Workflow Templates

Who’s it for Teams that care about space-weather impact—SRE/infra, satellite ops, aviation, power utilities, researchers—or anyone who wants timely, readable alerts when NASA publishes significant solar events. How it works / What it does Every 30 minutes a Cron trigger runs, the NASA DONKI node fetches the past 24 hours of space-weather notifications, and a code step de-duplicates, labels event types, and assigns a severity (CRITICAL / HIGH / OTHER). A Switch routes items: CRITICAL/HIGH** → an LLM (“AI Agent”) produces a concise Japanese alert → Slack posts with local time and source link. OTHER** → an LLM creates a short summary for record-keeping → a small merge step prepares fields → Google Sheets appends a new row. Sticky notes in the canvas explain the schedule, data source, and overall flow. How to set up Add credentials for Slack, Google Sheets, and OpenAI (or compatible LLM). Open the Slack nodes and select your workspace + target channel. Select your Google Sheet and worksheet for logging. (Optional) Adjust the Cron interval and the NASA lookback window. Test with a manual execution, then activate. Requirements Slack Bot with permission to post to the chosen channel Google account with access to the target Sheet OpenAI (or API-compatible) credentials for the LLM nodes Internet access to NASA DONKI (no API key required) How to customize the workflow Tweak severity rules inside the Analyze & Prioritize code node. Edit prompt tone/length in each AI Agent node. Change Slack formatting or mention style (@channel vs none). Add filters (e.g., alert only on CME/FLR) or extend logging fields in the merge step.

Managing contracts manually is time-consuming and prone to human error, especially when documents need to be shared, tracked, and stored across different tools. This workflow automates the entire process by capturing contract PDFs and Words uploaded to Slack, extracting key information with GPT, and organizing the data into a structured format inside Google Sheets. Essential fields such as client, service provider, contract value, and important dates are automatically parsed and logged, eliminating repetitive manual entry. Once the data is saved, a confirmation message is posted back to Slack so your team can quickly verify that everything has been recorded accurately. Who’s it for This workflow is ideal for operations teams, legal departments, or growing businesses that manage multiple contracts and want to maintain accuracy without spending hours on administration. By integrating Slack, GPT, and Google Sheets, you gain a simple but powerful contract management system that reduces risk, improves visibility, and keeps everyone aligned. Instead of scattered files and manual spreadsheets, you have a single automated pipeline that ensures your contract data is always up to date and accessible. How it works The workflow is triggered when a contract in PDF or Word format is shared in the designated Slack channel. The uploaded file is automatically retrieved for processing. Its content is extracted and converted into plain text. If the file is not in PDF or Word format, an error message is sent. GPT interprets the extracted text and structures the essential fields (e.g., Client, Service Provider, Effective Date, Expiration Date, Signature Date, Contract Value). The structured contract information is appended as a new row in the contract tracker spreadsheet on Google Sheets. A summary of the saved data is posted back to Slack for quick validation. How to set up You need to import this workflow into your n8n instance. You must authenticate your Slack account and select the target channel for contract submissions. You should link your Google account and specify the spreadsheet where the contract data will be stored. In this template, the required columns are Client, Service Provider, Effective Date, Expiration Date, Signature Date, and Contract Value. You can adjust the GPT parsing prompt to match the specific fields that your organization requires. You upload a sample contract in PDF or Word format to Slack and verify that the extracted data is correctly recorded in Google Sheets. Requirements You must have an active n8n instance in the cloud. You need a Slack account with permission to upload files and send messages. You must use a Google Sheets account with edit access to the target spreadsheet. You need a GPT integration (e.g., OpenAI) to enable AI-powered text parsing. How to customize the workflow You can modify this workflow to fit your organization’s unique contract needs. For example, you may update the GPT parsing prompt to capture additional fields, change the target Google Sheets structure, or integrate notifications into other tools. You have full flexibility to expand or simplify the steps so the workflow matches your team’s processes and compliance requirements.

How It Works This template is an n8n workflow that integrates with Jira to provide automated replies. When a ticket is assigned to a user, the workflow analyzes the ticket content, retrieves relevant knowledge from a vector database, and generates a response. By continuously enriching the knowledge base, the system improves response quality in Jira. Prerequisites A Jira account with API access A Pinecone account and credentials (API key and environment settings) An AI provider credential (e.g., OpenAI API key) Setup Instructions Jira Credentials Create Jira credentials in n8n (API token and email). In the Jira node, select the registered Jira account ID. Vector Database Setup (Pinecone) Register your Pinecone credentials (API key and environment variables) in n8n. Ensure that your knowledge base is indexed in Pinecone. AI Assistant Node Configure the OpenAI (or other LLM) node with your API key. Provide a system prompt that explains how to respond to Jira tickets using retrieved knowledge. Workflow Execution The workflow runs only via the Scheduled Trigger node at defined intervals. When Jira tickets are assigned, their summary, description, and latest comments are retrieved. These details are passed to the AI assistant, which queries Pinecone and generates a response. The generated response is then posted as a Jira comment. Step by Step Scheduled Trigger The workflow is executed at regular intervals using the Scheduled Trigger node. Jira Trigger (Issue Assigned) Retrieves the summary, description, and latest comments of assigned tickets. AI Assistant Sends ticket details to the AI assistant, which searches and summarizes relevant knowledge from Pinecone. Response Generation / Ticket Update The AI generates a response and automatically posts it as a Jira comment. (Optionally, the workflow can update the ticket status or mention the assignee.) Notes Keep your Pinecone knowledge base updated to improve accuracy. You can customize the AI assistant’s behavior by adjusting the system prompt. Configure the Scheduled Trigger frequency carefully to avoid API rate limits. Further Reference For a detailed walkthrough (in Japanese), see this article: 👉 Automating Jira responses with n8n, AI, and Pinecone (Qiita) You can find the template file on GitHub here: 👉 Template File on GitHub

AI Blog & LinkedIn Content Publisher How it works Daily trigger scans your Notion database for unpublished blog ideas AI generates complete blog posts + engaging LinkedIn content using OpenAI (Blog Posting is not implemented yet) Creates custom images for posts using Replicate's Flux-Schnell AI model Auto-publishes to LinkedIn with image OR emails draft for review Updates Notion with published content and tracks status Set up steps Connect accounts: Notion, OpenAI, Replicate, LinkedIn, Gmail Create 2 Notion databases: Ideas (input) and Articles (output) Update config node: Add your database IDs and email Test with one idea: Run manually first to verify everything works Enable daily automation: Turn on the cron trigger Perfect for: Content creators, developers, and marketers who want to transform rough ideas into professional blog posts and LinkedIn content automatically.

Instantly access live Bybit Spot Market data in Telegram! This workflow integrates the Bybit REST v5 API with Telegram and optional GPT-4.1-mini formatting, delivering real-time crypto market insights such as latest prices, order books, trades, and candlesticks — all presented in clean, structured Telegram messages. 🔎 How It Works A Telegram Trigger node listens for incoming user requests. User Authentication checks the Telegram ID against an allowlist. A Session ID is created from chat.id for lightweight memory across interactions. The Bybit AI Agent orchestrates multiple API requests via HTTP nodes: Latest Price & 24h Stats (/v5/market/tickers?category=spot&symbol=BTCUSDT) Order Book Depth (/v5/market/orderbook?category=spot&symbol=BTCUSDT&limit=50) Best Bid/Ask Snapshot (from order book top levels) Candlestick Data (Klines) (/v5/market/kline?category=spot&symbol=BTCUSDT&interval=15&limit=200) Recent Trades (/v5/market/recent-trade?category=spot&symbol=BTCUSDT&limit=100) Utility Nodes process and format the response: Calculator → computes spreads, mid-prices, % changes. Think → transforms JSON into human-readable reports. Simple Memory → stores symbol, sessionId, and previous inputs. Message Splitter ensures responses over 4000 characters are broken into chunks. Final results are sent back to Telegram in structured, readable format. ✅ What You Can Do with This Agent Get real-time Bybit prices & 24h statistics. Retrieve spot order book depth and liquidity snapshots. Analyze candlesticks (OHLCV) across multiple timeframes. View recent trades for market activity. Monitor bid/ask spreads & mid-prices with calculated values. Receive Telegram-ready reports, cleanly formatted and auto-split when long. 🛠️ Setup Steps Create a Telegram Bot Use @BotFather to create a bot and get a token. Configure in n8n Import Bybit AI Agent v1.02.json. Update the User Authentication node with your Telegram ID. Add your Telegram API credentials (bot token). Add OpenAI API key (Optional) Add Bybit API key if you want AI-enhanced formatting. Deploy and Test Activate the workflow in n8n. Send a message like BTCUSDT to your bot. Instantly receive Bybit Spot data inside Telegram. 📺 Setup Video Tutorial Watch the full setup guide on YouTube: ⚡ Unlock Bybit Spot Market insights in Telegram — fast, structured, and API-key free. 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn

How it works: This template turns rows in a Google Sheet into polished newsletter drafts in Notion using an AI writing agent. You click Execute workflow in n8n. It fetches all rows marked N8n Status = Pending, generates a draft from Newsletter Title and About the Newsletter, creates a Notion page, writes the full draft, then flips the sheet row to Done before moving to the next one. Before you start (use your own credentials): Create and select your credentials in n8n: Google Sheets (OAuth2 or Service Account) with access to the target spreadsheet. Notion (Internal Integration) with access to the target database. OpenAI (API Key) for the Chat Model. Replace any placeholders in nodes: Spreadsheet ID/URL and sheet/tab name (e.g., newsletter). Notion Database ID / Parent and any page or block IDs used by HTTP Request nodes. OpenAI model name if you prefer a different model. Give the Notion integration access to the database (Share → Invite the integration). Do not hard-code secrets in nodes. Store them in n8n Credentials. Step-by-step: Manual Trigger Start the run with When clicking ‘Execute workflow’. Fetch pending input (Google Sheets → Get row(s) in sheet) Read the newsletter tab and pull only rows where N8n Status = Pending. Iterate (Split In Batches → Loop Over Items) Process one sheet row at a time for stable memory use and pacing. Generate the newsletter (AI Agent + OpenAI Chat Model) AI Agent loads the “System Role Instructions” that define style, sections, and format. Pass Newsletter Title and About the Newsletter to the OpenAI Chat Model to produce the draft. Create a Notion page (Notion → Create Page) Create a page in your Newsletter Automation database with the page title set from Newsletter Title. Prepare long content for Notion (Code) Split the AI output into \~1,800-character chunks and wrap as Notion paragraph blocks to avoid payload limits. Write content blocks to Notion (HTTP Request → UpdateNotionBlock) Send a PATCH request to append all generated blocks so the full draft appears on the page. Mark the sheet row as done (Google Sheets → Update row in sheet) Update N8n Status = Done for the processed Newsletter Title. Continue the loop Return to Split In Batches for the next pending row until none remain. Tools integration: Google Sheets** — input queue and status tracking (Pending → Done) OpenAI** — LLM that writes the draft from provided fields Notion** — destination database for each draft page n8n Code + HTTP Request** — chunking and Notion API block updates Want auto-runs? Add a Cron trigger before step 2 and keep the flow unchanged.

Instantly fetch live Gate.io Spot Market data directly in Telegram! This workflow integrates the Gate.io REST v4 API with GPT-4.1-mini-powered AI and Telegram, giving traders real-time access to price action, order books, candlesticks, and trade data. Perfect for crypto traders, analysts, and DeFi builders who need fast and reliable exchange insights. ⚙️ How It Works A Telegram bot listens for user queries (e.g., "BTC_USDT"). The workflow securely processes the request, authenticates the user, and attaches a sessionId. The Gate AI Agent orchestrates data retrieval via Gate.io Spot Market API, including: ✅ Latest Price & 24h Stats (/spot/tickers) ✅ Order Book Depth (with best bid/ask snapshots) ✅ Klines (candlesticks) for OHLCV data ✅ Recent Trades (up to 100 latest trades) Data is optionally cleaned using Calculator (for spreads, midpoints, % changes) and Think (for formatting). An AI-powered formatter (GPT-4.1-mini) structures results into Telegram-friendly reports. The final Gate.io Spot insights are sent back instantly in HTML-formatted Telegram messages. 💡 What You Can Do with This Agent This AI-driven Telegram bot enables you to: ✅ Track real-time spot prices for any Gate.io pair ✅ Monitor order book depth (liquidity snapshots) ✅ View recent trades for activity insights ✅ Analyze candlesticks across multiple intervals ✅ Compare bid/ask spreads with calculated metrics ✅ Get clean, structured data without raw JSON clutter 🛠️ Setup Steps Create a Telegram Bot Use @BotFather on Telegram to create a bot and obtain an API token. Configure Telegram API Credentials in n8n Add your bot token under Telegram API credentials. Replace the placeholder Telegram ID in the Authentication node with your own. Import & Deploy Workflow Load Gate AI Agent v1.02.json into n8n. Configure your OpenAI API key for . Configure your Gate api key. Save and activate the workflow. Run & Test Send a query (e.g., "BTC_USDT") to your Telegram bot. Receive instant Gate.io market insights formatted for easy reading. 📺 Setup Video Tutorial Watch the full setup guide on YouTube: ⚡ Unlock real-time Gate.io Spot Market insights directly in Telegram — fast, clean, and reliable. 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn

This n8n workflow automates the process of creating high-quality, scroll-stopping LinkedIn posts based on live research, AI insight generation, and Google Sheets storage. Instead of relying on recycled AI tips or boring summaries, this system combines real-time trend discovery via Perplexity, structured idea shaping with GPT-4, and content generation tailored to a bold, human LinkedIn voice. The workflow saves each post idea (with image prompt, tone, and summary) to a Google Sheet, sends you a Telegram alert, and even formats your content for direct publishing. Perfect for solopreneurs, startup marketers, or anyone who posts regularly on LinkedIn and wants to sound original, not robotic. Who’s it for Content creators and solopreneurs building an audience on LinkedIn Startup teams, PMs, and tech marketers looking to scale thought leadership Anyone tired of generic AI-generated posts and craving structured, edgy output How it works Daily trigger at 6 AM starts the workflow. Pulls recent post history from Google Sheets to avoid repeated ideas. Perplexity AI scans the web Generates 3 structured post ideas (including tone, hook, visual prompt, and summary). GPT-4 refines each into a bold, human-style LinkedIn post, following detailed brand voice rules. Saves everything to Google Sheets (idea, content, image prompt, post status). Sends a Telegram notification to alert you new ideas are ready. How to set up Connect your Perplexity, OpenAI, Google Sheets, and Telegram credentials. Point to your preferred Google Sheet and sheet tab for storing post data. Adjust the schedule trigger if you want more or fewer ideas per week. (Optional) Tweak the content style prompt to match your personal tone or niche. Requirements Perplexity API account OpenAI API access (GPT-4 or GPT-4-mini) Telegram bot connected to your account Google Sheets document with appropriate column headers How to customize the workflow Change the research sources or prompt tone (e.g., more tactical, more spicy, more philosophical) Add an image generation tool to turn prompts into visuals for each post Filter or tag ideas based on type (trend, tip, story, etc.) Post automatically via LinkedIn API or Buffer integration

🚀 AI Marketing Campaign Generator Upload product image + details → Get complete professional marketing campaign with 5 custom-generated assets automatically. 🤖 AI Model GPT-4o Mini (OpenAI) - For campaign strategy | Prompt Image generation GPT Image-1 (OpenAI) - For visual asset generation 🔑 Required API Keys OpenAI API - AI analysis & image generation Google Drive API - Asset storage & organization 🎯 What It Generates 5 Marketing Assets: Instagram Post, Instagram Story, Website Banner, Ad Creative, Testimonial Graphic Brand Strategy: Colors, tone, positioning from your product image Campaign Strategy: Messaging, target audience, objectives Visual Analysis: Extracts colors, materials, styling from uploaded image ⚙️ Setup Import JSON to n8n Add OpenAI & Google Drive credentials Configure Google Drive folder for asset storage Deploy form webhook Test with product image upload 📱 How It Works Upload product image → AI analyzes visual + text → Generates complete campaign → Creates 5 custom marketing assets → Saves to Google Drive

How it works This workflow automates customer feedback management by capturing reviews through a form, analyzing them with AI for sentiment and insights, and then creating structured tasks across Monday.com, ClickUp, and HubSpot. It ensures that customer concerns are categorized, prioritized, and assigned to the right teams with actionable metadata. Step-by-step Trigger & Input The workflow starts when a customer submits the Feedback Form containing their Name, Message, Rating, and Product/Service. The submitted data is pre-processed with a Code node to cleanly extract fields for analysis. AI Analysis & Processing The extracted review is sent to OpenAI GPT-4 for analysis. AI identifies sentiment, sentiment score, category (e.g., product, service, support, delivery, pricing), department, priority, required actions, keywords, and suggested response tone. A Data Processing node enriches the output with due dates, task titles, structured descriptions, and fallback handling in case of parsing issues. Structured Output Generation An AI Agent and OpenAI Chat model transform the enriched data into a strict JSON format that is compatible with Monday.com, ClickUp, and HubSpot. This ensures consistent field order, formatting, and metadata for all downstream integrations. Task Creation in Platforms The structured task data is automatically pushed to: Monday.com → Creates an item in a specified board. ClickUp → Creates a task with mapped fields and priority. HubSpot → Creates an engagement task in CRM with due date and priority. Benefits Automates end-to-end customer feedback analysis and task creation. Ensures structured, AI-driven insights for actionable responses. Reduces manual work in categorizing and assigning reviews. Keeps customer feedback synchronized across multiple platforms (Monday.com, ClickUp, HubSpot). Improves response time by prioritizing high-impact feedback with due dates.

Automating WhatsApp replies in Go High Level with Redis and Anthropic Description Integrates GHL + Wazzap with Redis and an AI Agent using ClientInfo to process messages, generate accurate replies, and send them via a custom field trigger. Who’s it for This workflow is for businesses using GoHighLevel (GHL), including the Wazzap plugin for WhatsApp, who want to automate inbound SMS/WhatsApp replies with AI. It’s ideal for teams that need accurate, data-driven responses from a predefined ClientInfo source and want to send them back to customers without paying for extra inbound automations. How it works / What it does Receive message in n8n via Webhook from GHL (Customer Replied (SMS) automation). WhatsApp messages arrive the same way using the Wazzap plugin. Filter message type: If audio → skip processing and send fallback asking for text. If text → sanitize by fixing escaped quotes, escaping line breaks/carriage returns/tabs, and removing invalid fields. Buffer messages in Redis to group multiple messages sent in a short window. Run AI Agent using the ClientInfo tool to answer only with accurate service/branch data. Sanitize AI output before sending back. Update GHL contact custom field (IA_answer) with the AI’s response. Send SMS reply automatically via GHL’s outbound automation triggered by the updated custom field. How to set up In GHL, create: Inbound automation: Trigger on Customer Replied (SMS) → Send to your n8n Webhook. Outbound automation: Trigger when IA_answer is updated → Send SMS to the contact. Create a custom field named IA_answer. Connect Wazzap in GHL to handle WhatsApp messages. Configure Redis in n8n (host, port, DB index, password). Add your AI model credentials (Anthropic, OpenAI, etc.) in n8n. (Optional) Set up the Google Drive Excel Merge sub-workflow to enrich ClientInfo with external data. Requirements GoHighLevel sub-account API key**. Anthropic (Claude)** API key or another supported LLM provider. Redis database** for temporary message storage. GHL automations: one for inbound messages to n8n, one for outbound replies when **IA\_answer is updated. GHL custom field: **IA\_answer to store and trigger replies. Wazzap plugin** in GHL for WhatsApp message handling. How to customize the workflow Add more context or business-specific data to the AI Agent prompt so replies match your brand tone and policies. Expand the ClientInfo dataset with additional services, branches, or product details. Adjust the Redis wait time to control how long the workflow buffers messages before replying.

How It Works User sends a reminder request via Telegram (e.g., “Remind me to clean the garage tomorrow at 12 pm”). The request is parsed by AI Agent and stored in Airtable with a unique reminder code. The reminder workflow checks Airtable at scheduled intervals and sends a Telegram notification when the reminder is due. Each reminder includes a unique cancel code (e.g., Reply 4936 to stop this reminder). If the user replies with the code, the bot searches Airtable, deletes the reminder, and confirms the deletion in Telegram. If the code doesn’t exist, the bot replies “Code not found.” ⚡ Setup Steps Create a Telegram Bot Use BotFather on Telegram. Run /newbot and copy your bot token. Add the token in your Telegram Trigger and Telegram Send nodes in n8n. Set Up Airtable Create an Airtable base called REMINDER-TABLE. Add a table with fields: title (Text) – reminder text due_at (Date/Time) – when the reminder is due chat_id (Text) – user’s Telegram chat ID code (Number/Text) – unique cancel code Generate an API key / Personal Access Token and connect it in n8n. Import This Workflow In n8n, click Import Workflow. Paste the JSON template. Connect your Telegram and Airtable credentials. Activate the Workflow Start the workflow in n8n Cloud or Self-Hosted. Send a test reminder in Telegram (e.g., “Remind me in 5 minutes to call mom”). When notified, reply with the cancel code to test deletion. Optional Customizations Modify reminder frequency (Every 5 minutes node). Change reminder message formatting in the Format Message node. Add logging/analytics by connecting Google Sheets or another DB. ⚡ Result: You now have a fully automated AI-powered Telegram Reminder Bot with Airtable storage, cancel codes, and real-time notifications!