Workflow Templates

AI-Powered Automatic Timesheet Generator for Google Sheets Stop wasting billable hours on manual time-tracking. AutoTimesheet Pro uses AI to collect emails, meetings, and GitHub work, then writes a clean timesheet straight into Google Sheets. Perfect for developers, consultants, agencies, and remote teams. 🚀 Key Features Automated Google Sheets time-tracking** — zero spreadsheet prep. AI-generated activity summaries** (≤ 120 chars) via OpenAI GPT-4o-mini. Gmail integration** — logs only important emails, skipping newsletters & no-replies. Google Calendar time logger** — captures confirmed events, duration, and attendees. GitHub commit & PR tracker** — records your commits plus opened/closed PRs. Daily 7 PM cron trigger** (easily adjustable). Month-based sheet creation** — new tab spins up on the first run each month. No-code n8n template* — just connect credentials and tweak one *Set Variables** node. 🔌 Easily extensible** — drag-and-drop extra n8n nodes to add Slack, Jira, Notion, Asana, Trello, Toggl, or any other data source you need. 🔍 How It Works Collect — n8n pulls data from Gmail, Google Calendar, and chosen GitHub repos. Clean — filters remove noise (newsletters, irrelevant commits, etc.). Condense — OpenAI rewrites each item into a concise, SEO-friendly description. Write — workflow appends Date, Type, and Description to your Timesheet Google Sheet. Extend — simply insert new n8n nodes (e.g., Slack, Notion, Jira) and merge them into the same pipeline. 📈 Benefits for SEO-Minded Professionals Keyword-rich activity log** improves internal search and reporting. Structured data** in Sheets simplifies export to accounting or PM tools. Consistent naming** (CALENDAR_EVENT, EMAIL, COMMIT, PR) makes analytics easy. ✅ Why Choose AutoTimesheet Pro? Zero manual entry — just open the sheet and bill clients. Immediate visibility into where your hours went. Works with any GitHub repo list and any inbox you own. 100 % no-code setup — activate in minutes. Built on n8n, so you can customize and scale without limits. 📥 Get Started Ready to replace manual time-tracking with smart automation? https://n8n.partnerlinks.io/ds9podzjls6d Join N8N now, connect your Google & GitHub accounts, and let AI handle your daily log.

In this workflow, we'll automate the export of all the submissions which have a total score greater than 15 for a final review on Trello. The workflow will also generate social media assets for the organizers and add them to the Trello card.

v1 Helper ℹ️ This workflow is to be run after upgrading to n8n v1. This workflow returns all locations where a node in an active workflow contains a parameter using an expression extension affected by v1 changes. For every location, please check that the workflow still behaves as intended.

This n8n workflow template allows you to write WordPress posts by just providing a few keywords. It uses AI technology to write the text and to create the post's featured image. The text includes an introduction, chapters, and conclusions. Each chapter is written independently and this allows you to create also very long articles. The workflow uses technologies provided by Open AI: Chat GPT for the text and Dall-E for the image. I suggest reviewing the created posts before publishing them on your WordPress website. The article generation might take some minutes as each chapter is created independently. Features Easy to use:** Easy web interface to start the generation of the WordPress post AI-powered:** Text and image generation is done by artificial intelligence Long-text ready:** Possibility to create very long articles Configurable:** Possibility to provide as many keywords as you want, to choose the number of chapters and the length of the article Plugs into your WordPress:** Easily integrates with your WordPress website Tweak it as you want:** Fine-tune the Open AI prompts and the workflow as you want Workflow Steps User form:** An n8n form is used to trigger the post creation Settings:** This node is used to set your WordPress URL (which is used later in the workflow) Article structure:** First AI action that writes the introduction, the conclusions, and the chapter structure. Data check:** Check that the data provided by the AI is valid Chapters split/Chapters text:** Splits the data for each chapter in a separate item and generates each chapter's text with AI Content preparation:** Prepares the text for posting merging the introduction, the chapters, and the conclusions. Adds some basic HTML formatting Draft on WordPress:** Creates the draft post on WordPress Featured image:** Creates a featured image and adds it to the post on WordPress User feedback:** Sends a feedback to the user on the n8n form Getting Started To deploy and use this template: Import the workflow into your n8n workspace Set your WordPress URL in the wordpress_url field in the "Settings" node. Include the slash (/) at the end of the URL Set up your Open AI n8n credentials by following this guide. The Open AI credentials are used by the Open AI nodes ("Create post title and structure", "Create chapters text", and "Generate featured image") Set up your WordPress n8n credentials by following this guide. The WordPress credentials are used by the WordPress and HTTP Request nodes ("Post on Wordpress", "Upload media", and "Set image ID for the post"). Pay attention that the "Password" in the WordPress credentials is not the user's password by the Application Password How use the workflow to create a WordPress post Activate the workflow Open the "Form" node and copy the "Production URL". This is the public URL of the form to AI-write the post Open the URL in a browser and fill in the form Wait a few minutes till you get the feedback in the form that the post was created Go to WordPress and check the newly created draft post. Review and publish your post!

Overview This n8n workflow automates the creation of 9:16 aspect ratio images optimized for short-form video content and thumbnails. It integrates multiple tools to retrieve content, generate scripts, and create AI-generated imagery. Key Features Trigger Workflow Manually The workflow starts when triggered manually in n8n. Retrieve Brand Guidelines Fetch brand elements like style, tone, and guidelines from Airtable. SEO Keywords and Blog Post Retrieval Retrieves blog posts and associated SEO keywords from Airtable to form the basis of image content. Content Preparation Uses GPT-4 to prepare a 4-scene script and thumbnail prompts for short-form videos. AI Image Generation Uses Leonardo.ai API to generate: Thumbnail Images Scene-specific Images (9:16 Aspect Ratio) Airtable Asset Management Generated assets (images) are saved back into Airtable with metadata like URLs and file sizes. Tools and Integrations n8n**: Workflow automation platform. OpenAI**: Generates scripts and prompts (GPT-4O-MINI). Leonardo.ai**: AI tool for improving prompts and generating high-quality images. Airtable**: Used as a data source for brand guidelines, blog posts, and to store generated assets. Workflow Steps Manual Trigger Initiate the workflow. Retrieve Brand and SEO Guidelines Fetch essential brand elements like tone, style, and keywords. Filter and Fetch Blog Content Search for blog posts relevant to selected SEO keywords. Script Preparation Use GPT-4 to generate a script with image prompts for scenes and thumbnails. Image Generation Call Leonardo.ai to create: Scene Images in 9:16 Aspect Ratio. A Thumbnail Image with an improved prompt. Store Assets Save generated assets (images) to Airtable for future use. Workflow Structure Nodes Breakdown: Manual Trigger**: Start the workflow. Get Brand Guidelines**: Pull brand-related information (style, tagline, tone, etc.) from Airtable. Set Guidelines**: Prepare fetched data. Get SEO Keywords**: Retrieve keywords to filter relevant content. Keyword Filter*: Filter results for specified keywords (e.g., *"AI Automation"). Script Prep**: Generate 4-scene scripts and prompts with GPT-4. Leo - Improve Prompt**: Improve image prompts for clarity and detail. Leo - Generate Image**: Create AI-generated images for scenes and thumbnails. Wait Nodes**: Ensures Leonardo image generation is complete. Add Asset Info**: Store the generated images back into Airtable with metadata. API Credentials Required Ensure the following credentials are configured in n8n: OpenAI API Key Leonardo.ai API Key Airtable API Token Output Generated Images**: High-quality AI-generated images with a 9:16 aspect ratio. Saved Metadata**: Asset details (URLs, sizes, types) stored in Airtable. Usage Import this workflow into n8n. Set up your Airtable API, Leonardo.ai API, and OpenAI API credentials. Run the workflow manually. Monitor image generation and check the Airtable output for results. Tags OpenAI** RunwayML** Leonardo** Airtable** Video Automation** Author AlexK1919 AI-Native Workflow Architect More Workflow Templates YouTube Channel Connect with Alex

Check Legal Regulations: This workflow involves scraping, so ensure you comply with the legal regulations in your country before getting started. Better safe than sorry! 📌 Purpose This workflow enables automated and AI-driven topic monitoring, delivering concise article summaries directly to a Slack channel in a structured and easy-to-read format. It allows users to stay informed on specific topics of interest effortlessly, without manually checking multiple sources, ensuring a time-efficient and focused monitoring experience. To get started, copy the Google Sheets template required for this workflow from here. 🎯 Target Audience This workflow is designed for: Industry professionals** looking to track key developments in their field. Research teams** who need up-to-date insights on specific topics. Companies** aiming to keep their teams informed with relevant content. ⚙️ How It Works Trigger: A Scheduler initiates the workflow at regular intervals (default: every hour). Data Retrieval: RSS feeds are fetched using the RSS Read node. Previously monitored articles are checked in Google Sheets to avoid duplicates. Content Processing: The article relevance is assessed using OpenAI (GPT-4o-mini). Relevant articles are scraped using Jina AI to extract content. Summaries are generated and formatted for Slack. Output: Summaries are posted to the specified Slack channel. Article metadata is stored in Google Sheets for tracking. 🛠️ Key APIs and Nodes Used Scheduler Node:** Triggers the workflow periodically. RSS Read:** Fetches the latest articles from defined RSS feeds. Google Sheets:** Stores monitored articles and manages feed URLs. OpenAI API (GPT-4o-mini):** Classifies article relevance and generates summaries. Jina AI API:** Extracts the full content of relevant articles. Slack API:** Posts formatted messages to Slack channels. This workflow provides an efficient and intelligent way to stay informed about your topics of interest, directly within Slack.

This workflow automates the process of sending text-to-speech (TTS) voice calls using API. It allows users to submit a form with the message content, recipient's phone number, voice type, and language, and then sends a voice call with the provided text. This workflow is a simple yet powerful way to automate text-to-speech voice calls using API. It’s ideal for notifications, reminders, or any scenario where voice communication is needed. Below is a breakdown of the workflow: 1. How It Works The workflow is designed to send voice calls with text-to-speech functionality. Here's how it works: Form Submission: The workflow starts with a Form Trigger node, where users submit a form with the following fields: Body: The text message to be converted to speech (max 600 characters). To: The recipient's phone number (including the international prefix, e.g., +39xxxxxxxxxx). Voice: The voice type (male or female). Lang: The language for the voice call (e.g., en-us, it-it, fr-fr, etc.). Once the form is submitted, the workflow is triggered. Send Voice Call: The Send Voice node sends a POST request to the ClickSend API (https://rest.clicksend.com/v3/voice/send). The request includes: The text message (Body) to be converted to speech. The recipient's phone number (To). The voice type (Voice). The language (Lang). Machine detection is enabled to detect if the call is answered by a machine. The API processes the request and initiates a voice call to the specified number, where the text is read aloud by the selected voice. Outcome: The recipient receives a voice call, and the submitted text is read aloud in the chosen voice and language. 2. Set Up Steps To set up and use this workflow in n8n, follow these steps: Register on ClickSend: Go to ClickSend and create an account. Obtain your API Key and take advantage of the 2 € free credits provided. Configure ClickSend API in n8n: In the Send Voice node, set up HTTP Basic Authentication: Username: Use the username you registered with on ClickSend. Password: Use the API Key provided by ClickSend. Set Up the Form Trigger: The Form Trigger node is pre-configured with fields for: Body: The text message to be converted to speech. To: The recipient's phone number. Voice: Choose between male or female voice. Lang: Select the language for the voice call. Customize the form fields if needed (e.g., add more languages or voice options). Test the Workflow: Submit the form with the required details (text, phone number, voice, and language). The workflow will send a voice call to the specified number, and the recipient will hear the text read aloud. Optional Customization: Modify the workflow to include additional features, such as: Adding more languages or voice options. Sending multiple voice calls in bulk. Integrating with other APIs or services for advanced use cases.

Supabase AI Agent with RAG & Multi-Tenant CRUD Version: 1.0.0 n8n Version: 1.88.0+ Author: Koresolucoes License: MIT Description A stateful AI agent workflow powered by Supabase and Retrieval-Augmented Generation (RAG). Enables persistent memory, dynamic CRUD operations, and multi-tenant data isolation for AI-driven applications like customer support, task orchestration, and knowledge management. Key Features: 🧠 RAG Integration: Leverages OpenAI embeddings and Supabase vector search for context-aware responses. 🗃️ Full CRUD: Manage agent_messages, agent_tasks, agent_status, and agent_knowledge in real time. 📤 Multi-Tenant Ready: Supports per-user/organization data isolation via dynamic table names and webhooks. 🔒 Secure: Role-based access control via Supabase Row Level Security (RLS). Use Cases Customer Support Chatbots: Persist conversation history and resolve queries using institutional knowledge. Automated Task Management: Track and update task statuses dynamically. Knowledge Repositories: Store and retrieve domain-specific information for AI agents. Instructions 1. Import Template Go to n8n > Templates > Import from File and upload this workflow. 2. Configure Credentials Add your Supabase and OpenAI API keys under Settings > Credentials. 3. Set Up Multi-Tenancy (Optional) Dynamic Webhook Path**: Replace the default webhook path with /mcp/tool/supabase/:userId to enable per-user routing. Table Names**: Use a Set Node to dynamically generate table names (e.g., agent_messages_{{userId}}). 4. Activate & Test Enable the workflow and send test requests to the webhook URL. Tags AI Agent RAG Supabase CRUD Multi-Tenant OpenAI Automation Screenshots License This template is licensed under the MIT License.

This n8n workflow sets up a smart home assistant using OpenAI and Homey integration. It uses LangChain agent tools to allow natural language queries (in Norwegian) to trigger workflows for controlling lights, curtains, temperature, TVs, and other devices across different rooms (e.g., living room, bedroom, cinema). The system uses tool-based workflows connected to specific smart home actions and responds in Norwegian. It’s designed to be modular and easily extended with new devices or capabilities.

Create a Branded AI Website Chatbot Engage website visitors with an intelligent chat widget powered by OpenAI. This template includes: 💬 Natural conversation handling 📅 Microsoft Outlook calendar integration 📝 Lead capture and information gathering 🔄 Human handoff capabilities Simply add a JavaScript snippet to your website and configure the workflow to match your needs. Follow our detailed setup guide to get started in minutes. > Note: Widget includes a "Powered By" affiliate link

This workflow performs basic XOR-based encryption and decryption using a custom password. It is intended to be triggered by another workflow and processes structured input in JSON format. Input Structure The workflow expects a single array of objects with the following fields: action-type: either "encrypt" or "decrypt" key: the password used for encryption and decryption data: the content to encrypt or decrypt Example: Encryption Input [ { "action-type": "encrypt", "key": "Password", "data": "Hello, this is a secret message" } ] Example: Decryption Input [ { "action-type": "decrypt", "key": "Password", "data": "ChwGAQceF15eE2QXFRcUagxGVgV8TBoNBA4VQVoQZkwVUhImU1FTEg==" } ] Output The output returns an array of results, each containing either the encrypted string (base64 format) or the decrypted plain text. Use Case This workflow is useful for simple internal message encoding, data obfuscation, or testing purposes. It is not recommended for securing sensitive or personal data, as XOR encryption is not cryptographically secure. The workflow logic is written in JavaScript using n8n Function nodes, without any external dependencies.

Unlock adaptive, context-aware AI chat in your automations—no coding required! This template is a plug-and-play n8n workflow that transforms how your chatbots, support agents, and knowledge systems respond to users. Powered by Google Gemini and a Qdrant vector database, it automatically classifies every incoming query and applies a tailor-made strategy for Factual, Analytical, Opinion, or Contextual requests—delivering the right answer, every time. 🛠️ Key Features Automatic Query Classification: Seamlessly detects whether the user wants facts, a deep analysis, opinions, or context—then routes each input to the best answering strategy. Four Dynamic Retrieval Modes: 1) Factual: Delivers precise, accurate information 2) Analytical: Breaks down complex topics for deep dives 3) Opinion: Surfaces diverse viewpoints and perspectives 4) Contextual: Connects the dots using implied or user-specific context End-to-End RAG Pipeline: Uses Gemini to classify and answer, while Qdrant powers fast, smart knowledge retrieval. No-Code Visual Editing: Import into n8n, connect your LLM and vector database credentials, and you’re live—customize, extend, and scale with zero backend code. Reusable in Any Project: Perfect for customer support, research, onboarding bots, internal knowledgebases, or any adaptive AI chat interface. 🚀 How it Works 1) User submits a query (via chat or API) 2) Query is auto-classified as Factual, Analytical, Opinion, or Contextual 3) Adaptive retrieval strategy is triggered (each with its own prompt logic and memory buffer) 4) Smart knowledge search is performed using Gemini and Qdrant 5) Response is generated and sent back to the user—tailored to the query type! 🧩 What’s Included Full n8n workflow (.json) Step-by-step setup instructions Sample prompts and system messages for each strategy Lifetime updates (as the workflow evolves) 💡 Use Cases Chatbots that adapt to every user’s intent Internal/external FAQ and helpdesk automations AI research and summarization agents Product support and onboarding flows Any scenario where smarter, more relevant answers = better user experience Ready to build smarter automations? Import this template, connect your Gemini & Qdrant accounts, and let your AI agent adapt to every conversation.