Workflow Templates

This free n8n automation helps anyone—from busy parents to entrepreneurs—get a daily SMS summary of their calendar events. It’s a personal assistant that gives you a heads up of what your day will look like. Great for: starting your day cognizant of the day's events, or for the neurodivergent. Example use case: Parent receives a text summarizing the Family Calendar events at 5AM. Its a reminder of a child's doctor appointment at 1PM and soccer practice at 430PM. The AI then ends the message on an uplifting note. Good to Know Requires user to buy a Twilio phone number to send SMS from. Each message, at the time of writing, is $0.083 CAD. Requires basic knowledge of Google Cloud Console for the activation of Google Calendar API How it Works Every morning at 7AM, your workflow checks Google Calendar for the day’s events. It formats your schedule into a friendly, easy-to-read summary using your favorite AI model (any LLM works—Anthropic, OpenAI, Gemini, etc). That summary is texted directly to your phone via Twilio as a personal daily reminder. How to Use Copy this n8n workflow into your own instance. Hook up your Google Calendar and Twilio accounts. You can choose the specific calendar in the Calendar node. Choose or swap in any AI model you prefer to personalize your summaries. I find Claude sounds the most natural. Enjoy your daily, cheerful calendar digest by SMS at 7AM! Requirements A Google Cloud account (to activate the Calendar API and get credentials—see Google documentation). Twilio account (for sending SMS—get started with Twilio’s easy setup). Any LLM API account (optional, but recommended for polite/friendly summaries). Customize this flow Change SMS times to fit your morning routine. Adjust message formatting for your style or brand. Swap LLM services, tweak prompts, or combine multiple calendars—whatever works for you. Reach out anytime at ralleyreminders.com if you have questions or want to share ideas!

Create LinkedIn Post from Telegram Voice or Text Message with AI Image Who's it for This workflow is perfect for busy professionals, content creators, and marketers who want to publish polished LinkedIn posts without spending time on formatting or design. Send a quick text or voice message via Telegram, and get a fully formatted LinkedIn post with a relevant AI-generated image, post it immediately on LinkedIn. Example use cases: Entrepreneurs sharing business insights on the go without opening LinkedIn Marketers creating consistent content during commutes or between meetings Thought leaders turning quick voice notes into professional posts with visuals How it works / What it does Receive text or voice messages through a Telegram bot. Transcribe voice messages using OpenAI's audio transcription. Transform raw input into a professional LinkedIn post using AI formatting (proper structure, tone, and character limits). Generate a relevant image prompt based on post content. Create an AI image that matches the post topic. Automatically publish the complete post (text + image) to LinkedIn. How to set up Create a Telegram bot via @BotFather and obtain your API token. For self-hosted n8n users: Create a LinkedIn app at developer.linkedin.com to get OAuth credentials (Client ID and Client Secret). Add the OpenAI API key, LinkedIn OAuth credentials, and Telegram API to n8n. Assign your credentials to the Telegram, OpenAI, and LinkedIn nodes. Deploy and activate the workflow. Send a text or voice message to your Telegram bot and watch it create and post to LinkedIn! Requirements Telegram Bot Token OpenAI API Key LinkedIn OAuth credentials n8n instance (cloud or self-hosted) How to customize the workflow Modify the LinkedIn Post Text prompt to match your personal writing style or brand voice. Adjust image generation settings (model, size, style) in the Create Image node. Add approval steps by routing posts to Google Sheets, Airtable, or Notion before publishing. Create a second workflow to schedule approved posts for specific times. Limitations and Usage Tips Input Clarity**: Voice messages should be clear and well-articulated for accurate transcription. LinkedIn Character Limits**: The AI formatter optimizes posts for 1,242-2,500 characters. API Costs**: Each post generation uses OpenAI API calls for transcription (if voice), text formatting, image prompt creation, and image generation. Monitor your usage to manage costs. LinkedIn Rate Limits**: LinkedIn API has posting frequency limits. Avoid bulk posting in short time periods to prevent rate limiting.

Voice-to-Ideas: Auto-Transcribe Telegram Voice Notes to Google Sheets Who it's for Creators, entrepreneurs, writers, and anyone who wants to capture ideas quickly without typing. This workflow is ideal for storing thoughts, content ideas, brainstorms, reminders, or voice memos on the go. What it does This workflow listens for Telegram voice messages, sends the audio to OpenAI Whisper for transcription, and saves the raw text directly into a Google Sheet. No formatting or additional processing is applied. The exact transcription from the audio is stored as-is. How it works A Telegram Trigger detects when you send a voice message to your bot. The Telegram node downloads the audio file. OpenAI Whisper transcribes the voice note into text. The raw transcription is appended to Google Sheets along with the current date. Requirements Telegram bot token (created via BotFather) OpenAI API key with Whisper transcription enabled Google Sheets credentials connected in n8n A Google Sheet with two columns: Notes (stores the transcription text) Date (timestamp of the voice note) Setup steps Create a Telegram bot with BotFather and connect Telegram credentials in n8n. Add your OpenAI API key to the OpenAI node. Connect Google Sheets credentials in n8n. Create a Google Sheet with two columns: Notes and Date. Send a voice message to your Telegram bot to test the workflow.

This n8n template provides a comprehensive suite of ElevenLabs audio processing capabilities through the KIE.AI API. The workflow includes three independent audio processing workflows: speech-to-text transcription, text-to-speech generation, and audio isolation. Each workflow can be used independently or combined to create complete audio processing pipelines. Use cases are many: Transcribe audio files to text with speaker diarization, convert text to natural-sounding speech audio, isolate and clean audio by removing background noise, create complete audio processing pipelines from transcription to speech generation, automate podcast transcription and audio enhancement, generate voiceovers from text content, clean up recordings by removing unwanted audio elements, create accessible content by converting text to audio, or process audio files in batch for content creation workflows! Good to know The workflow includes three independent ElevenLabs audio processing capabilities via KIE.AI API: Speech-to-Text: Transcribes audio to text with speaker diarization and audio event tagging Text-to-Speech: Converts text to natural-sounding speech with voice customization options Audio Isolation: Removes background noise and isolates audio sources Each workflow can be used independently or combined for complete audio processing pipelines Speech-to-text supports speaker diarization (identifying different speakers) and audio event tagging Text-to-speech supports multiple voices (Rachel, Adam, Antoni, Arnold, and more) with customizable stability, similarity boost, style, and speed Audio isolation removes background noise and separates audio sources for cleaner output KIE.AI pricing: Check current rates at https://kie.ai/ for audio processing costs Processing time: Varies based on audio length and KIE.AI queue, typically 10-30 seconds for text-to-speech, 30 seconds to 5 minutes for transcription and isolation Audio requirements: Files must be publicly accessible via URL (HTTPS recommended) Supported audio formats: MP3, WAV, M4A, FLAC, and other common audio formats Automatic polling system handles processing status checks and retries for all workflows How it works The template includes three independent workflows that can be used separately or combined: 1. Speech-to-Text Transcription: Audio URL Setup: Set the audio file URL in 'Set Audio URL' node Transcription Submission: Audio URL is submitted to KIE.AI API using ElevenLabs speech-to-text model with diarization and event tagging Processing Wait: Workflow waits 5 seconds, then polls the transcription status Status Check: Checks if transcription is complete, queuing, generating, or failed Polling Loop: If still processing, workflow waits and checks again until completion Text Extraction: Once complete, extracts the transcribed text from the API response 2. Text-to-Speech Generation: Text Input Setup: Set the text to convert to speech in 'Set Text Input' node Speech Generation Submission: Text is submitted to KIE.AI API using ElevenLabs text-to-speech multilingual v2 model Processing Wait: Workflow waits 5 seconds, then polls the generation status Status Check: Checks if audio generation is complete, queuing, generating, or failed Polling Loop: If still processing, workflow waits and checks again until completion Audio URL Extraction: Once complete, extracts the generated audio file URL from the API response 3. Audio Isolation: Audio URL Setup: Set the audio file URL in 'Set Audio URL 1' node Isolation Submission: Audio URL is submitted to KIE.AI API using ElevenLabs audio isolation model Processing Wait: Workflow waits 5 seconds, then polls the isolation status Status Check: Checks if audio isolation is complete, queuing, generating, or failed Polling Loop: If still processing, workflow waits and checks again until completion Isolated Audio URL Extraction: Once complete, extracts the isolated audio file URL from the API response All workflows automatically handle different processing states (queuing, generating, success, fail) and retry polling until processing is complete. Each workflow operates independently, allowing you to use only the features you need. How to use Setup Credentials: Configure KIE.AI API key as HTTP Bearer Auth credential (used for all three workflows) Choose Your Workflow: For Transcription: Update 'Set Audio URL' node with your audio file URL (must be publicly accessible) For Text-to-Speech: Update 'Set Text Input' node with your text content For Audio Isolation: Update 'Set Audio URL 1' node with your audio file URL (must be publicly accessible) Configure Voice Settings (Text-to-Speech only): Adjust voice, stability, similarity_boost, style, and speed in 'Submit Text for Speech Generation' node Deploy Workflow: Import the template and activate the workflow Trigger Processing: Use manual trigger to test, or replace with webhook/other trigger Receive Output: Get transcribed text, generated audio URL, or isolated audio URL depending on which workflow you use Pro tip: You can use these workflows independently or chain them together. For example, transcribe audio to text, then convert that text to speech with a different voice, or isolate audio first, then transcribe the cleaned audio. Ensure your audio files are hosted on public URLs (HTTPS recommended) for best results. The workflows automatically handle polling and status checks, so you don't need to worry about timing. For text-to-speech, experiment with voice settings - higher stability (0.7-1.0) creates more consistent voice, while higher similarity boost (0.7-1.0) makes the voice more similar to the original. Requirements KIE.AI API** account for accessing ElevenLabs audio processing models Audio File URL** (for transcription and isolation) that is publicly accessible (HTTPS recommended) Text Input** (for text-to-speech) to convert to speech n8n** instance (cloud or self-hosted) Supported audio formats: MP3, WAV, M4A, FLAC, or other formats supported by KIE.AI Customizing this workflow Workflow Selection: Use only the workflows you need by removing or disabling nodes for transcription, text-to-speech, or audio isolation. Each workflow operates independently. Trigger Options: Replace the manual trigger with webhook trigger for API-based audio/text submission, schedule trigger for batch processing, or form trigger for user uploads. Voice Customization (Text-to-Speech): Modify voice, stability, similarity_boost, style, and speed parameters in 'Submit Text for Speech Generation' node to fine-tune voice characteristics. Experiment with different voices (Rachel, Adam, Antoni, Arnold, etc.). Transcription Options: Adjust diarization and audio event tagging settings in 'Submit Audio for Transcription' node to customize transcription output. Workflow Chaining: Connect workflows together - transcribe audio to text, then convert that text to speech, or isolate audio first, then transcribe the cleaned audio. Batch Processing: Add loops to process multiple audio files or text inputs from a list or spreadsheet automatically. Storage Integration: Add nodes to save transcribed text, generated audio, or isolated audio to Google Drive, Dropbox, S3, or other storage services. Post-Processing: Add nodes after audio generation to download audio files, convert formats, apply additional audio filters, or integrate with video editing tools. Error Handling: Add notification nodes (Email, Slack, Telegram) to alert when processing completes, fails, or encounters errors. Content Management: Add nodes to log transcriptions, track audio processing results, or store outputs in databases or spreadsheets. Multi-Language Support: For text-to-speech, add language detection or selection before conversion for multilingual content creation. Audio Quality Enhancement: Chain multiple audio processing steps - isolate audio, then transcribe, or transcribe, then generate speech with different voices.

How it works This workflow automatically handles new Google reviews by generating AI-powered replies and deciding how to respond based on rating. Positive reviews are replied to instantly, while lower ratings are routed for manual approval via Slack. It ensures fast engagement without losing control over sensitive responses. The process runs continuously using a real-time trigger. Step-by-step Capture new reviews** Fetch New Reviews – Triggers when a new review is posted in Google Business Profile. Edit Fields – Extracts and formats reviewer name, rating, and review text. Generate AI response** AI Agent – Creates a contextual, human-like reply based on the review content. Groq Chat Model – Powers the AI Agent with a language model for response generation. Decision and response handling** If – Checks if the review rating is positive (4 or 5 stars). Reply to review – Automatically posts reply for positive reviews. Send message and wait for response – Sends review + AI reply to Slack for approval if rating is lower. If1 – Checks whether the Slack response is approved. Reply to review1 – Posts the approved reply back to Google Business Profile. Why use this? Respond instantly to positive reviews and boost customer engagement Maintain control over sensitive or negative feedback with approval flow Save time by automating repetitive review responses Ensure consistent tone using AI-generated replies Improve brand reputation with faster, structured responses

Description Route captured signals to the right destination with one click. Set a signal’s Route Destination in Notion, and this workflow automatically creates a Jira ticket, backlog item, or customer health entry, then confirms in the original Slack thread. Context This is the action layer for the Signal Catcher. When you set a signal’s Route Status to “Routing” in Notion, this workflow picks it up, reads the Route Destination you selected, and executes the routing. 5 destinations are supported: Jira Bug, Jira Feature, RICE+ Backlog, Customer Health, and Sprint Backlog. After routing, it updates the signal status to “Routed” and replies in the original Slack thread to confirm. Who is this for? • PMs who triage signals and route to Jira or backlogs • Product Ops teams building end-to-end signal workflows • Engineering teams that need clean bug ticket creation Requirements • Notion account with Signal Stream database • Jira account (for bug/feature routing) • Slack Bot token How it works Trigger Polls Signal Stream in Notion for entries where Route Status = “Routing.” Routing Engine Reads signal details and routes via a 5-way switch based on your selected destination. Destination Actions Creates Jira issue, backlog item, or customer health entry with full signal context. Closed Loop Updates signal to “Routed” with a reference link. Replies in the original Slack thread. What you get • One-click signal routing from Notion • Automatic Jira ticket creation with full context • Slack thread confirmation for traceability • 5 configurable routing destinations

Setting Up and Generating TOTP Step 1: Receive QR Code and Extract the Link 1. Receive the QR Code from the 2FA service After enabling two-factor authentication (2FA) on services like OpenAI, Google, GitHub, etc., a QR Code will be given to you, which you need to scan. This QR Code contains the TOTP link used to generate one-time passcodes. 2. Extract the link from the received QR Code To extract the link from the QR Code, use online tools. These tools will help you extract the corresponding link. After using an online tool, the extracted link will appear in the following format: otpauth://totp/ServiceName:username?secret=secret_key&issuer=ServiceName For example: otpauth://totp/OpenAI:amir676080@gmail.com?secret=test-test-test&issuer=OpenAI Step 2: Create TOTP Credential in n8n Create a new Credential To use TOTP in n8n, you need to create a new TOTP Credential. Enter the details in the Credential In the Secret field:* Enter the *secret key** (extracted from the QR Code link). For example: test-test-test In the Label field:* Enter *ServiceName:username** For example: OpenAI:amir676080@gmail.com Save the Credential After entering the information, click Save to save the Credential. Step 3: Get the TOTP Code Click on Test Workflow After setting up the credentials in n8n, click on Test, and the corresponding code will be delivered to you. Output: [ { "token": "720769", "secondsRemaining": 18 } ] ==This code is exactly the same as the one generated by apps and services like Google Authenticator or Authy. 🔐== Contact me on [Telegram]: https://t.me/amir676080

This allows different routes to input into our agent (e.g. the retry branch). In the AI Agent, we can use a relative $json reference for data, since it's always the same input schema going in. . Place...

💬 GPT-5 Slack Impersonation Agent with RAG – Auto-Respond to Messages Using Live Project Docs Let AI handle your Slack conversations — and always have the right answer. This n8n workflow transforms GPT-5 into your on-brand Slack assistant, capable of responding as you in real-time while referencing a Google Docs RAG (Retrieval-Augmented Generation) document for accurate project updates. Watch step-by-step build like these on: https://www.youtube.com/@automatewithmarc Here’s how it works: Listens for Slack mentions or messages — triggered instantly when someone talks to you. Understands the conversation context using GPT-5 and conversation memory. Retrieves the latest project updates from your linked Google Doc via RAG. Responds in Slack as you — maintaining your tone, style, and workplace personality. Key Features & Benefits: 🧠 RAG-powered accuracy – Always pulls the latest info from your project docs. 🤖 GPT-5 natural conversation – Replies feel human, friendly, and context-aware. ⚡ Instant responses – No more message backlog or missed updates. 🎯 Impersonation mode – Sends replies under your Slack name for seamless collaboration. 🔄 Continuous conversation memory – Keeps track of what was said before. Ideal Use Cases: Acting as a stand-in during busy periods so no message goes unanswered. Project managers who want instant, document-backed answers. Customer support or client-facing roles needing quick, accurate replies. Included Integrations: Slack Trigger & Send Message – Listen and reply in real-time. GPT-5 Agent – Craft context-aware, on-brand responses. Google Docs Tool – Pull live data from your RAG document. Conversation Memory – Maintain context across messages. 💡 Pro Tip: Customize the system prompt to mimic your exact tone and integrate with multiple docs for broader knowledge coverage.

How It Works Generate the document structure based on the provided title or short description. Use prompt chaining to create detailed content for each section while maintaining consistent context. Append the final content to a Google Document for easy access and review. How to Use Open the submission form. Enter your title and word count. Click Submit to generate your Google Document link. Wait a few minutes — completed document will be ready at that link. Requirements OpenAI account** Google Docs account** Customization Options Adjust the document length by changing the word count input. Modify the prompt logic to control writing style or tone. Update the section structure to fit different document types (e.g., blog, report, proposal). Replace the output destination if you prefer another storage option instead of Google Docs.

🚀 Overview This modern n8n workflow implements a multi-agent trading engine that orchestrates valuation, sentiment, fundamentals, technicals, and macro analyses to generate a single portfolio action with built-in risk controls. It integrates Telegram for live commands, fetches market data, fans out to expert LLM agents, applies position limits via a Risk Manager, executes orders, logs to Notion, and sends a summary back to Telegram. 🔧 What It Does Telegram Trigger** listens for ticker commands and context inputs 📲 Market Data Node** fetches live prices and exchange rates from an API (no hardcoded keys) 🔗 LLM Agents** run parallel analyses: valuation, sentiment, macro, fundamentals, technicals 🌐 Risk Manager** enforces max position sizes, stop-loss limits, and confidence thresholds ⚖️ Portfolio Manager** aggregates signals into a final BUY/SELL/HOLD decision with allocation % 📊 Execute Order** sends trade requests via HTTP Request 🔒 Log to Notion** writes a full audit trail for compliance 📓 Telegram Output** posts a concise report with signals, risk notes, and final decision 📤 💡 Why It’s Useful This template illustrates a modular “investment committee” architecture that is easy to extend, swap agents, and maintain. It follows n8n’s best practices for template submissions: sticky-note documentation, placeholder credentials, markdown descriptions, and clear H2 headings. 🔑 Prerequisites Telegram Bot credentials configured in n8n Exchange or data API credentials stored as n8n Credentials (no inline keys) OpenAI (or other LLM) API credential Notion integration credentials 🛠️ How to Use Import the JSON into n8n and open the canvas. Read each Sticky Note for node-by-node setup tips and rate-limit guidance 🗒️ Configure credentials via the n8n Credentials Manager 🔐 Test each branch (data fetch, agents, risk logic) in isolation before enabling order execution ✅ 📐 Architecture Layers Trigger**: Telegram Trigger → Data**: HTTP Request → Analysis**: Parallel LLM Agents → Risk**: Risk Manager → Decision**: Portfolio Manager → Action**: Execute Order, Log to Notion, Send Telegram summary 🔒 Security & Maintenance All API keys are stored securely as credentials. Sticky Notes document required scopes, retry strategies, and error-handling paths to ensure observability and safe testing. Enjoy building and customizing your own AI-powered hedge-fund workflow!

How it works Fetch campaign & members from Salesforce. GPT‑4 auto‑writes a channel‑appropriate, personalised outbound message. Switch node sends via Twilio (SMS/WhatsApp), SMTP (Email). Mark each member as processed to avoid double‑touches. Error trigger notifies Slack if anything fails. Set‑up steps Time: ~10‑15 min once credentials are ready. Prereqs: Active Salesforce OAuth app, Twilio account, SMTP creds, Slack app. In‑flow sticky notes walk you through credential mapping, environment variables, and optional tweaks (e.g., campaign SOQL filter). > Copy the workflow, add your keys, and run a quick manual test—after that you can place it on a cron or Salesforce trigger.