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How it works The automation loads rows from a Google Sheet of leads that you want to contact. It makes a Google search via Apify for LinkedIn links based on the First name / Last name / Company. Another Apify actor fetches the right LinkedIn profile based on the first profile which is retuned The same process is done for the company that the lead works for, giving extra context. If the lead has a current company listed on their LinkedIn, we use that URL to do the lookup, rather than doing a separate Google search. A call is made to OpenRouter to get an LLM to generate an email based on a prompt designed to do personalized outreach. An email is sent via a Gmail node. Set up steps Connect your Google Sheets + Gmail accounts to use these APIs. Make an account with Apify and enter your credentials. Set your details in the "Set My Data" node to customize the workflow to revolve around your company + value proposition. I would recommend changing the prompt in the "Generate Personalized Email" node to match the tone of voice that you want your agent to have. You can change the guidelines to e.g. change whether the agent introduces itself, and give more examples in the style you want to make the output better.
by Adam JanesAutomate video ads with NanoBanana, Seedream 4, ChatGPT Image and Veo 3 Who is this for? This template is designed for marketers, content creators, and e-commerce brands who want to automate the creation of professional ad videos at scale. It’s ideal for teams looking to generate consistent, high-quality video ads for social media without spending hours on manual design, editing, or publishing. What problem is this workflow solving? / Use case Creating video ads usually requires multiple tools and a lot of time: writing scripts, designing product visuals, editing videos, and publishing them across platforms. This workflow automates the entire pipeline — from idea to ready-to-publish ad video — ensuring brands can quickly test campaigns and boost engagement without production delays. What this workflow does 1. Generates ad ideas from Telegram input (text + product image). 2. Creates product visuals using multiple AI image engines: Seedream 4.0 (realistic visuals) NanoBanana (image editing & enhancement) ChatGPT Image / GPT-4o (creative variations) 3. Produces cinematic video ads with Veo 3 based on AI-generated scripts. 4. Merges multiple short clips into a polished final ad. 5. Publishes automatically to multiple platforms (TikTok, Instagram, LinkedIn, X, Threads, Facebook, Pinterest, Bluesky, YouTube) via Blotato. 6. Stores metadata and results in Google Sheets & Google Drive for easy tracking. 7. Notifies you via Telegram with the video link and copy. Setup 1. Connect your accounts in n8n: Telegram API (for input and notifications) Google Drive + Google Sheets (storage & tracking) Kie AI API (Seedream + Veo 3) Fal.ai API (NanoBanana + video merging) OpenAI (for script and prompt generation) Blotato API (for social publishing) 2. Prepare a Google Sheet with brand info and settings (product name, category, features, offer, website URL). 3. Deploy the workflow and connect your Telegram bot to start sending ad ideas (photo + caption). 4. Run the workflow — it will automatically generate images, create videos, and publish to your chosen channels. How to customize this workflow to your needs Brand customization: Adjust the Google Sheet values to reflect your brand’s offers and product features. Platforms: Enable/disable specific Blotato nodes depending on which platforms you want to publish to. Video style: Edit the AI agent’s system prompt to control tone, format, and transitions (cinematic, playful, modern, etc.). Notifications: Adapt Telegram nodes to send updates to different team members or channels. Storage: Change the Google Drive folder IDs to store generated videos and images in your preferred location. This workflow lets you go from idea → images → cinematic ad video → auto-published content in minutes, fully automated. --- Watch This Tutorial: Step by Step --- Documentation: Notion Guide --- Need help customizing? Contact me for consulting and support : Linkedin / Youtube
by Dr. FirasUse the n8n Data Tables feature to store, retrieve, and analyze survey results — then let OpenAI automatically recommend the most relevant course for each respondent. --- What this workflow does This workflow demonstrates how to use n8n’s built-in Data Tables to create an internal recommendation system powered by AI. It: Collects survey responses through a Form Trigger Saves responses to a Data Table called Survey Responses Fetches a list of available courses from another Data Table called Courses Passes both Data Tables into an OpenAI Chat Agent, which selects the most relevant course Returns a structured recommendation with: course: the course title reasoning: why it was selected > Trigger: Form submission (manual or public link) --- Who it’s for Perfect for educators, training managers, or anyone wanting to use n8n Data Tables as a lightweight internal database — ideal for AI-driven recommendations, onboarding workflows, or content personalization. --- How to set it up 1 Create your n8n Data Tables This workflow uses two Data Tables — both created directly inside n8n. Table 1: Survey Responses Columns: Name Q1 — Where did you learn about n8n? Q2 — What is your experience with n8n? Q3 — What kind of automations do you need help with? To create: 1. Add a Data Table node to your workflow. 2. From the list, click “Create New Data Table.” 3. Name it Survey Responses and add the columns above. --- Table 2: Courses Columns: Course Description To create: 1. Add another Data Table node. 2. Click “Create New Data Table.” 3. Name it Courses and create the columns above. 4. Copy course data from this Google Sheet: https://docs.google.com/spreadsheets/d/1Y0Q0CnqN0w47c5nCpbA1O3sn0mQaKXPhql2Bc1UeiFY/edit?usp=sharing This Courses Data Table is where you’ll store all available learning paths or programs for the AI to compare against survey inputs. --- 2 Connect OpenAI 1. Go to OpenAI Platform 2. Create an API key 3. In n8n, open Credentials → OpenAI API and paste your key 4. The workflow uses the gpt-4.1-mini model via the LangChain integration --- Key Nodes Used | Node | Purpose | n8n Feature | |------|----------|-------------| | Form Trigger | Collect survey responses | Forms | | Data Table (Upsert) | Stores results in Survey Responses | Data Tables | | Data Table (Get) | Retrieves Courses | Data Tables | | Aggregate + Set | Combines and formats table data | Core nodes | | OpenAI Chat Model (LangChain Agent) | Analyzes responses and courses | AI | | Structured Output Parser | Returns structured JSON output | LangChain | --- Tips for customization Add more Data Table columns (e.g., email, department, experience years) Use another Data Table to store AI recommendations or performance results Modify the Agent system message to customize how AI chooses courses Send recommendations via Email, Slack, or Google Sheets --- Why Data Tables? This workflow shows how n8n’s Data Tables can act as your internal database: Create and manage tables directly inside n8n No external integrations needed Store structured data for AI prompts Share tables across multiple workflows All user data and course content are stored securely and natively in n8n Cloud or Self-Hosted environments. --- Contact Need help customizing this (e.g., expanding Data Tables, connecting multiple surveys, or automating follow-ups)? robert@ynteractive.com Robert Breen ynteractive.com
by Robert BreenDaily Crypto AI Market Insight to Telegram This workflow generates a daily AI-powered crypto market insight and sends it to Telegram using Binance public market data, the Crypto Fear & Greed Index, and Google Gemini. It fetches BTC/USDT daily OHLCV data, calculates technical indicators, builds a structured analysis payload, asks Gemini for a buy/hold/sell confidence breakdown, and delivers the result as a clean Telegram report. It is useful for traders, builders, and crypto enthusiasts who want an automated daily technical summary without manually checking charts. Common use cases: Send a daily BTC market insight to your Telegram Monitor crypto technical indicators automatically Build a personal AI crypto analyst bot Create a lightweight daily trading signal workflow Learn how to combine market data, technical indicators, LLMs, and Telegram in n8n How it works Starts from a Schedule Trigger, which you can customize Sets the trading pair, for example BTCUSDT Fetches 300 daily OHLCV candles from Binance public API Normalizes Binance candle data into readable fields Fetches the latest market price and merges it into the latest candle Fetches the Crypto Fear & Greed Index from Alternative.me Calculates EMA(20), EMA(50), EMA(100), RSI(14), MACD histogram, ADX(14), +DI, and -DI Builds a structured technical payload Sends the payload to Google Gemini Parses Gemini’s response into structured JSON Formats the result into a Telegram message Sends the AI-generated insight to Telegram Setup steps Choose your trading pair in the Set Trading Pair node Connect your Google Gemini credentials Connect your Telegram credentials Set your Telegram chat ID in the Telegram node Adjust the Schedule Trigger if you want a different run time Test the workflow manually Activate the workflow Notes This workflow uses Binance public API data and does not require a Binance API key. The AI insight is generated only from the provided technical payload and should not be treated as financial advice. Need Help? Have questions or want to connect? Reach me on LinkedIn.
by Atha Ahsan Xavier Haris