Workflow Templates

How It Works This workflow automates multilingual audio content creation for content creators, educators, and marketing teams distributing materials globally. It solves the challenge of producing high-quality, translated audio content at scale without manual intervention. Starting with source text, the system translates content into English, Spanish, French, and German using AI translation services, validates translation quality through automated scoring, generates natural-sounding audio using ElevenLabs text-to-speech technology, calculates audio metrics for quality assurance, combines all language versions into a single package, uploads to Google Drive for centralized storage, and sends Slack notifications for team collaboration. The workflow eliminates weeks of manual translation and voice recording work while maintaining consistent quality across all language variants. Setup Steps Configure AI translation service credentials for multilingual processing Add ElevenLabs API key and select voice models for each target language Set quality threshold scores for translation validation gates Connect Google Drive with designated folder for audio storage Configure Slack webhook for team notifications with custom message Prerequisites AI translation API access (OpenAI/DeepL), ElevenLabs account with sufficient character quota Use Cases E-learning course localization, podcast multilingual distribution Customization Add additional languages, modify quality score thresholds Benefits Reduces content localization time by 95%, eliminates voice talent costs

AI Complaint Mining & Insight Extraction This n8n template automates complaint mining from unstructured text sources and turns raw user feedback into clear, actionable insights. It uses AI to identify recurring complaints, pain points, and themes, helping teams understand what users are unhappy about and why. Who’s it for Product managers identifying recurring user pain points Customer support and success teams Founders validating product-market fit issues UX researchers analyzing qualitative feedback Anyone dealing with large volumes of complaints or negative feedback How it works / What it does Trigger The workflow starts with a manual trigger, form submission, or imported text source containing user complaints. Data Preparation Raw complaint text is cleaned, normalized, and split into individual complaint entries. Ensures consistent input for AI processing. AI Complaint Analysis An AI model analyzes each complaint to identify: Core issue Complaint category Emotional tone Severity or urgency Pattern Detection Complaints are grouped by similarity to uncover recurring issues and themes. Highlights the most frequent and impactful problems. Insight Extraction AI summarizes key insights such as: Top recurring complaints Root causes Suggested improvement areas Structured Output Results are converted into structured data fields. Ready to be stored, visualized, or shared with stakeholders. Storage & Reporting Extracted complaints and insights are saved to a table or sheet for easy review and analysis. This workflow transforms unstructured complaint data into a clear feedback loop you can act on. How to set up Import the template into your n8n workspace. Connect your AI model credentials (OpenAI or Gemini). Define your input source (text, form, or file). Connect your storage destination (Google Sheets, Data Table, or database). Run the workflow to start mining complaints automatically. Requirements n8n account (cloud or self-hosted) AI model provider (OpenAI or Gemini) Storage destination (Google Sheets, Data Table, or database) How to customize the workflow Adjust complaint categories and severity scoring. Add sentiment analysis or emotion classification. Connect a vector database to track complaints over time. Trigger alerts when critical issues are detected. Generate dashboards or weekly complaint summaries automatically. 👉 This template helps you turn complaints into insights — and insights into product improvements.

Who’s it for This template is designed for podcasters, researchers, educators, product teams, and support teams who work with audio content and want to turn it into searchable knowledge. It is especially useful for users who need automated transcription, structured summaries, and conversational access to audio data. What it does / How it works This workflow starts with a public form where users upload an audio file. The audio is sent to AssemblyAI for speech-to-text processing, including speaker labels and bullet-point summarization. Once transcription is complete, the full text is converted into a document, split into chunks, and embedded using Google Gemini. The embeddings are stored in a Pinecone vector database along with metadata, making the content retrievable for future use. In parallel, the workflow logs uploaded file information into Google Sheets for tracking. A separate chat trigger allows users to ask questions about the uploaded audio files. An AI agent retrieves relevant context from Pinecone and responds using Gemini, enabling conversational search over audio transcripts. Requirements AssemblyAI API credentials Google Gemini (PaLM) API credentials Pinecone API credentials Google Sheets OAuth2 credentials A Pinecone index for storing audio embeddings How to set up Connect AssemblyAI, Gemini, Pinecone, and Google Sheets credentials in n8n. Configure the Pinecone index for storing transcripts. Verify the Google Sheet has columns for file name and status. Test by uploading an audio file through the form. Enable the workflow for continuous use. How to customize the workflow Change summary style or transcript options in AssemblyAI Adjust chunk size and overlap for better retrieval Add email or Slack notifications after processing Extend the chatbot to support multiple knowledge bases

Transform articles into children's audiobooks and comics via Telegram & BrowserAct This workflow acts as an AI Storyteller. Send an article link to your Telegram bot, and it will rewrite the content into an engaging children's story, generate a multi-panel comic book visualization, produce a narrated audiobook using ElevenLabs, and deliver the entire multimedia package back to your chat. Target Audience Parents, educators, and content creators looking to repurpose existing articles into kid-friendly, engaging formats. How it works Analyze Intent: The workflow receives a message via Telegram. An AI Agent classifies it: is it a casual chat or a story request (a link)? Fetch Content: If a link is detected, BrowserAct scrapes the text from the target webpage. Creative Production: A "Scriptwriter" AI Agent (using OpenRouter/Gemini) rewrites the article into a whimsical children's story, generates scene descriptions for a comic book, and drafts a social media caption. Generate Audio: ElevenLabs converts the story text into a narrated MP3 file. Generate Visuals: The workflow loops through the AI-generated scene descriptions, using Google Gemini to create comic book-style images for each part of the story. Deliver: The bot sends the audiobook, the comic panels, and the story text to your Telegram chat. How to set up Configure Credentials: Connect your Telegram, BrowserAct, ElevenLabs, Google Gemini, and OpenRouter accounts in n8n. Prepare BrowserAct: Ensure the Children’s Book Storytelling & Illustration template is saved in your BrowserAct account. Configure Telegram: Ensure your bot is created via BotFather and the API token is added to the Telegram credentials. Select Voice: Open the Convert text to speech node and choose a suitable narrator voice from ElevenLabs. Activate: Turn on the workflow. Test: Send an article link to your bot to start the storytelling process. Requirements BrowserAct* account with the *Children’s Book Storytelling & Illustration** template. ElevenLabs** account. Telegram** account (Bot Token). Google Gemini* & *OpenRouter** accounts. How to customize the workflow Change Art Style: Modify the system prompt in the Scriptwriter agent to request a different visual style (e.g., "Watercolor," "Pixel Art," or "Disney Style"). Adjust Story Tone: Update the Scriptwriter prompt to change the target age group or genre (e.g., "Spooky Ghost Story" or "Sci-Fi Adventure"). Add PDF Export: Add a PDF node to compile the text and images into a downloadable eBook file. Need Help? How to Find Your BrowserAct API Key & Workflow ID How to Connect n8n to BrowserAct How to Use & Customize BrowserAct Templates

This n8n workflow automatically generates a comprehensive dataset of 50 AI search prompts tailored to a specific company. It combines AI-powered company research with structured prompt generation to create monitoring queries for tracking brand visibility across AI search engines like ChatGPT, Perplexity, Claude, and Gemini. The dataset is ready for use and can be uploaded to any major AI search analytics platforms (like ALLMO.ai,...) or used in your own model. Who's it for & Use Cases SEO/GEO Marketing teams, Growth Managers, GTM engineers and Founders who want to: Create custom prompt datasets for visibility tracking platforms like ALLMO.ai Generate industry-specific search queries for AI model monitoring How It Works Phase 1: Company Research Start the workflow via the form and input your company name and website URL GPT-5 Mini with web search collects company information, including buyer personas, key features, and value proposition Phase 2: Prompt Generation Claude Sonnet 4.5 generates and refines natural language prompts based on Phase 1 findings English prompts are automatically translated into German Phase 3: Export & Implementation Wait for processing (~total of 2-5 minutes depending on website complexity) English and German prompt sets are merged with metadata and structured into table format Download the CSV file containing 50 prompts ready for import into AI Search monitoring systems (allmo.ai, etc.) How to Setup Just enter your API credentials in the Claude and ChatGPT Nodes. How to Expand You can update the system prompts for the "prompt writing engine" to create more prompts. You can update or add more translations. Output Structure: 25 English prompts + 25 German prompts (can be changed flexibly). Each prompt tagged with: company name, industry, category, language, and AI model for simple tracking. Ready for direct import into any GEO/ALLMO visibility tracking system. Requirements API Credentials: Anthropic API (Claude Sonnet 4.5) OpenAI API (GPT-5 Mini with web search capability) Data Input: Valid company website URL (publicly accessible) Company name as it should appear in tracking

🧠 How it works This workflow automatically translates messages between Japanese and English inside Slack — perfect for mixed-language teams. In our real-world use case, our 8-person team includes Arif, an English-speaking teammate from Indonesia, while the rest mainly speak Japanese. Before using this workflow, our daily chat often included: “Can someone translate this for Arif?” “I don’t understand what Arif wrote — can someone summarize it in Japanese?” “I need to post this announcement in both languages, but I don’t know the English phrasing.” This workflow fixes that communication gap without forcing anyone to change how they talk. Built with n8n and Google Gemini 2.5 Flash, it automatically detects the input language, translates to the opposite one, and posts the result in the same thread, keeping every channel clear and contextual. ⚙️ Features Unified translation system with three Slack triggers: 1️⃣ Slash Command /trans – bilingual posts for announcements. 2️⃣ Mention Trigger @trans – real-time thread translation for team discussions. 3️⃣ Reaction 🇯🇵 / 🇺🇸 – personal translation view for readers. Automatic JA ↔ EN detection and translation via Gemini 2.5 Flash 3-second instant ACK to satisfy Slack’s response timeout Shared Gemini translation core across all three modes Clean thread replies using chat.postMessage 💼 Use Cases Global teams** – Keep Japanese and English speakers in sync without switching tools. Project coordination** – Use mentions for mixed-language stand-ups and updates. Announcements** – Auto-generate bilingual company posts with /trans. Cross-cultural communication** – Help one-language teammates follow along instantly. 💡 Perfect for Global companies** with bilingual or multilingual teams Startups** collaborating across Japan and Southeast Asia Developers** exploring Slack + Gemini + n8n automation patterns 🧩 Notes You can force a specific translation direction (JA→EN or EN→JA) inside the Code node. Adjust the system prompt to match tone (“business-polite”, “casual”, etc.). Add glossary replacements for consistent terminology. If the bot doesn’t respond, ensure your app includes the following scopes: app_mentions:read, chat:write, reactions:read, channels:history, and groups:history. Always export your workflow with credentials OFF before sharing or publishing. ✨ Powered by Google Gemini 2.5 Flash × n8n × Slack API A complete multilingual layer for your workspace — all in one workflow. 🌍

Title Japanese Document Translation Quality Checker with DeepL & Google Drive to Slack Who’s it for Localization teams, QA reviewers, and operations leads who need a fast, objective signal on Japanese document translation quality without manual checks. What it does / How it works This workflow watches a Google Drive folder for new Japanese documents, exports the text, translates JA→EN with DeepL, then back-translates EN→JA. It compares the original and back-translation to estimate a quality score and summarizes differences. A Google Docs report is generated, and a Slack message posts the score, difference count, and report link—so teams can triage quickly. How to set up Connect credentials for Google Drive, DeepL, and Slack. Point the Google Drive Trigger to your “incoming JP docs” folder. In the Workflow Configuration (Set) node, fill targetFolder (report destination) and slackChannel. Run once, then activate and drop a test doc. Requirements n8n (Cloud or self-hosted), Google Drive, DeepL, and Slack credentials; two Drive folders (incoming, reports). How to customize the workflow Tune the diff logic (character → token/line level, normalization rules), adjust score thresholds and Slack formatting, or add reviewer routing/Jira creation for low-score cases. Always avoid hardcoded secrets; keep user-editable variables in the Set node.

Why use this? This workflow turns any event-related text into a new event on your calendar. Poster for a concert you want to go to? Snap a photo [with your iPhone] and boom city, it's in your calendar. † Parent-Teacher conference you can't forget? Forward that email to the webhook. † Appointment card from the doctor? Snap it in, baby! † How it works (Very, very simple) Data received by webhook. Ai Agent prompted to parse the text into structured event data. Create event in NextCloud cal (or Zoho, or GoogleCal). (Optional, intended use case) Set up the iOS Shortcut (linked in workflow) to turn your iPhone into the trigger for this workflow. Say "Siri, Add Event To Calendar," and she opens the camera, OCRs the text in the photo and sends that to the webhook. Boom city. Expected input structure [ { "body": { "cal": "work", <- this is optional for deciding among calendars "eventInfo": "Join us for Betty-Jean's 98th birthday! (Yes, we celebrate every year now...) It's October 11th at 2:30pm, at Betty-Jean's house. Come after lunch 'cause her kitchen hasn't been used in 20 years. She mellows out pretty early these days so plan for the party to end by 4:00pm." } } ] Extras Includes multiple calendar nodes.** Whether you're using NextCloud, Zoho or Google Cal, you can swap in the node you need. iOS Shortcut linked in workflow.** I also set up a Shortcut for the iPhone. The first time you use the Shortcut, you'll need to give it some permissions, and paste in your production webhook URL. Expansion option: Accept images**. iPhone has a native OCR feature but this isn't always an option. To make this workflow more versatile, consider building out a second branch to send an image to an Agent to parse the event data from the image directly. Expansion option: Multiple triggers**. You could add more triggers to receive event-related text from other sources, like an IMAP node reading your email (pro tip: set up a designated folder and give the IMAP access only to that folder). † Workflow begins with a webhook which can receive correctly-formatted data from anywhere on the web --- mailhook, webform, iOS Shortcut, etc. Direct data to this webhook from your source of text to use this workflow.

📋Instant Proposal Generator Automatically convert sales call transcripts into professional client proposals by extracting key details with AI, dynamically populating Google Slides templates, and tracking progress in Airtable, all in one seamless workflow. 🎯 What does this workflow do? This end-to-end automation creates client-ready proposals by: Taking call transcripts via chat interface The AI analyzes the transcript to extract key details like company name, goals, budget, and requirements, then structures this data as JSON for seamless workflow integration. Generating customized documents using Google Slides template with dynamic variables, Auto populating {Company_Name}, {Budget}, etc. from extracted data. Delivering finished proposals: Sharing final document with client, and Updating CRM status automatically. ⚙️ How it works User input: Paste call transcript in chat trigger node AI analysis: OpenAI node processes text to extract structured JSON, Identifies company name, goals, budget, requirements, etc. Document copy: it copies the file from Google Drive, and name it {company name} proposal. Variables replacement: Replaces all template variables ({Company_Name}, {Budget}, etc.) with extracted data from ChatGPT. Delivery & tracking: Shares finalized proposal with client via email, an Updates Airtable "Lead Status" to "Proposal Sent". 🔑 Required setup OpenAI API Key: Create a key from here Google Cloud Credentials: Setup here Required scopes: Google Slides edit + file creation Airtable Access Token: Create one from here

This n8n template automates your customer support workflow by connecting Gmail, OpenAI, Supabase, and Slack. It listens for new incoming emails, classifies them using AI, routes them to the appropriate Slack channel based on category (e.g., support or new requests), logs each thread to Supabase for tracking, and marks the email as read once processed. Good to know • The OpenAI API is used for automatic email classification, which incurs a small per-request cost. See OpenAI Pricing for up-to-date info. • You can easily expand the categories or connect more Slack channels to fit your workflow. • The Supabase integration ensures you don’t process the same thread twice. How it works Gmail Trigger checks for unread emails. Supabase Get Row verifies if the thread already exists. If it’s a new thread, the OpenAI node classifies the email into categories such as “support” or “new-request.” The Switch node routes messages to the correct Slack channel based on classification. Supabase Create Row logs thread details (sender, subject, IDs) to your database. Finally, the Gmail node marks the message as read to prevent duplication. How to use • The workflow uses a manual Gmail trigger by default, but you can adjust the polling frequency. • Modify category names or Slack channels to match your internal setup. • Extend the workflow to include auto-replies or ticket creation in your CRM. Requirements • Gmail account (with OAuth2 credentials) • Slack workspace (with channel access) • OpenAI account for classification • Supabase project for storing thread data Customizing this workflow Use this automation to triage incoming requests, route sales leads to specific teams, or even filter internal communications. You can add nodes for auto-responses, CRM logging, or task creation in Notion or ClickUp.

YNAB Super Budget Ever wish that Y.N.A.B was just a little smarter when auto-categorizing your transactions? Now you can supercharge your YNAB budget with ChatGPT! No more manual categorization. Setup Get a YNAB Api Key Get YNAB Budget ID & Account ID (They are part of the URL) https://app.ynab.com/BUDGETID/accounts/ACCOUNTID Additional information Every transaction that this workflow modifies will be tagged with n8n and color yellow. You can easily review all changes by selecting just that tag. Customization By default it pulls transactions from the last 30 days. This workflow will post a message in a discord channel showing which transactions it modified and what categories it chose. Discord notifications are optional. Considerations YNAB allows for 200 api calls per hour. If you have more than 200 Uncategorized transactions, consider reducing the previous_days value.

This n8n template demonstrates how to automatically convert voice messages from Telegram into structured, searchable notes in Google Docs using AI transcription and intelligent tagging. Use cases are many: Try capturing ideas on-the-go while walking, recording meeting insights hands-free, creating voice journals, or building a personal knowledge base from spoken thoughts! Good to know OpenAI Whisper transcription costs approximately $0.006 per minute of audio ChatGPT tagging adds roughly $0.001-0.003 per message depending on length The workflow supports both German and English voice recognition Text messages are also supported - they bypass transcription and go directly to AI tagging Perfect companion: Combine with the "Weekly AI Review**" workflow for automated weekly summaries of all your notes! How it works Telegram receives your voice message or text and triggers the workflow An IF node intelligently detects whether you sent audio or text content For voice messages: Telegram downloads the audio file and OpenAI Whisper transcribes it to text For text messages: Content is passed directly to the next step ChatGPT analyzes the content and generates up to 3 relevant keywords (Work, Ideas, Private, Health, etc.) A function node formats everything with Swiss timestamps, message type indicators, and clean structure The formatted entry gets automatically inserted into your Google Doc with date, keywords, and full content Telegram sends you a confirmation with the transcribed/original text so you can verify accuracy How to use Simply send a voice message or text to your Telegram bot - the workflow handles everything automatically The manual execution can be used for testing, but in production this runs on every message Voice messages work best with clear speech in quiet environments for optimal transcription Requirements Telegram Bot Token and configured webhook OpenAI API account for Whisper transcription and ChatGPT tagging Google Docs API access for document writing A dedicated Google Doc where all notes will be collected Customising this workflow Adjust the AI prompt to use different tagging categories relevant to your workflow (e.g., project names, priorities, emotions) Add multiple Google Docs for different contexts (work vs. private notes) Include additional processing like sentiment analysis or automatic task extraction Connect to other apps like Notion, Obsidian, or your preferred note-taking system And don't forget to also implement the complimentary workflow Weekly AI Review!