload Episode to Buzzsprout Audio file from Google Drive → uploaded via multipart/form-data Title & description set Response returns audio URL and episode ID These are stored in Airtable. Step 9 — Slack Notification Sends message containing: Episode Title Buzzsprout Episode ID Published At Date Thumbnail URL How to Customize Nodes Google Drive Trigger Change the folder ID to monitor a different source directory. OpenAI Metadata Prompt Adjust tone, style, summarization level or tag generation. Social Content Node Modify the prompt to produce longer posts, more thread tweets or add new channels. Image Generation Customize thumbnail style: minimal, realistic, bold text, brand colors, etc. Buzzsprout Upload Node Set episode[published_at] to schedule future releases. Slack Notification Add more fields such as show notes or Airtable record links. Add-Ons (Optional Enhancements) You may extend the workflow with: Auto-post to LinkedIn, X, Instagram, TikTok** via Buffer API Notion page creation** for drafting content Automatic transcript** upload to Google Docs Email notification** to hosts or guests Auto-publish** YouTube video version (using static background + audio) Use Case Examples Podcast Production Automation – Record audio, upload to Drive and get a fully published episode automatically. Content Repurposing Workflow – Turn one audio file into several content formats instantly. Marketing Team Efficiency – Auto-generate social posts for multiple platforms. Client Podcast Management – Agencies can manage episodes with zero manual work. Internal Communications – Convert internal voice memos into polished summaries and blogs. (There can be many more such use cases depending on customization.) Troubleshooting Guide | Issue | Possible Cause | Solution | | ------------------------------------- | ---------------------------------- | -------------------------------------------------------------------- | | Buzzsprout upload missing audio | Wrong field name or missing binary | Ensure file field is binary & set to correct Drive binary property | | Episode title missing in Buzzsprout | OpenAI JSON not parsed correctly | Check parse code & that episode_title exists | | Social content not stored in Airtable | Airtable field type mismatch | Convert arrays into strings before writing | | Thumbnail not displaying | Expired OpenAI image URL | Regenerate or store static copy in Drive | | Workflow not triggering | Wrong Drive folder ID | Update folder ID in trigger node | Need Help? If you need assistance customizing this workflow, adding new features or building similar automations, WeblineIndia’s n8n automation developers can help you design, optimize and scale enterprise-grade n8n workflows. Feel free to reach out for professional support anytime.

Generate AEO strategy from brand input using AI competitor analysis This workflow automatically creates a comprehensive Answer Engine Optimization (AEO) strategy by identifying your top competitors, analyzing their positioning, and generating custom recommendations to help your brand rank in AI-powered search engines like ChatGPT, Perplexity, and Google SGE. Who it's for This template is perfect for: Digital marketing agencies** offering AEO services to clients In-house marketers** optimizing content for AI search engines Brand strategists** analyzing competitive positioning Content teams** creating AI-optimized content strategies SEO professionals** expanding into Answer Engine Optimization What it does The workflow automates the entire AEO research and strategy process in 6 steps: Collects brand information via a user-friendly web form (brand name, website, niche, product type, email) Identifies top 3 competitors using Google Gemini AI based on product overlap, market position, digital presence, and geographic factors Scrapes target brand website with Firecrawl to extract value propositions, features, and content themes Scrapes competitor websites in parallel to gather competitive intelligence Generates comprehensive AEO strategy using OpenAI GPT-4 with 15+ actionable recommendations Delivers formatted report via email with executive summary, competitive analysis, and implementation roadmap The entire process runs automatically and takes approximately 5-7 minutes to complete. How to set up Requirements You'll need API credentials for: Google Gemini API** (for competitor analysis) - Get API key OpenAI API** (for strategy generation) - Get API key Firecrawl API** (for web scraping) - Get API key Gmail account** (for email delivery) - Use OAuth2 authentication Setup Steps Import the workflow into your n8n instance Configure credentials: Add your Google Gemini API key to the "Google Gemini Chat Model" node Add your OpenAI API key to the "OpenAI Chat Model" node Add your Firecrawl API key as HTTP Header Auth credentials Connect your Gmail account using OAuth2 Activate the workflow and copy the form webhook URL Test the workflow by submitting a real brand through the form Check your email for the generated AEO strategy report Credentials Setup Tips For Firecrawl: Create HTTP Header Auth credentials with header name Authorization and value Bearer YOUR_API_KEY For Gmail: Use OAuth2 to avoid authentication issues with 2FA Test each API credential individually before running the full workflow How it works Competitor Identification The Google Gemini AI agent analyzes your brand based on 4 weighted criteria: product/service overlap (40%), market position (30%), digital presence (20%), and geographic overlap (10%). It returns structured JSON data with competitor names, URLs, overlap percentages, and detailed reasoning. Web Scraping Firecrawl extracts structured data from websites using custom schemas. For each site, it captures: company name, products/services, value proposition, target audience, key features, pricing info, and content themes. This runs asynchronously with 60-second waits to allow for complete extraction. Strategy Generation OpenAI GPT-4 analyzes the combined brand and competitor data to generate a comprehensive report including: executive summary, competitive analysis, 15+ specific AEO tactics across 4 categories (content optimization, structural improvements, authority building, answer engine targeting), content priority matrix with 10 ranked topics, and a detailed implementation roadmap. Email Delivery The strategy is formatted as a professional HTML email with clear sections, visual hierarchy, and actionable next steps. Recipients get an immediately implementable roadmap for improving their AEO performance. How to customize the workflow Change AI Models Replace Google Gemini** with Claude, GPT-4, or other LLM in the competitor analysis node Replace OpenAI** with Anthropic Claude or Google Gemini in the strategy generation node Both use LangChain agent nodes, making model swapping straightforward Modify Competitor Analysis Find more competitors**: Edit the AI prompt to request 5 or 10 competitors instead of 3 Add filtering criteria**: Include factors like company size, funding stage, or geographic focus Change ranking weights**: Adjust the 40/30/20/10 weighting in the prompt Enhance Data Collection Add social media scraping**: Include LinkedIn, Twitter/X, or Facebook page analysis Pull review data**: Integrate G2, Capterra, or Trustpilot APIs for customer sentiment Include traffic data**: Add SimilarWeb or Semrush API calls for competitive metrics Change Output Format Export to Google Docs**: Replace Gmail with Google Docs node to create shareable documents Send to Slack/Discord**: Post strategy summaries to team channels for collaboration Save to database**: Store results in Airtable, PostgreSQL, or MongoDB for tracking Create presentations**: Generate PowerPoint slides using automation tools Add More Features Schedule periodic analysis**: Run monthly competitive audits for specific brands A/B test strategies**: Generate multiple strategies and compare results over time Multi-language support**: Add translation nodes for international brands Custom branding**: Modify email templates with your agency's logo and colors Adjust Scraping Behavior Change Firecrawl schema**: Customize extracted data fields based on industry needs Add timeout handling**: Implement retry logic for failed scraping attempts Scrape more pages**: Extend beyond homepage to include blog, pricing, and about pages Use different scrapers**: Replace Firecrawl with Apify, Browserless, or custom solutions Tips for best results Provide clear brand information**: The more specific the product type and niche, the better the competitor identification Ensure websites are accessible**: Some sites block scrapers; consider adding user agents or rotating IPs Monitor API costs**: Firecrawl and OpenAI charges can add up; set usage limits Review generated strategies**: AI recommendations should be reviewed and customized for your specific context Iterate on prompts**: Fine-tune the AI prompts based on output quality over multiple runs Common use cases Client onboarding** for marketing agencies - Generate initial AEO assessments Content strategy planning** - Identify topics and angles competitors are missing Quarterly audits** - Track competitive positioning changes over time Product launches** - Understand competitive landscape before entering market Sales enablement** - Equip sales teams with competitive intelligence Note: This workflow uses community and AI nodes that require external API access. Make sure your n8n instance can make outbound HTTP requests and has the necessary LangChain nodes installed.

Automated AI-Driven Competitor & Market Intelligence System Problem Solved:** Small and Medium-sized IT companies often struggle to stay ahead in a rapidly evolving market. Manually tracking competitor moves, pricing changes, product updates, and emerging market trends is time-consuming, inconsistent, and often too slow for agile sales strategies. This leads to missed sales opportunities, ineffective pitches, and a reactive rather than proactive market approach. Solution Overview:** This n8n workflow automates the continuous collection and AI-powered analysis of competitor data and market trends. By leveraging web scraping, RSS feeds, and advanced AI models, it transforms raw data into actionable insights for your sales and marketing teams. The system generates structured reports, notifies relevant stakeholders, and stores intelligence in your database, empowering your team with real-time, strategic information. For Whom:** This high-value workflow is perfect for: IT Solution Providers & SaaS Companies: To maintain a competitive edge and tailor sales pitches based on competitor weaknesses and market opportunities. Sales & Marketing Leaders: To gain comprehensive, automated market intelligence without extensive manual research. Product Development Teams: To identify market gaps and validate new feature development based on competitive landscapes and customer sentiment. Business Strategists: To inform strategic planning with data-driven insights into industry trends and competitive threats. How It Works (Scope of the Workflow) ⚙️ This system establishes a powerful, automated pipeline for market and competitor intelligence: Scheduled Data Collection: The workflow runs automatically at predefined intervals (e.g., weekly), initiating data retrieval from various online sources. Diverse Information Gathering: It pulls data from competitor websites (pricing, features, blogs via web scraping services), industry news and blogs (via RSS feeds), and potentially other sources. Intelligent Data Preparation: Collected data is aggregated, cleaned, and pre-processed using custom code to ensure it's in an optimal format for AI analysis, removing noise and extracting relevant text. AI-Powered Analysis: An advanced AI model (like OpenAI's GPT-4o) performs in-depth analysis on the cleaned data. It identifies competitor strengths, weaknesses, new offerings, pricing changes, customer sentiment from reviews, emerging market trends, and suggests specific opportunities and threats for your company. Automated Report Generation: The AI's structured insights are automatically populated into a professional Google Docs report using a predefined template, making the intelligence easily digestible for your team. Team Notification: Stakeholders (sales leads, marketing managers) receive automated notifications via Slack (or email), alerting them to the new report and key insights. Strategic Data Storage & Utilization: All analyzed insights are stored in a central database (e.g., PostgreSQL). This builds a historical record for long-term trend analysis and can optionally trigger sub-workflows to generate personalized sales talking points directly relevant to ongoing deals or specific prospects. Setup Steps 🛠️ (Building the Workflow) To implement this sophisticated workflow in your n8n instance, follow these detailed steps: Prepare Your Digital Assets & Accounts: Google Sheet (Optional, if using for CRM data): For simpler CRM, create a sheet with CompetitorName, LastAnalyzedDate, Strengths, Weaknesses, Opportunities, Threats, SalesTalkingPoints. API Keys & Credentials: OpenAI API Key: Essential for the AI analysis. Web Scraping Service API Key: For services like Apify, Crawlbase, or similar (e.g., Bright Data, ScraperAPI). Database Access: Credentials for your PostgreSQL/MySQL database. Ensure you've created necessary tables (competitor_profiles, market_trends) with appropriate columns. Google Docs Credential: To link n8n to your Google Drive for report generation. Create a template Google Doc with placeholders (e.g., {{competitorName}}, {{strengths}}). Slack Credential: For sending team notifications to specific channels. CRM API Key (Optional): If directly integrating with HubSpot, Salesforce, or custom CRM via API. Identify Data Sources for Intelligence: Compile a list of competitor website URLs you want to monitor (e.g., pricing pages, blog sections, news). Identify relevant online review platforms (e.g., G2, Capterra) for competitor products. Gather RSS Feed URLs from key industry news sources, tech blogs, and competitor's own blogs. Define keywords for general market trends or competitor mentions, if using tools that provide RSS feeds (like Google Alerts). Build the n8n Workflow (10 Key Nodes): Start a new workflow in n8n and add the following nodes, configuring their parameters and connections carefully: Cron (Scheduled Analysis Trigger): Set this to trigger daily or weekly at a specific time (e.g., Every Week, At Hour: 0, At Minute: 0). HTTP Request (Fetch Competitor Web Data): Configure this to call your chosen web scraping service's API. Set Method to POST, URL to the service's API endpoint, and build the JSON/Raw Body with the startUrls (competitor websites, review sites) for scraping, including your API Key in Authentication (e.g., Header Auth). RSS Feed (Fetch News & Blog RSS): Add the URLs of competitor blogs and industry news RSS feeds. Merge (Combine Data Sources): Connect inputs from both Fetch Competitor Web Data and Fetch News & Blog RSS. Use Merge By Position. Code (Pre-process Data for AI): Write JavaScript code to iterate through merged items, extract relevant text content, perform basic cleaning (e.g., HTML stripping), and limit text length for AI input. Output should be an array of objects with content, title, url, and source. OpenAI (AI Analysis & Competitor Insights): Select your OpenAI credential. Set Resource to Chat Completion and Model to gpt-4o. In Messages, create a System message defining AI's role and a User message containing the dynamic prompt (referencing {{ $json.map(item => ... ).join('\\n\\n') }} for content, title, url, source) and requesting a structured JSON output for analysis. Set Output to Raw Data. Google Docs (Generate Market Intelligence Report): Select your Google Docs credential. Set Operation to Create document from template. Provide your Template Document ID and map the Values from the parsed AI output (using JSON.parse($json.choices[0].message.content).PropertyName) to your template placeholders. Slack (Sales & Marketing Team Notification): Select your Slack credential. Set Chat ID to your team's Slack channel ID. Compose the Text message, referencing the report link ({{ $json.documentUrl }}) and key AI insights (e.g., {{ JSON.parse($json.choices[0].message.content).Competitor_Name }}). PostgreSQL (Store Insights to Database): Select your PostgreSQL credential. Set Operation to Execute Query. Write an INSERT ... ON CONFLICT DO UPDATE SQL query to store the AI insights into your competitor_profiles or market_trends table, mapping values from the parsed AI output. OpenAI (Generate Personalized Sales Talking Points - Optional Branch): This node can be part of the main workflow or a separate, manually triggered workflow. Configure it similarly to the main AI node, but with a prompt tailored to generate sales talking points based on a specific sales context and the stored insights. Final Testing & Activation: Run a Test: Before going live, manually trigger the workflow from the first node. Carefully review the data at each stage to ensure correct processing and output. Verify that reports are generated, notifications are sent, and data is stored correctly. Activate Workflow: Once testing is complete and successful, activate the workflow in n8n. This system will empower your IT company's sales team with invaluable, data-driven intelligence, enabling them to close more deals and stay ahead in the market.

💥 Create AI Viral Videos using NanoBanana 2 PRO & VEO3.1 and Publish via Blotato Who is this for? This template is for content creators, marketers, agencies, and UGC studios who want to turn a simple Telegram message into AI-generated vertical videos, automatically published across multiple social platforms using Blotato. What problem is this workflow solving? / Use case Creating short-form video ads usually requires: Designing visuals Writing hooks and captions Generating or editing video Manually uploading to TikTok, Instagram, YouTube, Facebook, LinkedIn, X, etc. This workflow solves that by automating the full pipeline from image + idea → edited image → AI video → multi-platform post. What this workflow does Create Image with NanoBanana 2 PRO User sends a photo + caption idea to a Telegram bot. OpenAI Vision analyzes the reference image. An LLM builds a UGC-style image prompt. NanoBanana 2 PRO generates an enhanced, UGC-friendly image. Generate Video with VEO3.1 An AI Agent structures a detailed Veo prompt (scene, camera, lighting, audio). Prompt is optimized and sent to VEO3.1 reference-to-video. The result is a 9:16, ~8s vertical video downloaded back into n8n. Publish with Blotato Video is uploaded to Blotato. Posts are created for TikTok, Instagram, YouTube, Facebook, LinkedIn, and X using the AI-generated caption, title, and hashtags. A final “Published” message is sent on Telegram. Setup Create and configure: Telegram bot (token in Set: Bot Token (Placeholder) node). OpenAI credentials. Fal.ai API key (for NanoBanana 2 PRO + VEO3.1). Blotato account + API credentials and connected social accounts. Import the template into n8n and update all credential references. Test by sending a product image + short idea to your Telegram bot. How to customize this workflow to your needs Edit the UGC image prompt system message to change visual style (more cinematic, minimal, etc.). Adjust the VEO prompt optimizer to tweak duration, mood, or camera movement. Enable/disable specific Blotato platforms depending on where you want to publish. Modify the caption/hashtag generation logic to match your brand tone, language, or niche. 👋 Need help or want to customize this? 📩 Contact: LinkedIn 📺 YouTube: @DRFIRASS 🚀 Workshops: Mes Ateliers n8n 📄 Documentation: Notion Guide Need help customizing? Contact me for consulting and support : Linkedin / Youtube / 🚀 Mes Ateliers n8n

Overview Transform your Gmail sent folder into a comprehensive, enriched contact database automatically. This workflow processes hundreds or thousands of sent emails, extracting and enriching contact information using AI and web search – saving days of manual work. What This Workflow Does Loads sent Gmail messages and extracts basic contact information Deduplicates contacts against your existing Google Sheets database Searches for email conversation history with each contact AI-powered extraction from email threads (phone, socials, websites) Fallback web search via Brave API when no email history exists Saves enriched data to Google Sheets with all discovered contact details Perfect For Musicians & bands** organizing booker/venue contacts Freelancers & agencies** building client databases Sales teams** enriching prospect lists from outbound campaigns Consultants** creating structured contact databases from years of emails Key Features Intelligent Two-Path Enrichment Path A (Email History)**: Analyzes existing email threads to extract contact details from signatures and message content Path B (Web Search)**: Falls back to Brave API search + HTML scraping when no email history exists AI-Powered Data Extraction Uses GPT-5 Nano to intelligently parse: Phone numbers Website URLs LinkedIn profiles Instagram, Twitter, Facebook, Youtube, TikTok, LinkTree, BandCamp... Alternative email addresses Built-in Deduplication Prevents duplicate entries by checking existing Google Sheets records before processing. Free-Tier Friendly Runs entirely on free tiers: Gmail API (free) OpenAI GPT-5 Nano (cost-effective) Brave Search API (2,000 free searches/month) Google Sheets (free) Setup Requirements Required Accounts & Credentials Gmail Account - OAuth2 credentials for Gmail API access OpenAI API Key - For GPT-5 Nano model Brave Search API Key - Free tier (2,000 searches/month) Google Sheets - OAuth2 credentials Google Sheets Structure Create a Google Sheet with these columns (see template link): Template Sheet: Make a copy here How to Use Clone this workflow to your n8n instance Configure credentials for Gmail, OpenAI, Brave Search, and Google Sheets Create/connect your Google Sheet using the template structure Run manually to process all sent emails and build your initial database Review results in Google Sheets - enriched with discovered contact info First Run Tips Start with a smaller Gmail query (e.g., last 6 months) to test Check Brave API quota before processing large volumes Manual trigger means you control when processing happens Processing time varies based on email volume (typically 2-5 seconds per contact) Customization Ideas Extend the Enrichment Include company information parsing Extract job titles from email signatures Automate Regular Updates Convert manual trigger to scheduled trigger Process only recent sent emails for incremental updates Add email notification when new contacts are added Integration Options Push enriched contacts to CRM (HubSpot, Salesforce) Send Slack notifications for high-value contacts Export to Airtable for relational database features Improve Accuracy Add human-in-the-loop review for uncertain extractions Implement confidence scoring for AI-extracted data Add validation checks for phone numbers and URLs Use Case Example Music Promoter Building Venue Database: Processed 1,835 sent emails to bookers and venues AI extracted contact details from 60% via email signatures Brave search found websites for remaining 40% Final database: 1,835 enriched contacts ready for outreach Time saved: ~40 hours of manual data entry Technical Notes Rate Limiting**: Brave API free tier = 2,000 searches/month Duplicates**: Handled at workflow start, not during processing Empty Results**: Stores email + name even when enrichment fails Model**: Uses GPT-5 Nano for cost-effective parsing Gmail Scope**: Reads sent emails only (not inbox) Cost Estimate For processing 1,000 contacts: Gmail API**: Free GPT-5 Nano**: ~$0.50-2 (depending on email length) Brave Search**: Free (within 2K/month limit) Google Sheets**: Free Total**: Under $2 for 1,000 enriched contacts Template Author: Questions or need help with setup? 📧 Email:xciklv@gmail.com 💼 LinkedIn:https://www.linkedin.com/in/vaclavcikl/

Overview This advanced automation workflow enables deep web scraping combined with Retrieval-Augmented Generation (RAG) to transform websites into intelligent, queryable knowledge bases. The system recursively crawls target websites, extracts content, and indexes all data in a vector database for AI conversational access. How the system works Intelligent Web Scraping and RAG Pipeline Recursive Web Scraper - Automatically crawls every accessible page of a target website Data Extraction - Collects text, metadata, emails, links, and PDF documents Supabase Integration - Stores content in PostgreSQL tables for scalability RAG Vectorization - Generates embeddings and stores them for semantic search AI Query Layer - Connects embeddings to an AI chat engine with citations Error Handling - Automatically retriggers failed queries Setup Instructions Estimated setup time: 30-45 minutes Prerequisites Self-hosted n8n instance (v0.200.0 or higher) Supabase account and project (PostgreSQL enabled) OpenAI/Gemini/Claude API key for embeddings and chat Optional: External vector database (Pinecone, Qdrant) Detailed configuration steps Step 1: Supabase configuration Project creation**: New Supabase project with PostgreSQL enabled Generating credentials**: API keys (anon key and service_role key) and connection string Security configuration**: RLS policies according to your access requirements Step 2: Connect Supabase to n8n Configure Supabase node**: Add credentials to n8n Credentials Test connection**: Verify with a simple query Configure PostgreSQL**: Direct connection for advanced operations Step 3: Preparing the database Main tables**: pages: URLs, content, metadata, scraping statuses documents: Extracted and processed PDF files embeddings: Vectors for semantic search links: Link graph for navigation Management functions**: Scripts to reactivate failed URLs and manage retries Step 4: Configuring automation Recursive scraper**: Starting URL, crawling depth, CSS selectors HTTP extraction**: User-Agent, headers, timeouts, and retry policies Supabase backup**: Batch insertion, data validation, duplicate management Step 5: Error handling and re-executions Failure monitoring**: Automatic detection of failed URLs Manual triggers**: Selective re-execution by domain or date Recovery sub-streams**: Retry logic with exponential backoff Step 6: RAG processing Embedding generation**: Text-embedding models with intelligent chunking Vector storage**: Supabase pgvector or external database Conversational engine**: Connection to chat models with source citations Data structure Main Supabase tables | Table | Content | Usage | |-------|---------|-------| | pages | URLs, HTML content, metadata | Main storage for scraped content | | documents | PDF files, extracted text | Downloaded and processed documents | | embeddings | Vectors, text chunks | Semantic search and RAG | | links | Link graph, navigation | Relationships between pages | Use cases Business and enterprise Competitive intelligence with conversational querying Market research from complex web domains Compliance monitoring and regulatory watch Research and academia Literature extraction with semantic search Building datasets from fragmented sources Legal and technical Scraping legal repositories with intelligent queries Technical documentation transformed into a conversational assistant Key features Advanced scraping Recursive crawling with automatic link discovery Multi-format extraction (HTML, PDF, emails) Intelligent error handling and retry Intelligent RAG Contextual embeddings for semantic search Multi-document queries with citations Intuitive conversational interface Performance and scalability Processing of thousands of pages per execution Embedding cache for fast responses Scalable architecture with Supabase Technical Architecture Main flow: Target URL → Recursive scraping → Content extraction → Supabase storage → Vectorization → Conversational interface Supported types: HTML pages, PDF documents, metadata, links, emails Performance specifications Capacity**: 10,000+ pages per run Response time**: < 5 seconds for RAG queries Accuracy**: >90% relevance for specific domains Scalability**: Distributed architecture via Supabase Advanced configuration Customization Crawling depth and scope controls Domain and content type filters Chunking settings to optimize RAG Monitoring Real-time monitoring in Supabase Cost and performance metrics Detailed conversation logs

💥 Automate YouTube thumbnail creation from video links (with templated.io) Who is this for? This workflow is designed for content creators, YouTubers, and automation enthusiasts who want to automatically generate stunning YouTube thumbnails and streamline their publishing workflow — all within n8n. If you regularly post videos and spend hours designing thumbnails manually, this automation is built for you. What problem is this workflow solving? Creating thumbnails is time-consuming — yet crucial for video performance. This workflow completely automates that process: No more manual design. No more downloading screenshots. No more repetitive uploads. In less than 2 minutes, you can refresh your entire YouTube thumbnail library and make your channel look brand new. What this workflow does Once activated, this workflow can: ✅ Receive YouTube video links via Telegram ✅ Extract metadata (title, description, channel info) via YouTube API ✅ Generate a custom thumbnail automatically using Templated.io ✅ Upload the new thumbnail to Google Drive ✅ Log data in Google Sheets ✅ Send email and Telegram notifications when ready ✅ Create and publish AI-generated social posts on LinkedIn, Facebook, and Twitter via Blotato Bonus: You can re-create dozens of YouTube covers in minutes — saving up to 5 hours per week and around $500/month in manual design effort. Setup 1️⃣ Get a YouTube Data API v3 key from Google Cloud Console 2️⃣ Create a Templated.io account and get your API key + template ID 3️⃣ Set up a Telegram bot using @BotFather 4️⃣ Create a Google Drive folder and copy the folder ID 5️⃣ Create a Google Sheet with columns: Date, Video ID, Video URL, Title, Thumbnail Link, Status 6️⃣ Get your Blotato API key from the dashboard 7️⃣ Connect your social media accounts to Blotato 8️⃣ Fill all credentials in the Workflow Configuration node 9️⃣ Test by sending a YouTube URL to your Telegram bot How to customize this workflow Replace the Templated.io template ID with your own custom thumbnail layout Modify the OpenAI node prompts to change text tone or style Add or remove social platforms in the Blotato section Adjust the wait time (default: 5 minutes) based on template complexity Localize or translate the generated captions as needed Expected Outcome With one Telegram message, you’ll receive: A professional custom thumbnail An instant email + Telegram notification A Google Drive link with your ready-to-use design And your social networks will be automatically updated — no manual uploads. Credits Thumbnail generation powered by Templated.io Social publishing powered by Blotato Automation orchestrated via n8n 👋 Need help or want to customize this? 📩 Contact: LinkedIn 📺 YouTube: @DRFIRASS 🚀 Workshops: Mes Ateliers n8n 🎥 Watch This Tutorial 📄 Documentation: Notion Guide Need help customizing? Contact me for consulting and support : Linkedin / Youtube / 🚀 Mes Ateliers n8n