Workflow Templates

🔍 Workflow Overview What This Workflow Does This workflow automatically saves copies of all your Notion databases to Google Drive. It's like creating a safety backup of your important Notion information, similar to saving important documents in a filing cabinet. Target Audience: Anyone who uses Notion and wants to protect their data by creating automatic backups to Google Drive. Prerequisites (What You Need Before Starting) Required Accounts Notion Account - Where your databases are stored Google Account - For Google Drive storage Telegram Account - To receive backup notifications (free messaging app) Required Software n8n Community Edition v2.0.0** installed on your computer or server Web browser** (Chrome, Firefox, Safari, or Edge) Step-by-Step Configuration Guide PART 1: Setting Up Notion Access Step 1: Create a Notion Integration Step 2: Share Your Databases with the integration PART 2: Setting Up Google Drive Access Step 1: Create a Google Drive Folder Step 2: Connect Google Drive to n8n PART 3: Setting Up Telegram Notifications Step 1: Create a Telegram Bot Step 2: Get Your Chat ID Step 3: Connect Telegram to n8n PART 4: Installing the Workflow in n8n Step 1: Import the Workflow Step 2: Configure Credentials For Notion nodes (Get All Databases, Get Database Pages) For Google Drive nodes (Create Backup Folder, Upload Backup File, etc.) For Telegram node (Send Telegram Notification) Step 3: Configure the Workflow Settings PART 5: Testing Your Workflow Step 1: Run a Test Step 2: Verify the Backup If Something Goes Wrong Red X marks on nodes**: Check that all credentials are properly connected "Not found" errors**: Make sure you shared your Notion databases with the integration No Telegram message**: Verify your Chat ID is correct No files in Google Drive**: Check your Folder ID is correct

🧠 AI Telegram Customer Support Assistant + Lead Manager This n8n workflow provides a fully automated AI-driven customer support assistant connected to Telegram, with built-in lead management, knowledge-base querying, and context-aware answers. ⭐ What this workflow does Receives user messages from Telegram Logs all incoming/outgoing messages into a Data Table Checks if a lead exists for the user (via chat_id) Creates new leads automatically if needed Builds an AI-ready context (user info + lead info + latest message) Uses the AI Agent to answer questions using: FAQ database Services table (programs, prices, descriptions) Settings table (agency info) Lead update tool Sends a natural, friendly reply back to Telegram Updates leads in real time (name, phone, email, notes…) 📦 Required Data Tables (to be created by the user) leads Stores all user information (full_name, phone, email, etc.) services List of available programs/services with prices, duration, category. faq Frequently asked questions with answers and optional tags. settings Company/agency details used by the assistant. chat_logs Logs all messages exchanged with users (user + bot). 🔧 Required Credentials Telegram Bot API Key AI Model Credential (OpenAI, OpenRouter, Groq…) No other credentials required. 🚀 How to use it Import the workflow into your n8n instance Create the required Data Tables as defined inside the Sticky Notes Add your credentials (Telegram + AI Model) Customize the prompt to match your business Activate the workflow — you're ready to go! 💡 Suitable for: Travel agencies Customer support chatbots Lead qualification + automation AI knowledge-based assistants Telegram-first businesses

Automatically Import Research Papers using DOI URL from Telegram to Zotero This workflow allows you to automatically import research papers into your Zotero library by simply sending a DOI link through Telegram. It fetches metadata from reliable sources such as Crossref, DataCite, and Unpaywall, enriches the bibliographic details, attaches the best available full-text PDF when possible, and generates a concise summary of the abstract using an LLM before sending it back to Telegram. ✨ Key Features Telegram Integration** – Send a DOI link via Telegram bot to trigger the workflow. DOI Parsing** – Automatically detects and extracts DOI or arXiv identifiers from user messages. Metadata Fetching* – Retrieves bibliographic information from *Crossref, **DataCite, and Unpaywall. Smart PDF Finder** – Locates the best available PDF (publisher link, open access, or arXiv). Zotero Integration** – Creates a Zotero parent item with complete metadata and attaches the PDF link when available. Abstract Summarization** – Uses a basic LLM chain to generate a short and clear summary of the abstract. Telegram Feedback** – Sends the title, URL, and abstract summary back to the user in Telegram. 🔑 Required Credentials Telegram API** – To connect the workflow with your Telegram bot. Zotero API Key** – To create and update items in your Zotero library. OpenRouter API Key** – To enable the LLM for generating abstract summaries. (Optional) Email for Unpaywall API requests (recommended for stable access). 💡 Benefits Save time by automating manual research paper imports. Ensure high-quality metadata by combining multiple sources (Crossref, DataCite, Unpaywall). Get instant summaries of abstracts directly in Telegram for quick understanding. Keep your Zotero library organized with accurate titles, abstracts, authors, and tags. Quickly attach available full-text PDFs without manual searching. Improve your academic workflow by managing references and summaries directly from Telegram.

The problem Ever attend a networking event and find yourself taking screenshots of people's LinkedIn? Sounds counter-intuitive because you are connecting on LinkedIn. But you find it hard to keep track of everyone you've met. You also don't want to miss diligently updating your CRM with details and insights. *The solution * There's no need for yet another app. Continue taking screenshots. Just share them on a 2-field only Google Form: screenshot + your quick notes about the person. Create a shortcut to the Google Form link on your phone homescreen. Voila! You have app-like access without the need for an app. Once you submit with just these 2 pieces of info, AI parses the image AND crafts a follow-up message. Within minutes! Just open your spreadsheet to have all that information consolidated - automatically - for your review. Promote yourself from do-er to manager. Who should use it? Anyone really. If you find yourself meeting people but want to be more meticulous or efficient staying on top, use this. How to set it up Time: ~10 minutes end-to-end. Import the provided workflow JSON in n8n. Connect credentials: Google Drive (read), Google Sheets (write), OpenAI. Configure key information: Google Sheets and relevant columns Configure Open AI models based on your cost/ efficiency requirements Confirm column headers in your Sheet match the variables (or update the variables). Test with one screenshot. Pro-tip: Add that Google Form link as a shortcut on your phone's home screen. Get app-like convenience without downloading yet another app.

🛠️ Landing-Page Roast & CRO Ideas Bot – Quick Guide What this workflow does Takes any public landing-page URL. Scrapes the page content. Uses Gemini 2.5-pro to • Roast the page (friendly but brutally honest) • Give 10 high-impact, 2024-ready CRO ideas – all in Turkish, max 3 000 characters. Sends the result back to you on Telegram. Two ways to trigger it Web form • Open the form titled “Conversion Rate Optimizer.” • Paste your landing-page URL(with https or http in front of it). • Click Submit. Telegram (fastest) • Send the URL in a DM to @MertSiteRaporBot. • Forgot the “https://”? No worries—the bot adds it automatically. Behind the scenes • Code node normalises the URL. • HTTP Request scrapes the page HTML. • AI Agent (Gemini) produces the Roast + Recommendations. • Telegram node sends the formatted reply to you. Usage tips • One URL per request. • Page must be publicly accessible (no login). • Very long pages may be trimmed to fit model limits. • Output language is always Turkish.

Try It Out! This workflow builds a Telegram-based Solana (SOL/USDT) Multi-Timeframe AI Market Analyzer that automatically pulls live candlestick data for SOL/USDT, runs structured multi-timeframe technical analysis (1-minute, 5-minute, 1-hour) through an AI Agent, and posts a professional, JSON-structured analysis + trading recommendation straight to your Telegram chat. It combines on-chain / market data aggregation, LLM-driven interpretation, and instant Telegram reporting — giving you concise, actionable market intelligence every hour. How It Works Hourly Trigger – The workflow runs once per hour to pull fresh market data. Market Data Fetch – Three HTTP requests gather candlesticks from CryptoCompare: 1-minute (last 60 candles) 5-minute aggregate (last 60 aggregated candles) 1-hour (last 60 candles) Merge & Transcribe – The three feeds are merged and a lightweight code node extracts: symbol, current price, arrays for data_1m, data_5m, data_1h. AI Agent Analysis – The LLM (configured via your model node) receives the merged payload and runs a structured multi-timeframe technical analysis, returning a strict JSON report containing: Per-timeframe analysis (momentum, volume, S/R,MA, volatility) Market structure / confluence findings Trading recommendation (action, entry, stop, TPs, position sizing) A final disclaimer Parse AI Output – Extracts the JSON block from the agent’s reply and validates/parses it for downstream formatting. Telegram Reporting – Sends two nicely formatted Telegram messages: Multi-timeframe breakdown (1m / 5m / 1h) Market structure + Trading Recommendation (TPs, SL, position size, disclaimer) How to Use Import the workflow into your n8n workspace (or replicate the nodes shown in the JSON). Add credentials: CryptoCompare API Key — for reliable candlestick data. LLM model credentials — e.g., Google Gemini / OpenAI, configured in the LangChain/LM node. Telegram Bot Token & Chat ID — to send messages. (Optional) AFK Crypto API key if you want to enrich data with wallet info later. Node mapping & endpoints: Fetch_1m → GET https://min-api.cryptocompare.com/data/v2/histominute?fsym=SOL&tsym=USDT&limit=60 Fetch_5m → GET https://min-api.cryptocompare.com/data/v2/histominute?fsym=SOL&tsym=USDT&limit=60&aggregate=5 Fetch_1h → GET https://min-api.cryptocompare.com/data/v2/histohour?fsym=SOL&tsym=USDT&limit=60 Merge → combine the three responses into a single payload. Transcribe (code) → extract last close as current price and attach the arrays. AI Agent → pass the structured prompt (system message instructs exact JSON structure). Parse AI Output → extract the json ... block and JSON.parse it. Telegram nodes → format and send two messages (timeframes and recommendation). Adjust analysis frequency: default is hourly — change the Schedule Trigger node as desired. Deploy and activate: the workflow will post an AI-driven SOL/USDT market analysis to your Telegram hourly. (Optional) Extend This Workflow Add price / orderbook enrichment (e.g., AFK price endpoints or exchange orderbook) to improve context. Add wallet exposure checks (AFK wallet balances) to tailor position sizing suggestions. Store AI reports in Notion / Google Sheets for historical auditing and backtesting. Add alert filtering to only post when the LLM flags high-confidence signals or confluence across timeframes. Expose Telegram commands to request on-demand analysis (e.g., /analyze now 5m). Add risk management logic to convert LLM recommendation into automated orders (careful — requires manual review and stronger safety controls). Safety Mechanisms Explicit system prompt — forces AI to output only the exact JSON structure to avoid free-form text parsing errors. JSON parser node — validates the agent response and throws if malformed before any downstream action. Read-only market analysis — the workflow only reports by default (no auto-trading), reducing operational risk. Credentials gated — ensure LLM and Telegram credentials are stored securely in n8n. Disclaimer — every report includes a legal/financial disclaimer from the agent. Requirements CryptoCompare API Key (for minute/hour candlesticks) LLM model credentials (Google Gemini / OpenAI / other supported model in your LangChain node) Telegram Bot Token + Chat ID (where analysis messages are posted) Optional: AFK Crypto API key if you plan to add wallet/position context n8n instance with: HTTP Request, Code, Merge, LangChain/Agent, and Telegram nodes enabled AFK / External APIs Used CryptoCompare Candles: GET https://min-api.cryptocompare.com/data/v2/histominute?fsym=SOL&tsym=USDT&limit=60 (1m) GET https://min-api.cryptocompare.com/data/v2/histominute?fsym=SOL&tsym=USDT&limit=60&aggregate=5 (5m) GET https://min-api.cryptocompare.com/data/v2/histohour?fsym=SOL&tsym=USDT&limit=60 (1h) Telegram Bot API – via n8n Telegram node. LLM / LangChain – your chosen LLM provider (configured in the workflow). Summary The Solana (SOL/USDT) Multi-Timeframe AI Market Analyzer (Telegram) gives you hourly, professional multi-timeframe technical analysis generated by an LLM agent using real candlestick data from CryptoCompare. It combines the speed of automated data collection with the structure and reasoning of an AI analyst, delivering clear trading recommendations and a timestamped analysis to your Telegram chat — ideal for traders who want reliable, concise market intelligence without manual charting. Our Website: https://afkcrypto.com/ Check our blogs: https://www.afkcrypto.com/blog

This workflow bridges the gap between anonymous website traffic and on-chain wallet activity. It captures wallet connections via a webhook, enriches the data with real-time USD balances from the Zerion API, and syncs the results to Google Analytics 4, BigQuery, and Discord for immediate action. This directly helps Web3 marketing and growth teams identify high-value "whales" the moment they connect to your dApp, allowing for real-time monitoring and advanced attribution analysis. How it works Video tutorial: https://youtu.be/2_wuTRzRpkg How it works Webhook Trigger: Receives the wallet address, GA Client ID, and Session ID from your website via GTM. Zerion API Integration: Queries the real-time USD balance and individual chain distributions for the connected wallet. Whale Filtering (Switch): A logic that filters wallets based on a USD threshold (e.g., >$50) to trigger high-priority alerts. Dynamic Discord Alerts: Sends a formatted message to Discord with a 2-decimal rounded total balance and a dynamic breakdown of assets across all active chains (Base, Ethereum, etc.). GA4 Push: Sends the wallet_usd_balance as a custom metric to GA4 via the Measurement Protocol to maintain session continuity. BigQuery Archive: Records the wallet address, hashed ID, and USD balance into a secure table for SQL joining with raw GA4 data Prerequisites Zerion API Key: Required for fetching real-time balance and chain data. Discord Bot Token: Required to send automated whale alerts to your team server. Google Cloud Project: A project with BigQuery enabled and a JSON Service Account key for secure data insertion. GA4 Measurement Protocol API Secret: Required to push custom metrics back into active GA4 sessions.

Task-based Assignee billing via Time Tracking This workflow automates billing by scanning a target Dartboard on schedule, aggregating time logs from completed tasks, cross‑referencing assignee rates in Google Sheets, calculating total pay, and updating the sheet with final billable hours and amounts. Who's it for Individuals, agencies, companies, and project managers automating payroll or client invoicing from task data. How to setup Link your Dart and Google accounts. Replace the dummy ID in the List tasks node with your actual target Dartboard ID. Set your preferred run frequency (e.g., Weekly). Create a Google Sheet with these exact headers: Name, HourlyRate, TotalHours, TotalPay, DateCalculated. Connect the Sheet nodes to your file. Pre-fill Name (matching Dart Assignees exactly) and HourlyRate in your Google Spreadsheet. Optional: Add a last header column in the sheet as a Status header to track if the bill is paid or pending. Customizing the workflow Choose your AI model for your AI time tracking and assignee scanner Use your own google sheet account and target spreadsheet document

Who is this for This workflow is built for tutoring schools, cram schools, and independent teachers who want to offer students 24/7 Q&A support via LINE — Japan's most widely used messaging app. No coding knowledge is required to set it up. What this workflow does When a student sends a question on LINE, an AI Agent (powered by Gemini) reads the conversation history stored in Google Sheets, searches your teaching materials in Google Drive, and replies with a clear explanation directly in LINE. If the agent cannot find a confident answer — for example, the topic is not covered in the materials or the question is too complex — it automatically sends an escalation alert to a designated Slack channel so a teacher can follow up personally. The agent also logs every question and its resolution status to Google Sheets, giving teachers a running record of each student's weak points and question frequency. How to set up Connect your LINE Messaging API credentials in n8n. Create a Google Sheet with columns: student ID, timestamp, question, answer, resolved (yes/no). Upload your teaching materials (PDF or text files) to a Google Drive folder. Set the Drive folder ID and Sheet ID in the Set Fields node. Add your Slack webhook URL for teacher escalation notifications. Activate the workflow and share the LINE bot link with students. Requirements LINE Messaging API channel (free tier works) Google Drive folder with study materials (PDF or .txt) Google Sheets spreadsheet for conversation history and progress tracking Slack incoming webhook URL Gemini API key (free tier available) How to customize You can swap Google Drive for a different file source, adjust the Gemini prompt in the AI Agent node to change the explanation style (e.g., simpler language for younger students), or add more Slack channels to route questions by subject. The escalation threshold can be tuned by editing the condition in the If node.

🧠 Browsing History Automation Analyzer – Automation Toolkit (Google Sheets + AI) This n8n workflow analyzes your browsing history to identify opportunities for automation. It reads history from a Google Sheet, groups visits by domain, filters out irrelevant entries, and uses AI to recommend what can be automated — including how and why. 📌 What It Does 📄 Reads your browsing history from Google Sheets 🌐 Groups history by domain 🚫 Filters out common non-actionable domains (e.g., YouTube, Google) 🤖 Uses AI to analyze whether your activity on each site is automatable 💡 Provides suggestions including what to automate, how to do it, and which tools to use 📝 Saves results into a new tab in the same Google Sheet 🔍 Searches for n8n workflow templates related to the suggested automation 📊 Demo Sheet Input + output are handled via the following Google Sheet: 📎 Spreadsheet: View on Google Sheets Sheet: history** → Input browsing history Sheet: automations** → Output AI automation suggestions 🧠 AI Analysis Logic The AI agent receives each domain's browsing history and responds with: domain: The website domain automatable: true/false what_to_automate: Specific actions that can be automated reason: Why it's suitable (or not) for automation tool: Suggested automation tool (e.g., n8n, Apify) automation_rating: High, Medium, Low, or Not Automatable n8n_template: Relevant automation template (if found) 🔧 Technologies Used | Tool | Purpose | |--------------------------|-------------------------------------| | n8n | Workflow automation | | LangChain AI Agent | AI-based analysis | | Google Sheets Node | Input/output data handling | | OpenRouter (LLM) | Language model for intelligent reasoning | | JavaScript Code Node | Grouping and formatting logic | | Filter Node | Remove unwanted domains | | HTTP Request Node | Search n8n.io templates | 💻 Chrome History Export You can use this Chrome extension to export your browsing history in a format compatible with the workflow: 🔗 Export Chrome History Extension 📧 Want Personalized Automation Advice? If you'd like personalized automation recommendations based on your browsing history—just like what this workflow provides—feel free to contact me directly: > 📩 msaidwolfltd@gmail.com I'll help you discover what tasks you can automate to save time and boost productivity. 🚀 Example Use Cases Automate daily logins to dashboards Auto-fill forms on repetitive websites Schedule data exports from web portals Trigger reminders based on recurring visits Discover opportunities for scraping and integration 📜 License This workflow is provided as-is for educational and personal use. For commercial or customized use, contact the author.

✅ What problem does this workflow solve? Missed return pickups create logistics delays, extra follow-ups, and unhappy customers for e-commerce teams. This workflow automates return pickup reminders, ensuring customers are notified on the day of pickup via WhatsApp messages and automated voice calls, without any manual effort. ⚙️ What does this workflow do? Runs automatically on a daily schedule. Reads return pickup data from Google Sheets. Identifies customers with: 📅 Pickup date = today ⏳ Status = Pending Sends personalized WhatsApp reminders. Places automated voice call reminders when required. Updates reminder status in Google Sheets for clear tracking. 🧠 How It Works – Step by Step 1. ⏰ Scheduled Trigger The workflow starts at a fixed time every day (e.g., 9–10 AM) using a Schedule Trigger. 2. 📄 Read Pickup Data from Google Sheets It fetches rows from Google Sheets where: Pickup Date** = today Status** = Pending This ensures only relevant pickups are processed. 3. 🔁 Loop Through Pickups Each matching row is processed individually to send customer-specific reminders. 4. ✍️ Generate Personalized Messages Using a Code node, the workflow creates: 📲 A WhatsApp text message 📞 A voice message script Messages include: Customer name Product name Pickup address Return reason Pickup timing reminder 5. 📲 Send WhatsApp Reminder A personalized WhatsApp message is sent via Twilio, reminding the customer to keep the package ready. 6. 📞 Place Voice Call Reminder If required, the workflow places an automated voice call using Twilio and reads out a clear pickup reminder using text-to-speech. 7. ✅ Update Pickup Status Once notifications are sent: The workflow updates the Status column to “Reminder Sent” Ensures the same pickup is not notified again 📊 Sample Google Sheet Columns | Order ID | Customer Name | Phone Number | Product | Pickup Date | Address | Return Reason | Status | |--------|----------------|--------------|---------|-------------|---------|---------------|--------| 🔧 Integrations Used Google Sheets** – Pickup data source and tracking Twilio WhatsApp API** – Message delivery Twilio Voice API** – Automated call reminders n8n Schedule + Logic Nodes** – Automation orchestration 👤 Who can use this? Perfect for: 🛒 E-commerce brands 📦 Reverse logistics teams 🚚 Delivery & pickup operations 🧑‍💼 Customer support teams It also works well for service visits, deliveries, appointments, and field operations. 💡 Key Benefits ✅ Fewer missed pickups ✅ Improved customer compliance ✅ Reduced manual follow-ups ✅ Clear tracking in Google Sheets ✅ Scalable and fully automated 🚀 Ready to Use? Just connect: ✅ Google Sheets with pickup data ✅ Twilio credentials (WhatsApp + Voice) ✅ Schedule trigger time

📒 Generate Product Requirements Document (PRD) and test scenarios form input to PDF with OpenRouter and APITemplate.io This workflow generates a Product Requirements Document (PRD) and test scenarios from structured form inputs. It uses OpenRouter LLMs (GPT/Claude) for natural language generation and APITemplate.io for PDF export. Who’s it for This template is designed for product managers, business analysts, QA teams, and startup founders who need to quickly create Product Requirement Documents (PRDs) and test cases from structured inputs. How it works A Form Trigger collects key product details (name, overview, audience, goals, requirements). The LLM Chain (OpenRouter GPT/Claude) generates a professional, structured PRD in Markdown format. A second LLM Chain creates test scenarios and Gherkin-style test cases based on the PRD. Data is cleaned and merged using a Set node. The workflow sends the formatted document to APITemplate.io to generate a polished PDF. Finally, the workflow returns the PDF via a Form Completion node for easy download. ⚡ Requirements OpenRouter API Key (or any LLM) APITemplate.io account 🎯 Use cases Rapid PRD drafting for startups. QA teams generating test scenarios automatically. Standardized documentation workflows. 👉 Customize by editing prompts, PDF templates, or extending with integrations (Slack, Notion, Confluence). Need Help? Ask in the n8n Forum! Happy Automating with n8n! 🚀