Workflow Templates

This workflow pulls deals from Pipedrive, categorizes them by stage, and logs them into a Google Sheet for reporting and tracking. ⚙️ Setup Instructions 1️⃣ Connect Pipedrive In Pipedrive → Personal preferences → API → copy your API token URL shortcut: https://{your-company}.pipedrive.com/settings/personal/api In n8n → Credentials → New → Pipedrive API Company domain: {your-company} (the subdomain in your Pipedrive URL) API Token: paste the token from step 1 → Save In the Pipedrive Tool node, select your Pipedrive credential and (optionally) set filters (e.g., owner, label, created time). 2️⃣ Prepare Your Google Sheet Connect your Data in Google Sheets Use this format: Sample Sheet Row 1 = column names In n8n, create credentials: Google Sheets (OAuth2) Log in with your Google account and select your Spreadsheet + Worksheet 🧠 How it works Get many deals (Pipedrive)**: Fetches all deals with stage IDs. Categorize Stages**: Maps stage IDs → friendly stage names (Prospecting, Qualified, Proposal, Negotiation, Closed Won). Today's Date**: Adds a date stamp to each run. Set Fields**: Combines stage, deal name, and date into clean columns. Google Sheets (Append)**: Writes all rows to your reporting sheet. 📬 Contact Need help customizing this (e.g., pulling only active deals, calculating win-rates, or sending dashboards)? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

Query personal finance data in Notion via Telegram and WhatsApp Who’s it for This workflow is for individuals who track their finances in Notion and want quick answers via chat. Entrepreneurs, freelancers, and professionals can use it to check expenses, income, or budgets instantly without opening Notion. How it works The workflow acts as an Accountant Agent powered by Claude AI through OpenRouter. When you send a query like “Total expenses for August 2025” through Telegram or WhatsApp, the agent identifies the right Notion database, applies filters, and retrieves the requested data. It then replies with a summarized result directly to your phone. How to set up Clone the Personal Finance System Notion template into your workspace. Create a Telegram bot with BotFather and collect the bot token and chat ID. Get an API key from OpenRouter. Create a Notion integration token and connect it with your duplicated finance template. Set up WhatsApp Business credentials via Meta (WABA ID, Phone Number ID, and permanent access token). Requirements n8n instance (self-hosted or cloud) Accounts on Telegram, OpenRouter, Notion, and WhatsApp Business Your duplicated Personal Finance System Notion template How to customize the workflow You can extend the workflow to handle assets, liabilities, or budgets. Add more Notion databases, adjust query filters, or configure WhatsApp templates for automated financial updates.

🚀 Telegram Google Trends Bot Workflow This workflow creates a powerful, multi-country Google Trends bot on Telegram. Users can request the top trending search queries for any country by simply sending its two-letter country code (e.g., EG, US, SA). The bot fetches the latest data, formats it into a clean report, and sends it back to the chat. ✨ Key Features 🌍 Dynamic Country Selection:** Get trends for any country on the fly by providing its geo code 📡 Automated RSS Fetching:** Pulls the latest data directly from Google's official daily trends RSS feed 📊 Clean, Formatted Reports:** Uses a custom code node to generate a beautiful, Markdown-formatted message that is easy to read on mobile 📈 Rich Information:** Each trend includes: 🔍 The search query title 📊 Approximate search traffic volume (e.g., "20K+ searches") 📰 Links to the top 2 related news articles, complete with their sources 🌟 Optimized for Arabic:** The report headers and labels are in Arabic, making it perfect for users in the MENA region, but can be easily adapted ⚙️ How It Works 💬 Telegram Trigger: A user sends a message containing a two-letter country code (e.g., EG) 🌐 HTTP Request: The workflow uses this code as the geo parameter in a request to the trends.google.com/trending/rss endpoint 📄 XML Parser: The native XML node converts the raw RSS feed data into a structured JSON format 💻 Code (Format Report): A JavaScript function processes the JSON data. It extracts the top 5 trends, formats the titles, traffic, and news items, and constructs the final Markdown text for the report 📤 Send to Telegram: The final, formatted report is sent back to the user who requested it 🛠️ Setup 🔐 Telegram Credentials: Add your Telegram API credentials to the Telegram Trigger and Send a text message nodes 🌐 (Optional) Customize Language: The text and labels in the Code node can be easily translated to any language you prefer

📄 What this workflow does Every 3 hours, the workflow fetches 3 random English words, asks Gemini to generate a short Vietnamese vocabulary digest (word, Vietnamese meaning, and an example sentence), and sends it to a Telegram chat. Perfect for steady, low-effort vocab exposure in groups. 👤 Who is this for English learners who want a gentle, automated learning cadence. Teachers/tutors who share daily vocab in Telegram groups. Community admins who want lightweight, useful content for members. Anyone who prefers bite-sized language learning on autopilot. ✅ Requirements Gemini API access (configured in n8n). Telegram Bot token + chat ID (the chat you want to receive messages). Internet access to Random Word API (no API key required). n8n instance with outbound HTTPS access. ⚙️ How to set up Add your Gemini credentials in n8n (the Google Gemini/PaLM node). Add your Telegram credentials and set the chatId in the “Send a text message” node. (Optional) Adjust the schedule interval (default: every 3 hours). (Optional) Change the number of words by updating the HTTP Request URL param words=3. (Optional) Edit the Gemini prompt language/content to fit your style (currently Vietnamese output). Run once to test; confirm the message arrives in Telegram. 🔁 How it works Schedule Trigger → runs every 3 hours. HTTP Request → calls random-word-api to get 3 words. Edit Fields (Set) → wraps the API response under word. Aggregate → prepares the word field for the LLM. Message a model (Gemini) → creates a Vietnamese digest: English word, Vietnamese meaning, and example sentence for each word. Send a text message (Telegram) → posts the digest to your specified chat. 💡 About Margin AI Margin AI is an AI-services agency that acts as your AI Service Companion. We design intelligent, human-centric automation solutions—turning your team’s best practices into scalable, automated workflows and tools. Industries like marketing, sales, and operations benefit from our tailored AI consulting, automation tools, chatbot development, and more.

Automated TikTok Real Estate Research for Couples This workflow automates the process of finding real estate (rental) videos on TikTok, filtering them for a specific target audience (couples in their 20s), generating an explanation of why they are recommended, and saving the results to Google Sheets and Slack. Who’s it for Real Estate Agents & Marketers:** To research trending rental properties and video styles popular on social media. Content Curators:** To automatically gather and summarize niche content from TikTok. House Hunters:** To automate the search for "rental" videos tailored to couples. How it works / What it does Trigger: The workflow starts manually (on click). Scrape TikTok: It connects to Apify to run a "TikTok Scraper". It searches for videos with the hashtag 賃貸 (Rental) and retrieves metadata. Filter & Extract (AI Agent 1): An AI Agent (using OpenRouter) analyzes the retrieved video data to select properties suitable for "couples in their 20s" and outputs the video URL. Generate Insights (AI Agent 2): A second AI Agent reviews the URL/content and generates a specific reason why this property is recommended for the target audience, formatting the output with the URL and explanation. Save to Database: The final text (URL + Reason) is appended to a Google Sheet. Notify Team: The same recommendation text is sent to a specific Slack channel to alert the user. Requirements n8n:** Version 1.0 or later. Apify Account:** You need an API token and access to the clockworks/tiktok-scraper actor. OpenRouter Account:** An API Key to use Large Language Models (LLMs) for the AI Agents. Google Cloud Platform:** A project with the Google Sheets API enabled and OAuth credentials. Slack Workspace:** Permission to add apps/bots to a channel. How to set up Import the Workflow: Copy the JSON code and paste it into your n8n editor. Configure Credentials: Apify: Create a new credential in n8n using your Apify API Token. OpenRouter: Create a new credential using your OpenRouter API Key. Google Sheets: Connect your Google account via OAuth2. Slack: Connect your Slack account via OAuth2. Configure Nodes: Google Sheets Node: Select your specific Spreadsheet and Sheet from the dropdown lists (replace the placeholders YOUR_SPREADSHEET_ID etc. if they don't update automatically). Slack Node: Select the Channel where you want to receive notifications (replace YOUR_CHANNEL_ID). Test: Click "Execute Workflow" to run a test. How to customize the workflow Change the Search Topic:* Open the *Apify** node and change the hashtags value in the "Custom Body" JSON (e.g., change "賃貸" to "DIY" or "Travel"). Adjust the Persona:* Open the *AI Agent** nodes and modify the text prompt. You can change the target audience from "20s couples" to "students" or "families." Increase Volume:* In the *Apify** node, increase the resultsPerPage or maxProfilesPerQuery to process more videos at once (note: this will consume more API credits). Change Output Format:* Modify the *Google Sheets** node to map specific fields (like Video Title, Author, Likes) into separate columns instead of just one raw output string.

Who it’s for This workflow is for content creators and marketers who write short scripts in Google Sheets and want to automatically turn each line into an AI-generated avatar video stored in Google Drive, with links written back to the sheet. How it works A Manual Trigger starts the workflow. It first uses Get Avatar Description (Google Sheets) to read avatar details from a dedicated “Gaia” sheet. The Global Variables node sets the working script page (for example, “Draft 5”) and exposes the avatar description. Next, Get Script reads all rows from the selected sheet. Loop Over Items iterates through each row, while Set Loop Inputs prepares the variables: avatar description, speech, and framing. For every row, Generate a video with Veo (Google Gemini video model) creates an 8-second 16:9 clip. Upload video file saves it to a chosen Google Drive folder, and Update row in sheet with link to video writes the Drive link back into the same row, then loops to the next snippet. Yellow sticky notes explain each phase, with the large one summarizing the end-to-end snippet generation loop. How to set up Connect your Google Sheets and Google Drive credentials. Update the spreadsheet IDs, sheet names, and Drive folder to match your own. Configure the Gemini/Veo model credentials. Adjust the default script page name in Global Variables. Requirements n8n instance Google Sheets and Google Drive accounts Google Gemini / Veo API access No API keys or personal identifiers are hardcoded; always store credentials securely in n8n and avoid real PII in test data. How to customize Change the page value in Global Variables to target different script tabs. Edit the Veo prompt to alter background, camera framing, or speaking style. Modify video duration, aspect ratio, or output folder in the Gemini and Drive nodes. Extend the loop to add more post-processing steps (e.g., thumbnail generation, analytics tracking).

This workflow automatically enriches company domain lists with comprehensive business information using Perplexity AI's research capabilities and organizes the data in Google Sheets for easy analysis and use. Who's it for Sales teams** building prospect databases with accurate contact information Marketing professionals** researching target companies for campaigns Business development teams** gathering competitive intelligence Data analysts** enriching existing company datasets Researchers** collecting business information for market analysis How it works The workflow reads unprocessed company domains from a Google Sheets document, processes them in batches of 10 using Perplexity AI to research detailed business information, then saves the enriched data back to the spreadsheet. It focuses on German addresses but can be customized for any region. What it does Fetches unprocessed domains - Reads company domains from Google Sheets that haven't been processed yet Batches for efficiency - Groups domains into batches of 10 to optimize API costs and performance AI-powered research - Uses Perplexity AI to find comprehensive business data for each company Parses structured data - Converts AI responses into clean, structured JSON format Updates spreadsheet - Saves enriched data and marks domains as processed to prevent duplicates Requirements Perplexity AI API key** (Get one here) Google Sheets API access** (OAuth2 credentials) Google Sheets template** - Make a copy of this template How to set up Make a copy of the template Google Sheet and update the document ID in both Google Sheets nodes Configure Perplexity AI credentials in the HTTP Request node Set up Google Sheets OAuth2 authentication Add your company domains to the "domain" column in the Data tab Leave the "processed" column empty for new domains Run the workflow using the manual trigger How to customize the workflow Change target region**: Modify the AI prompt to research addresses in different countries Adjust batch size**: Change the batch size in the "Batch Process Domains" node (smaller batches = lower costs) Add custom fields**: Extend the AI prompt and Google Sheets mapping to include additional data points Automate execution**: Replace Manual Trigger with Schedule Trigger for regular processing Filter criteria**: Modify the Google Sheets filter to process specific subsets of domains Output data includes Complete company address (street, city, state, postal code, country) International phone number format Latest employee count and annual revenue (USD) Industry classification LinkedIn company URL Reliable source URL for verification Processing status tracking

⚡ Overview This workflow connects Telegram with an AI Agent (Gemini) and Notion to automate content requests. Team members can request content ideas directly in Telegram. The AI processes the request, then automatically creates a new entry in your Notion Content database. 🛠️ Features 🤖 AI-powered assistant: Gemini AI with memory to understand context and generate better responses. 📲 Telegram integration: Accepts requests directly from your Telegram bot. 🗂️ Notion automation: Auto-creates records in your Notion database (title, content draft, channel, assignee, date, references, type). 🛡️ Secure & flexible: No hardcoded API keys, placeholders used for easy setup. 📝 Setup Instructions Add your Telegram Bot Token, Google Gemini API Key, and Notion Integration Token in n8n credentials. Steps: Import this template JSON into your n8n instance. Configure credentials in n8n (Telegram, Notion, Gemini API). 🎯 Use Cases Content marketing teams managing requests via Telegram. Automating idea collection from distributed teams. Keeping Notion Content updated without manual entry.

Teach your AI agent HOW to think, not WHAT to think This workflow demonstrates how you can build an AI agent in n8n that uses the reasoning logic you define. So an LLM learns a way of thinking, which you can then apply to multiple problems: Make an AI chatbot that knows how to convince anybody using the "Getting to Yes" method Build an LLM workflow that uses Ray Dalio's principles to spot investment opportunities Create an AI agent crew of interdisciplinary thinkers: e.g. a specialist in psychology who gives an advice on education programmes. How it works This template uses the n8n AI agent node as an orchestrating agent that has access to a certain reasoning logic defined by an InfraNodus knowledge graph. This graph contains a list of reasoning rules (ontology), which is extracted to provide an advice that is relevant to the original prompt. It uses GraphRAG under the hood to traverse the parts of the graph relevant to the query. This advice and the reasoning logic extracted is then used by the AI agent to generate a response that is relevant to the user's query but that uses the reasoning logic provided through the graph. Here's a description step by step: The user submits a question using the AI chatbot (n8n interface, in this case, a web form that can be embedded to any website, or a webhook that can be connected to a Telegram / WhatsApp bot) The AI agent node accesses the Reasoning Logic HTTP InfraNodus nodes. The description of AI agent and the description of the reasoning InfraNodus node provides the agent with an understanding of how to rephrase the original question to retrieve relevant reasoning logic. The request is sent to the InfraNodus node. It provides a response that contains the reasoning logic needed to answer the question. This reasoning logic is then sent back to an LLM along with the original query to produce the response. InfraNodus uses GraphRAG under the hood: convert user query into graph find the overlap with the reasoning graph (using n=1 or more hops to include more relations) use similarity search to get additional parts of the graph generate a response based on this intersection as well as the context provided provide information about the underlying structure How to use You need an InfraNodus account to use this workflow. Create an InfraNodus account Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Create a separate knowledge graph for the reasoning logic Use the AI ontology creator to generate an ontology for a certain topic or text using AI. Then augment it with your own data. See our help article on creating ontologies for detailed instructions For each graph, go to the workflow, paste the name of the graph into the request JSON body name field. Change the system prompt in the AI agent node to reflect the nature of your reasoning logic. For instance, if it's an expert in interactions, you specify that, if it's a psychology expert, you need to specify that as well. Change the description of the reasoning node (HTTP tool). Use the InfraNodus summary and Project Notes > RAG prompt buttons to generate a description for the reasoning logic, which you can then reuse in your workflow. add the LLM key to the OpenAI node (or to the model of your choice) and launch the workflow Requirements An InfraNodus account and API key An OpenAI (or any other LLM) API key Customizing this workflow You can use this same workflow with a Telegram bot, so you can interact with it using Telegram. There are many more customizations available. Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/21429518472988-Using-Knowledge-Graphs-as-Reasoning-Experts Also check out the video tutorial with a demo:

⚡ Next-Gen Customer Support: Two-Way WhatsApp + Telegram Integration for 10k+ Clients Who is this workflow for This workflow is designed for **customer support teams, e-commerce founders, and operations managers** who want to handle thousands of customer queries seamlessly. Instead of building a brand-new chat application, it leverages WhatsApp (where customers already are) and Telegram (where your support team operates) to create a scalable, topic-based support system. If you are a brand handling 1000s of daily WhatsApp customer messages and need a structured way to map each customer into a dedicated support thread without chaos, this workflow is for you. What it does / How it works This two-way n8n automation bridges WhatsApp and Telegram by creating one Telegram forum topic per customer and syncing messages both ways: Incoming WhatsApp → Telegram When a new WhatsApp message arrives, the workflow checks if the customer already has a topic in Telegram. If yes → The message is forwarded into that existing topic. If no → A new topic is created automatically, the mapping is saved in the database, and the message is posted there. Result: every customer has a dedicated thread in your Telegram supergroup. Outgoing Telegram → WhatsApp When a support agent replies in a Telegram topic, the workflow looks up the linked WhatsApp number. The reply is sent back to the customer on WhatsApp, preserving context. Result: two-way synced conversations without building a custom app. How to set it up Configure WhatsApp Cloud API Create a Meta Developer account and register a WhatsApp Business number. Generate an access token and phone number ID. Configure Telegram Bot Use BotFather to create a bot and enable it in a **Telegram Supergroup with Topics**. Get the chat_id and allow the bot to create/send messages in topics. Database (Supabase/Postgres) Create a table wa_tg_threads to map phone_e164 ↔ telegram_topic_id ↔ supergroup_id. n8n Workflows Workflow A: WhatsApp → Telegram Trigger: WhatsApp Webhook Steps: Lookup customer → If exists send to topic, else create topic → Save mapping → Forward message. Workflow B: Telegram → WhatsApp Trigger: Telegram Webhook Steps: Filter only topic replies → Lookup mapping → Send WhatsApp message. Testing Send a WhatsApp message → Check Telegram topic created. Reply in Telegram topic → Ensure customer receives WhatsApp reply. Requirements A free or paid n8n instance (self-hosted or cloud). WhatsApp Cloud API credentials** (phone number ID + access token). Telegram Bot token* with access to a *Supergroup with Topics** enabled. A Postgres/Supabase database to store thread mappings. Basic familiarity with editing HTTP Request nodes in n8n. How to customize the workflow Brand personalization:** Pre-populate first message templates (thank you, order status, delivery updates). Routing rules:** Assign specific agents to certain topics by ID ranges. Integrations:** Extend to CRMs (HubSpot, Zoho) or support platforms (Freshdesk, Zendesk). Notifications:** Push high-priority WhatsApp queries into Slack/Teams for instant alerts. Archival:** Auto-close inactive topics after N days and mark customers as dormant. Why Telegram instead of building a new App The client's requirement was clear: **use an existing, reliable, and scalable chat platform** instead of building a new app from scratch. Telegram Supergroups with Topics** scale to 100,000+ members and millions of messages, making them ideal for managing 10k+ customer threads. Agents don't need to install or learn a new tool---they continue inside Telegram, which is fast, free, and mobile-friendly. Building a custom chat app would require authentication, push notifications, scaling infra, and UX---all solved instantly by Telegram. This decision **saves development cost, accelerates deployment, and provides proven scalability**. Why this improves support productivity Organized by customer:** Each WhatsApp number has its own Telegram topic. No missed messages:** Agents can quickly scroll topics without drowning in one endless chat. Two-way sync:** Replies flow back to WhatsApp seamlessly. Scales automatically:** Handle 10k+ conversations without losing track. Leverages existing tools:** WhatsApp (customers) + Telegram (agents). Result: **faster responses, better tracking, and zero need to reinvent chat software.**

Transform your Telegram bot into a secure content analyzer: send any URL, and get safe, structured Q&A extractions with AI-powered safety checks and web search capabilities. 📋 What This Template Does This workflow activates when a user sends a valid URL to your Telegram bot. It extracts questions and answers from the webpage using Airtop, applies NSFW and PII guardrails to ensure safe content, then uses an OpenRouter AI agent (with optional Tavily search) to generate and send a concise response. If guardrails fail, it alerts the user instead. Filters for valid URLs only to prevent unnecessary processing Extracts structured Q&A from documents or forms Enforces safety checks for harmful or private content Supports web searches for enhanced responses when needed 🔧 Prerequisites A Telegram bot created via @BotFather Accounts with Airtop, OpenRouter, and Tavily 🔑 Required Credentials Telegram API Setup Open Telegram → Search @BotFather → Use /newbot command Follow prompts to create bot and obtain API token Add to n8n as Telegram API credential type Airtop API Setup Visit https://airtop.ai → Sign up or log in → Navigate to Dashboard → API Keys Generate a new API key with extraction permissions Add to n8n as Airtop API credential type OpenRouter API Setup Go to https://openrouter.ai → Sign up or log in → Navigate to API Keys section Generate and copy your API key (free tier sufficient for basic use) Add to n8n as OpenRouter API credential type Tavily API Setup Visit https://app.tavily.com → Sign up or log in → Go to API Keys Generate and copy your API key Add to n8n as Tavily API credential type ⚙️ Configuration Steps Import the workflow JSON into n8n Assign your Telegram, Airtop, OpenRouter, and Tavily credentials to the respective nodes Activate the workflow to register the Telegram trigger Test by sending a plain URL (no extra text) to your bot in Telegram Monitor the first execution and adjust guardrail thresholds if needed 🎯 Use Cases Researchers summarizing academic papers or reports while ensuring no sensitive data leaks Support teams extracting info from customer-submitted docs/forms with automatic safety filtering Content creators pulling Q&A from articles for bots, blocking inappropriate responses Educators analyzing educational resources safely for student-facing chat tools ⚠️ Troubleshooting No response from bot: Verify the message contains only a valid URL; adjust regex in Filter Only URLs node if needed Guardrail failures: Lower NSFW threshold (e.g., from 0.7 to 0.5) or disable PII checks in Apply Safety Guardrails node Extraction errors: Test with public, text-heavy URLs; some JS-heavy sites may require alternative extractors Rate limits hit: Check OpenRouter/Tavily dashboards for usage; upgrade to paid tiers for heavy traffic

Advanced Code Review Automation (AI + Lint + Slack) Who’s it for For software engineers, QA teams, and tech leads who want to automate intelligent code reviews with both AI-driven suggestions and rule-based linting — all managed in Google Sheets with instant Slack summaries. How it works This workflow performs a two-layer review system: Lint Check: Runs a lightweight static analysis to find common issues (e.g., use of var, console.log, unbalanced braces). AI Review: Sends valid code to Gemini AI, which provides human-like review feedback with severity classification (Critical, Major, Minor) and visual highlights (red/orange tags). Formatter: Combines lint and AI results, calculating an overall score (0–10). Aggregator: Summarizes results for quick comparison. Google Sheets Writer: Appends results to your review log. Slack Notification: Posts a concise summary (e.g., number of issues and average score) to your team’s channel. How to set up Connect Google Sheets and Slack credentials in n8n. Replace placeholders (<YOUR_SPREADSHEET_ID>, <YOUR_SHEET_GID_OR_NAME>, <YOUR_SLACK_CHANNEL_ID>). Adjust the AI review prompt or lint rules as needed. Activate the workflow — reviews will start automatically whenever new code is added to the sheet. Requirements Google Sheets and Slack integrations enabled A configured AI node (Gemini, OpenAI, or compatible) Proper permissions to write to your target Google Sheet How to customize Add more linting rules (naming conventions, spacing, forbidden APIs) Extend the AI prompt for project-specific guidelines Customize the Slack message formatting Export analytics to a dashboard (e.g., Notion or Data Studio) Why it’s valuable This workflow brings realistic, team-oriented AI-assisted code review to n8n — combining the speed of automated linting with the nuance of human-style feedback. It saves time, improves code quality, and keeps your team’s review history transparent and centralized.